GOAL ETHIOPIA

FINDINGS OF NUTRITION SURVEYBORANA ZONE-OROMIA REGION

JUNE 12th – 26th, 2000

JANE BLACKHURSTGOAL NUTRITIONIST

ADDIS ABABAJULY 2000

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ACKNOWLEDGEMENTS

I would like to thank to the following people for their help support and advicein the preparation and implementation of this survey.

All GOAL staff in Yabello, Addis Ababa and DublinThe Oromia DPPBBorana Zonal Health DepartmentThe Yabello and Teltele Emergency Task Force CommitteesYabello and Teltele Health Authorities

Extra Special thanks to Kerren Hedland – WFP for all her help with EPI –infoamong other things and to Colette Kirwin GOAL, my survey partner.

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LIST OF ABBREVIATIONS

CBR Crude Birth Rate

CDC Centre for Disease Control

CMR Crude Mortality Rate

DPPC Disaster Prevention and Preparedness Commission

GAM Global acute malnutrition (<-2 Z-scores W/H +/- oedema)

MoH Ministry of Health

MSF Médecins Sans Frontières

MUAC Mid-upper arm circumference

NCHS National Centre for Health Statistics

PA Peasant Association

SAM Severe acute malnutrition (<-3 Z-scores W/H +/- oedema)

UNHCR United Nations High Commission for Refugees

WFP World Food Programme

W/H/L Weight for height or length as a percentage of the median

WHO World Health Organisation

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TABLE OF CONTENTS

1.0 EXECUTIVE SUMMARY ...................................................................... 1

1.1 OBJECTIVES ........................................................................................... 11.2 METHODOLOGY ...................................................................................... 11.3 RESULTS................................................................................................ 2

1.3.1 Nutritional indices of children 6-59 months (65-110cm W/L/H)...... 21.3.2 Nutritional indices of a convenience sample of elderly people ...... 21.3.3 Food security................................................................................. 2

1.4 CONCLUSIONS ........................................................................................ 31.5 RECOMMENDATIONS ............................................................................... 3

2.0 INTRODUCTION AND BACKGROUND INFORMATION ....................................... 5

3.0 OBJECTIVES ........................................................................................... 5

4.0 METHODOLOGY ...................................................................................... 54.1 Sampling Method .............................................................................. 54.2 Sample size....................................................................................... 64.3 Sample Population............................................................................ 64.4 Data collected ................................................................................... 64.5 Team Composition ............................................................................ 74.6 Implementation ................................................................................. 7

5.0 RESULTS................................................................................................ 85.1 Demographic Distribution.................................................................. 85.2 Nutritional status by z-scores and percentage of the median............ 85.3 Levels of Malnutrition in the Elderly................................................. 105.4 Food security .................................................................................. 11

6.0 LIMITATIONS ......................................................................................... 15

7.0 CONCLUSIONS ...................................................................................... 15

8.0 RECOMMENDATIONS ............................................................................. 15

REFERENCES............................................................................................... 18

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LIST OF TABLES

TABLE 1 HOUSEHOLD DEMOGRAPHY ..........................................................................8

TABLE 2 DISTRIBUTION OF SAMPLE BY AGE AND SEX....................................................8

TABLE 3 NUTRITIONAL STATUS - CHILDREN 6-59 MONTHS OR 65-110CM W/L/H............8

TABLE 4 PREVALENCE OF MALNUTRITION BY AGE CATEGORY .......................................9

TABLE 5 PREVALENCE OF MALNUTRITION BY WOREDA ................................................9

TABLE 6 MEAN WEIGHT/LENGTH/HEIGHT BY WOREDA ..................................................9

TABLE 7 PREVALENCE OF GLOBAL MALNUTRITION BASED ON MAIN PRE- DROUGHT LIVELIHOOD STATUS ...................................................................................10

TABLE 8 PREVALENCE OF SEVERE ACUTE MALNUTRITION BASED ON MAIN PRE-DROUGHT LIVELIHOOD STATUS ...................................................................................10

TABLE 9 NUTRITIONAL STATUS OF THE ELDERLY BY MUAC MEASUREMENTS ..............10

TABLE 10 FOOD AID RECEIVED BY TYPE AND POPULATION COVERAGE ..........................11

TABLE 11 CEREAL SOURCES PRE-DROUGHT AND CURRENTLY......................................11

TABLE 12 MILK SOURCES PRE-DROUGHT AND CURRENTLY...........................................11

TABLE 13 LIVELIHOODS PURSUED IN PRE-DROUGHT YEARS .........................................12

TABLE 14 CURRENT SOURCES OF INCOME OR FOOD BY HOUSEHOLD ............................12

TABLE 15 LANDHOLDINGS PER HOUSEHOLD................................................................14

TABLE 16 MORTALITY RATES.....................................................................................14

TABLE 17 PERCENTAGE AND FREQUENCY OF REPORTED CHILD ILLNESSES ...................14

LIST OF APPENDICES

APPENDIX 1 MAP OF SURVEY AREA

APPENDIX 2 SURVEY QUESTIONNAIRES

APPENDIX 3 ANALYSIS OF MALNUTRITION BY CLUSTER

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1.0 Executive Summary

GOAL in collaboration with the Disaster Prevention and PreparednessCommission (DPPC) and Ministry of Health (MoH) conducted a baselinenutrition survey of the pastoral and agro-pastoral areas of Yabello and TelteleWoredas of Borana Administrative Zone, Oromia Regional State from June12-26th 2000.

1.1 Objectives

§ To quantify the nutritional status of children aged 6-59 months or between65-110cm in length in GOAL Ethiopia’s relief project areas of BoranaAdministrative Zone

§ To assess the nutrition status of people above 55 years old living in theproject area using MUAC measurements of a convenience sample in thesurvey area

§ To examine the current situation with regard to food security with particularfocus on the following:§ Aid coverage§ Food sources§ Effects of the drought on livelihood strategies§ Effects on health

1.2 Methodology

A two stage 30 cluster survey was conducted, based on a populationsampling frame of 18 peasant associations (PAs) (60 villages), 9 in Yabelloworeda and 9 in Teltele woreda. Standard UNHCR/WFP/MSF methodologywas followed. The sample size was calculated using the expected prevalenceof malnutrition for Teltele woreda of 35% (CARE, April 2000). Precision wascalculated at 3%, error risk at 5% and a design effect of 2. Weight, height,age, and presence or absence of oedema were recorded for 1,950 childrenaged between 6-59 months or with a length between 65-110cm.Anthropometric measurements were made by fully trained medical personnel.Results for weight and height index values are based on the ReferencePopulation Table of the NCHS/CDC/WHO 1982.

Mid-upper arm circumference measurements (MUAC) were taken on aconvenience sample of people aged above 55 years, who lived in thehousehold and were present at the time of interview.

A questionnaire was completed for each child and data were collected onvaccination and health history and child feeding. Household surveys wereconducted in 1,103 households and community interviews were carried out in49 villages. Data collected included: household size and composition; birthsand deaths in the previous 12 months; pre-drought and current livelihoodstrategies, food types and sources, livestock status and land resources.

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1.3 Results

1.3.1 Nutritional indices of children 6-59 months (65-110cm W/L/H)

Sample by age and sexSEX No. % of sampleMale 976 51.4Female 922 48.6

Ratio M:F 1.06:1

Nutritional status of children between children 56-59 months or between65-110cm length/height

Anthropometric Indices No. % 95% CI*Z-Scores (Weight for height/length)

> 2 Z-scores (obese) 20 1.0 0.9996-1.004

-2.0 to 2.0 Z-scores (normal) 1655 87.2 86.185-88.215

-3.0 to <-2.0 z-scores (moderate malnutrition) 199 10.5 10.486-10.514

<-3 z-scores or oedema (SAM) 24 1.3 1.295-1.305

Total <-2 Z-scores or oedema (GAM) 223 11.8 11.785-11.815

% of the median (Weight for height/length)

<80% or oedema =GAM

<70% or oedema = SAM

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7.4

0.3

7.388-7.412

0.298-0.302

Mean weight for length 94.5 SD 37.4

*95% confidence intervals with calculated cluster effectGAM = Global acute malnutrition SAM =Severe acute malnutrition

1.3.2 Nutritional indices of a convenience sample of elderly people

Classification of MuacMeasures

Nutritional Status No. %

Above 24cm Normal weight 50 22.723.1-24cm Mild malnutrition 29 13.222.1-23 cm Moderate malnutrition 38 17.3Below 22cm Severe malnutrition 103 46.8TOTAL 220 100Total Malnourished 170 77.3

1.3.3 Food securityFood security is poor with the majority of the population dependent on aid fortheir main source of food. Although crops and livestock benefited temporarilyfrom scattered rainfall, crops are wilting and livestock are again threatened bylack of pasture, water and disease. Income diversification has taken place dueto the lack of rain and poor harvest and many households have resorted toselling household assets or migration as coping strategies. At the community

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level, 77.5% of the communities reported a high level of illnesses in theprevious six months.

1.4 Conclusions

• Overall nutritional status in the under five population has improved in theYabello and Teltele woredas in comparison with surveys conducted inMarch 20001 (Norwegian Church Aid et al, 2000) and April 20002 (CARE,2000).

• In spite of this improvement, a very high percentage of the population isdependent on food Aid for their main food source.

• Nutritional status varied with location, with some villages showing highlevels of malnutrition and others showing a very low prevalence.

• The prevalence of moderate and severe malnutrition observed in theelderly is extremely high as was found by Help Age International(April,2000) 3.

• Livelihood strategies have changed and the more extreme copingstrategies such as selling essential household assets have already startedto be adopted.

• Market conditions are improving with the re-appearance of some products,such as milk, that were not available six months ago. However, onlypeople with enough purchasing power can access them.

• Harvest predictions are poor and the condition of livestock will likelydeteriorate again due to pressure on pasture, water sources and disease.

The combination of the above factors would indicate that although theprevalence of malnutrition has significantly decreased over the past twomonths, the current situation is very unstable and could deteriorate rapidly.

1.5 Recommendations

• As the majority of the population are currently reliant on free food aid, it isimperative that the general ration and supplementary distribution arecontinued for a minimum of six months until the crops planted during theSeptember rains are harvested.

• NGOs should co-ordinate their activities along with the GovernmentEmergency Task Force Committees to ensure that an adequate level ofprotein and energy is being distributed between the general andsupplementary rations.

• An ongoing system of food distribution surveillance and monitoring shouldbe established in the area in order to ensure that the correct rations arereaching the target population.

1 Norwegian Church aid found a mean WFL of 86.1% in Yabello and 89.3% in Teltele compared to the currentfindings of 94.1% and 95.0% respectively.2 CARE found a global malnutrition rate of 21.8% in Yabello and 34.8% in Teltele compared to the current findings of11.2% and 12.3% respectively3 HelpAge found a total of 86.7% below the 24cm MUAC cut-off point for malnutrition for three woredas includingYabello and Teltele compared to a total of 77.3% in the current survey.

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• The location of distribution sites should be reviewed and research into thefeasibility of introducing additional sites, which would reduce traveldistance for a large number of beneficiaries, should be carried out.

• Differing levels of malnutrition were found in the various PAs with noapparent relationship. It is recommended that a complete re-registrationand screening is carried out in the worst affected areas to target themalnourished.

• Research into the viability of establishing mobile outreach teams toconduct weight for height screening to locate and register malnourishedchildren for supplementary feeding in EPI outreach sites, in tandem withthe EPI programme, should be carried out.

• Given the high levels of malnutrition in the elderly, supplementary foodshould be made available specifically targeted to this population.

• In Boran culture, children under five receive preferential feeding. It isrecommended that in order to target children above the age of five whoappeared to be malnourished, school feeding programmes, starting inSeptember, should be established in a number of areas to target thesechildren, with the dual benefit of increasing nutritional status andencouraging education.

• It is recommended that a repeat survey be carried out in early Septemberprior to the next rains to assess the impact of the drought. The surveyshould include some assessment of children aged over five years, adultsand elderly to deliver a more complete picture of nutritional status.

• As seed has been distributed but no crop harvested due to lack ofsufficient rainfall, it is recommended that seed and tool distribution beprovided prior to the onset of the September rains.

• The loss of oxen for ploughing has meant that many agriculturists or agro-pastoralists are using their hands to plant crops. The viability of providingoxen for the use of communities who have none remaining should beinvestigated.

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2.0 Introduction and background information

Borana Administrative Zone in Southern Oromiya Regional State has 12administrative woredas, two of which - Yabello and Teltele - are included inthe survey. Both woredas are lowland areas characterised by arid and semi-arid weather conditions.

Rainfall is bimodal with the main rains, the ganna, accounting for 65% of theannual precipitation which falls between mid-March to May and the smallrains, hagaya which provide the remaining 35% of rainfall and occur fromSeptember until the end of November. These woredas have not received anysizeable rains since October/November 1998 when the hagaya failed. Dataindicates that the current climatic drought cycle may have shrunk from five tothree years in the zone (UNDP June 2000).

The zone is drought prone and has continually received food aid for a numberof years. Both Yabello and Teltele woredas are pastoral and agro-pastoralareas which have been under food stress for the whole of 1999, a situationwhich has continued. UNDP (June 2000) estimated that if the mid March toMay rains did not arrive there would be a need for a major relief operation.

3.0 Objectives

§ To quantify the nutritional status of children aged 6-59 months or between65-110cm in length in GOAL Ethiopia’s relief project areas of BoranaAdministrative Zone.

§ To assess the nutrition status of people above 55 years old living in theproject area using MUAC measurements of a convenience sample in thesurvey area.

§ To examine the current situation with regard to food security with particularfocus on the following:§ Aid coverage§ Food sources§ Effects of the drought on livelihood strategies§ Effects on health

4.0 Methodology

4.1 Sampling MethodAs recommended by the UNHCR/MSF/WFP, the two stage random clustersampling method was used. Thirty clusters were selected from a populationsampling frame of 18 Peasant Associations (60 villages) using populationproportion to size techniques, based on the DPPB Yabello and TelteleWoreda Task Force population figures (April and May 2000 respectively)4.Fifteen clusters were taken from Teltele woreda and 15 from Yabello woreda,all of which were receiving supplementary distribution from GOAL at the time 4 CSA (1994) projected the population to be 53,671 by 2000, whereas the woreda task forcefigures which were used estimated the population to be at 75,211 for the area, thus increasingthe %of population covered by the sampling frame

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of the survey (see Appendix 1:Map). A total of 65 children per cluster wererandomly selected.

4.2 Sample sizeThe sample size was calculated using the expected prevalence of malnutritionof 35% for Teltele Woreda (CARE, April 2000). Precision was calculated at3%, error risk at 5% and a design effect of 2. A total of 1,950 children wereassessed with 65 children in each cluster from a total estimated under-fivepopulation of 12,589, (15.5%). The percentage of under-fives was calculatedusing the average number (18%) for Oromiya region (Yabello Health Centre,April 2000/CSA,1994).

4.3 Sample PopulationChildren aged from 6-59 months or between 65-110 cm were included. Of the1,950 children assessed, 52 were excluded as they were outside the selectedlength/height cut-offs.

In addition a convenience sample of elderly persons, (aged over 55 years)who were resident in the chosen households and present at the time of theassessment were selected for MUAC measurements.

4.4 Data collectedInformation was collected through anthropometric measurements and threequestionnaires:- child, household and community, conducted throughinterviews (see Appendix 2:Questionnaires). All questionnaires were pilotedprior to the survey.

Information per child:• Sex• Age (in months)• Weight (kg) with a precision of 100g using hanging Salter Weigh Tronix

scales (maximum 25kg) for children below three years and metricbathroom type mechanical International Dispensary Association scaleswith a precision of 500g (maximum 120kg) for children above three years.

• Height (cms) to the nearest 0.1cm using the Oxfam nutritional survey kitlength/height boards. Children between 65 and 85cm were measuredhorizontally. The boards were marked with red lines between theselengths to facilitate this.

• Presence or absence of bilateral oedema on both feet after 3 seconds ofpressure.

Other information per child was collected using a child questionnaire• Vaccination status• Current and recent health history• Breastfeeding practices• A record of the types, frequency and sources of meals consumed over the

previous 24 hours.

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Household surveys were conducted in 1,103 households and information onthe following areas was collected:

• Demographic breakdown of the household• Births and deaths over the previous 12 months• Pre-drought and current livelihood strategies• Livestock and land holdings• Access to school feeding programme• MUAC measurements and frequency of meals consumed by people aged

over 55 years in the household. Help Age colour-coded MUAC tapes forolder people in sub-Saharan Africa were used.

Community questionnaires were conducted in 49 out of the 60 villages andinformation was collected about the following areas:• Number of households and population• Pre-drought and current livelihood and coping strategies• Livestock holdings and crop planting• Water sources (previous and current)• Food consumption, security and priority of food distribution• Community health and mortality

4.5 Team CompositionTwo teams conducted the survey and each was composed of the following

• An expatriate nutritionist or nurse as team leader and interviewer• An interpreter who worked alongside the expatriate• A fully trained Ministry of Health nurse/health assistant, responsible for

anthropometric measurements• A recorder, also trained in anthropometric assessment, who double-

checked and recorded the measurements• A facilitator who assisted in the random selection of the households,

communicated with and organised the villagers

All members of the team received a full day training course by a qualifiednutritionist to ensure that the techniques and methodology to be followed wereunderstood.

4.6 Implementation

The survey was conducted from 12-26th June 2000 in 18 PAs, nine in Yabelloworeda and nine in Teltele woreda, Borana Administrative zone, OromiaRegional State. Both Yabello and Teltele Emergency Task Force Committeeswere informed about the purpose and scheduling of the survey and wereasked to disseminate information to the relevant PA Chairmen andDevelopment Agents in advance of the survey. The population wererequested to remain in their houses until completion of the assessment.

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5.0 ResultsAnalysis was done using EPIINFO 6, EPINUT 2.0 and EXCEL. Weight forheight index values are based on the Reference Population Tables of theNCHS/CDC/WHO 1982.

5.1 Demographic Distribution

5.1.1 Household Level

Table 1 Household demography

No ofHouseholds

Totalpopulation

%Under-fives

% Aged 5-55years

% Elderly(55+ years)

No % No % No %1,103 7,173 2,088 29.1 4,713 65.7 372 5.2

The average household size is 6.5 persons which is higher than the nationalaverage of 4.8 for Oromia region (Ministry of Health, 1998)

5.1.2 Under-five years of age Level

Table 2 Distribution of sample by age and sex

Age class Sex TotalMale Female

No % total No % total No Total %6-29 months 394 20.8 378 19.9 772 40.730-59 months 582 30.7 544 28.7 1126 59.3TOTAL 976 51.4 922 48.6 1898 100.0

5.2 Nutritional status by z-scores and percentage of the median

Table 3 Nutritional status - children 6-59 months or 65-110cm W/L/H

Anthropometric Indices No. % 95% CI*Z-Scores (Weight for height/length)

> 2 Z-scores (obese) 20 1.0 0.9996-1.004

-2.0 to 2.0 Z-scores (normal) 1655 87.2 86.185-88.215

-3.0 to <-2.0 z-scores (moderate malnutrition) 199 10.5 10.486-10.514

<-3 z-scores or oedema (*SAM) 24 1.3 1.295-1.305

Total <-2 Z-scores or oedema (*GAM) 223 11.8 11.785-11.815

% of the median (Weight for height/length)

<80% or oedema =GAM

<70% or oedema = SAM

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7.4

0.3

7.388-7.412

0.298-0.302

Mean weight for length 94.5 SD 37.4

95% confidence intervals with calculated cluster effect*GAM = Global acute malnutrition *SAM =Severe acute malnutrition

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The prevalence of global malnutrition is 11.8% which is classified as a level ofmalnutrition requiring targeted supplementary feeding (>10% GAM), (MSF,1995).

5.2.1 Malnutrition by age

Table 4 Prevalence of malnutrition by age category

Anthropometric Indices 6-29months

95% CI* 30-59months

95% CI*

Z-Scores (W/H/L)-3.0 to <-2.0 z-scores 5.11 5.1-5.12 5.37 5.360-4.380<-3 z-scores or oedema(*SAM) 0.84 0.836-0.840 0.42 0.417-0.423Total <-2 Z-scores oroedema (*GAM) 5.95 5.939-5.961 5.80 5.788-5.812% of the median (W/H/L)<90% W/H<80% or oedema =GAM<70 or oedema = SAM

17.44.80.3

17.383-17.4170.298-0.302

21.52.60.1

21.482-21.5182.593-2.6070.99-0.11

All the severely malnourished children >-3SD were aged between 12-48months. Of these, 66.7% were in the 6-29 month category.

5.2.2 Malnutrition by sexThere was no significant difference between nutritional status and sex ineither age category.

5.2.3 Malnutrition by location

Table 5 Prevalence of malnutrition by woreda

Woreda Global acute malnutrition Severe acute malnutritionNo % 95% CI No. % 95% CI

Yabello 107 11.2 11.18-11.22 10 1.0 0.996-1.004Teltele 116 12.3 12.28-12.32 14 1.5 1.495-1.505

95% confidence intervals with calculated cluster effect

There was no statistical difference between prevalence of malnutrition andworeda.

Table 6 Mean weight/length/height by Woreda

Woreda Mean W./L % Standard DeviationYabello 94.1 30.9Teltele 95.0 43.1

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Although clusters are not traditionally analysed separately, due to the widegeographical spread of the clusters, analysis revealed that levels of globalmalnutrition ranged from 1.3% to 26.2%, with nine of the clusters having aprevalence of over 15% (see Appendix 3). However no obvious relationshipwas detected. Overcrowding in some areas or remote location may explainhigher levels in these areas.

5.2.4. Malnutrition and livelihood

Tables 7 and 8 show the number of children with global malnutrition in each ofthe three largest livelihood categories. For example 45 malnourished childrencame from agriculturist households, constituting 20% of all children frompurely agriculturist households.

Table 7 Prevalence of global malnutrition based on main pre-drought livelihood status

Livelihood No. Globally malnourished % Globally malnourishedAgriculturist 45 20Agro-pastoralist 158 71Pastoralist 11 5

Table 8 Prevalence of severe acute malnutrition based on main pre-drought livelihood status

Livelihood No. Globally malnourished % Globally malnourishedAgriculturist 5 20.8Agro-pastoralist 18 75Pastoralist 0 0

As is shown in both Table 7 and 8, the pre-drought agro-pastoralist populationin this area appears to be most affected.

5.3 Levels of Malnutrition in the Elderly

Table 9 Nutritional Status of the elderly by MUAC measurements

Classification of MuacMeasures

Nutritional Status No. %

Above 24cm Normal weight 50 22.723.1-24cm Mild malnutrition 29 13.222.1-23 cm Moderate malnutrition 38 17.3Below 22cm Severe malnutrition 103 46.8TOTAL 220 100Total Malnourished 170 77.3

A high percentage of the elderly measured were malnourished (77.3%), and46.8% of this malnutrition was severe.

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5.4 Food security

5.4.1 AidThe majority of the households interviewed (89.5%) received some food aid.

Of the children who were not exclusively breastfeeding (n=1670), 18.8%(n=314) were reported to be totally reliant on aid food and 12.2% (n=204)were reported to have no access to food other than wild foods.

Breastfeeding data was deemed unreliable as many of the mothers reportedbreastfeeding for 2-3 years, but had children under that age and were notfeeding more than one child simultaneously.

Table 10 Food Aid received by type and population coverage

AID No ofHouseholds

%

Receiving Aid (total) 934 84.7Of the 89.5% receiving aid:Receiving General Ration 670 60.7Receiving supplementary food 770 69.8Receiving General & supplementary 578 52.4

5.4.2 Food Sources

Table 11 Cereal sources pre-drought and currently

Source Pre-drought CurrentPre-drought % of

communitiesAid only Aid & Market Market only

%Home-grown 67.3 36.7 28.6 2Combination

grown &purchased

32.7 14.3 12.2 6.1

Total 100 51 40.8 8.1

A total of 91.8% of the cereals consumed in communities comes from free Aidor Aid supplemented by foods purchased.

Table 12 Milk sources pre-drought and currently

Source Pre-drought CurrentPre-drought % of

communitiesNone Own

animalsPurchased Own &

purchasedOwn animals 95.9 54.3 23.9 19.6 2.2

There has been a 54% reduction in the consumption of milk from pre-droughtto current times and 19.6% of those communities have changed fromproducing their own milk to solely purchasing it. Milk is one of the maintraditional sources of nutrition for the Borana people and was not available onthe market six months earlier.

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At the community interview level, 63% reported that wild foods were beingconsumed. In addition, the variety of food in the diet has reduced on averageby 50.%, (ranging from 0-100%) excluding aid and wild foods which leads toquestions about the nutritional value of the foods left.

5.4.3 Livelihood Changes

In pre-drought years the households interviewed pursued the followinglivelihoods:

Table 13 Livelihoods pursued in pre-drought years

Livelihood No. %Agro-pastoralist 820 75.1%Agriculturist 161 14.7Pastoralist 65 6.0Petty trader/merchant 33 3.1Other 13 1.2Total Households 1092 100

5.4.4. Current sources of income or food

The households interviewed commonly adopted several of the income/foodsources. Table 14 shows the number and percentage of households usingeach strategy.

Table 14 Current sources of income or food by household

Income/food source No %Aid 916 83.0sell firewood/charcoal 352 31.9Sell animals (mainly goats) 182 16.5Sell water 166 15.0Daily labour 156 14.1Petty trader 54 4.9Sell milk 54 4.9Merchant 53 4.8Sell grass 40 3.6Gold mining 16 1.5Migrate – send money 34 3.1Nothing - no aid 24 2.2Sell agricultural produce 14 1.3Migrate – no money 12 1.1Sell soil/building materials 7 0.6Other 77 7.0

A variety of other strategies had been adopted such as selling stones, clay ortrees for building and dried flowers for stuffing mattresses. People alsoreported selling the only assets they had remaining such as the roof of theirhuts or household pottery. Migration was another strategy adopted; however

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in many cases the male members of the household has simply migrated anddoes not send money to the family. Not only are people diversifying theirincomes, but the undertaking of dangerous jobs such as gold mining wasseen (an increase of 6.3%) from pre-drought years. There have been manyreports of high malarial risk in the gold-mining areas, in addition to the lack ofadequate safety precautions.

The price of firewood, which is already low (2-3 Birr for a large bundle offirewood), is likely to decrease further due to increased competition, asincreasing numbers turn to wood harvesting for income. Opportunities fordaily labour are fast diminishing as traditional daily work such as weeding inthe larger farms are not available due to the lack of rain.

5.4.5 Livestock Holdings

Figures for cattle loss vary. According to the households interviewed, therewas a 77.8% (n=10,389) reduction in the cattle herd over the previous sixmonths. However it is not clear whether the cattle died or were sold on. Fromthe community level questionnaires it is estimated that 42.5% of the cattledied. Statistics from the “Borana Zone Belg Assessment Report” (DPPCmulti-agency June 2000) report a 50.2% cattle loss attributable to drought inYabello and a 24.2% loss in Teltele. In any case, cattle loss varied byhousehold which means that all households were not affected equally.

At the community level (n=49), lack of water (77.6%), lack of pasture (89.95%)and disease (77.6%) were all reported as major problems for the livestock.

Although there has been a visible improvement in the physical condition of thelivestock, which is reflected in market prices, people reported widespreadcattle migration from Kenya. This will put additional pressure on grazing areasand water sources and may introduce further diseases.

5.4.6 Crop Performance

At the community level 98% of those interviewed said that they had plantedcrops. However it was clear that although the low rainfall between March andMay had allowed crop planting in many areas, the absence of any further rainhas meant that the crops are wilting in the fields. Crop yield, given the lack offurther rainfall, is expected to be maximum of about 20% (Teffaro, personalcommunication, Ministry of Agriculture, Teltele, June 2000). Beans and chickpeas, which are shallow crops, appear to be the only crops doing well.

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5.4.7 Land holdings

Table 15 Landholdings per household

Land (hectares) No %< 1 365 33.61-<5 545 50.25-10 29 2.7> 10 9 0.8None 138 12.7 The average amount of land per household is quite small and those who donot own land rent small areas from the Government.

5.4.8 Effects on Health

5.4.8.1 Crude Birth RateCrude Birth Rate: 287 out of a total population of 7,173 people which gives aCBR of 40/1000. This is similar to the National level (40.5/1000) but higherthan the average for Oromia (30.8) (Ministry of Health, 1998).

5.4.8.2 Mortality

From the 1,103 households visited, a total of 101 deaths were reported overthe previous 12 months. From the total household population of 7,173people, 44.5% (n=45) were under five years of age, 21.8% (n=22) were over55 years of age and the remaining 33.7% (n=34) were between these ages.

Table 16 Mortality Rates

Population CMR* <5 year mortality rateTotal 0.4/10,000/day 0.6/10,000/day *Crude mortality rateIn sub-Saharan Africa the CMR is 0.4/10,000/day and the under-five mortalityrate is 1.0/10,000/day (MSF,1995).

5.4.8.3 Morbidity

From the child questionnaires, it was reported that 16.7% (n=317) of thechildren were currently ill, or had been in the previous two weeks.

Table 17 Percentage and frequency of reported child illnesses

Illness* Frequency reported %Diarrhoeal diseases 160 45.5Common Cold 65 18.5Fever 42 11.9Skin infection 20 5.7Eye infection 19 5.4Malaria 6 1.7Other 40 5.6TOTAL 352 100*The occurrence of these illnesses was not medically diagnosed.

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At the community level, 77.5% reported high levels of disease, the mostprevalent of which were malaria (26%), diarrhoeal diseases (20.6%), commoncold (11%), skin diseases and gastric complaints ( both 8.6%).

6.0 Limitations

• The MUAC measurements on the elderly were made only on the elderlywho were present at the time of the assessment. It is possible that thesepeople may have been less healthy than the elderly not assessed who hadgone to the farms or elsewhere at the time of the survey.

• Interviews were carried out by expatriate staff using a local interpreter.There may be errors due to the language barrier.

• The target group were extremely vulnerable and despite being informedthat the survey was not related to food distributions, they may have givendistorted information in the belief that the outcome of the survey wouldaffect their next distribution.

• The timing of food distributions may have affected the availability of food atthe household level at the time of the survey. Had the survey beenconducted a week or more later in some areas, recently distributed foodmay have finished at the household level.

• The sampling methodology was limited by road access, weatherconditions and the degree of co-operation by the PA Chairmen andpersonnel. It was logistically impossible to access large areas of the PAswhich may have affected the results.

• Children under five receive priority feeding in the survey populations.Hence the results may not represent the conditions of the population as awhole.

• The survey was conducted after the region had received a little rain. Therain did not continue so the picture presented may be more optimistic thanthe current survey results indicate.

7.0 Conclusions

• Overall nutritional status in the under five population has improved in theYabello and Teltele woredas in comparison with surveys conducted inMarch 20005 (Norwegian Church Aid et al , 2000) and April 20006 (CARE,2000).

• In spite of this improvement, a very high percentage of the population isdependent on food aid for their main food source.

• Nutritional status varied with location, with some villages showing highlevels of malnutrition and others showing a very low prevalence.

5 Norwegian Church aid found a mean WFL of 86.1% in Yabello and 89.3% in Teltele compared to the currentfindings of 94.1% and 95.0% respectively.6 CARE found a global malnutrition rate of 21.8% in Yabello and 34.8% in Teltele compared to the current findings of11.2% and 12.3% respectively

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• The prevalence of moderate and severe malnutrition observed in theelderly is extremely high, as was found by Help Age International(April,2000) 7.

• Livelihood strategies have changed and the more extreme copingstrategies such as selling essential household assets have already startedto be adopted.

• Market conditions are improving with the re-appearance of some products,such as milk, that were not available six months ago. However, onlypeople with enough purchasing power can access them.

• Harvest predictions are poor and the condition of livestock will likelydeteriorate again due to pressure on pasture, water sources and disease.

The combination of the above factors would indicate that although theprevalence of malnutrition has significantly decreased over the past twomonths, the current situation is very unstable and could deteriorate rapidly.

8.0 Recommendations

• As the majority of the population are currently reliant on free food aid, it isimperative that the general ration and supplementary distribution arecontinued for a minimum of six months until the crops planted during theSeptember rains are harvested.

• NGOs should co-ordinate their activities along with the GovernmentEmergency Task Force Committees to ensure that an adequate level ofprotein and energy is being distributed between the general andsupplementary rations.

• An ongoing system of food distribution surveillance and monitoring shouldbe established in the area in order to ensure that the correct rations arereaching the target population.

• The location of distribution sites should be reviewed and research into thefeasibility of introducing additional sites, which would reduce traveldistance for a large number of beneficiaries, should be carried out.

• Differing levels of malnutrition were found in the various PAs with noapparent relationship. It is recommended that a complete re-registrationand screening is carried out in the worst affected areas to target themalnourished.

• Research into the viability of establishing mobile outreach teams toconduct weight for height screening to locate and register malnourishedchildren for supplementary feeding in EPI outreach sites, in tandem withthe EPI programme, should be carried out.

• Given the high levels of malnutrition in the elderly, supplementary foodshould be made available specifically targeted to this population.

7 HelpAge found a total of 86.7% below the 24cm MUAC cut-off point for malnutrition for three woredas includingYabello and Teltele compared to a total of 77.3% in the current survey.

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• In Boran culture, children under five receive preferential feeding. It isrecommended that in order to target children above the age of five whoappeared to be malnourished, school feeding programmes, starting inSeptember, should be established in a number of areas to target thesechildren, with the dual benefit of increasing nutritional status andencouraging education.

• It is recommended that a repeat survey be carried out in early Septemberprior to the next rains to assess the impact of the drought. The surveyshould include some assessment of children aged over five years, adultsand elderly to deliver a more complete picture of nutritional status.

• As seed has been distributed but no crop harvested due to lack ofsufficient rainfall, it is recommended that seed and tool distribution beprovided prior to the onset of the September rains.

• The loss of oxen for ploughing has meant that many agriculturists or agro-pastoralists are using their hands to plant crops. The viability of providingoxen for the use of communities who have none remaining should beinvestigated.

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References

Care Ethiopia (April 2000) A short summary nutrition survey report AddisAbaba

DPPC Multi-agency Report (June 2000) Borena Zone Belg AssessmentReport

Federal Democratic Republic of Ethiopia, Ministry of Health (January 1998)Health and Health Related Indicators

HelpAge International (April 2000) Nutritional Assessment of Older People,Borena Zone, Ethiopia

Medecins Sans Frontieres (1995) Nutrition Guidelines MSF Paris

Ministry of Health, January 1998 Health and Health related Indicators FederalDemocratic Republic of Ethiopia

Norwegian Church Aid, Dutch Interchurch Aid, EECMY/SES (March 2000)Report on Nutrition Survey in Borena Zone (Oromiya region) and Afder andLiben Zones (Somali Region)

UNDP –Emergencies Unit for Ethiopia (March 2000) Borena Zone ofOromiya: Relief Assistance Alleviates Crisis but more help needed A fieldMission Report

United Nations Emergency Unit for Ethiopia (July 2000) Update on theCurrent Humanitarian Situation in Ethiopia

APPENDIX 1

MAP OF SURVEY AREA

(not available)

APPENDIX 2

CHILD INFORMATION QUESTIONNAIRE

IDENTIFICATIONSurvey date: ________ Cluster No: ___ Woreda: _________________________________PA _________________ Ketena __________ Ola _____________________________________Name of interviewer: ________________________________________________________________Name of respondent:_________________________________________________________________Child Name _____________________ Child No: _________ Child age__________

HEALTH INFORMATION

1. Is the child fully vaccinated? Yes NoPolio & vitamin A mass campaign Yes No

2. Did the child have the following illnesses in the last two weeks? (circle yes or no)

Diarrhoea – no blood Yes NoBloody Diarrhoea Yes NoCough Yes NoFever Yes NoMeasles Yes No

CHILD FEEDING INFORMATION

3. Is the child on breast-milk Yes No

4. If not on breast-milk how old was he/she when completely weaned (tick the relevant box)

1 Never-breast-fed 2 6 months – 1 year 3 1-1½ years4 2-3 years 5 Not own child/don’t know

5. Why was breast-feeding stopped? (tick the relevant box)

1 Usual time to stop 2 Mother was sick3 Low milk production 4 Other (specify)

6. How many times did the child eat yesterday? (*do not include breast feeds) (circle the answer)1 2 3 4 5 6

7. What kinds of foods did the child eat yesterday excluding breast? (tick all foods eaten)

KEY 1 2 3 4Source Own produce Purchased Aid (specify

donor)Other (specify)

Type of food Eaten

UsualfoodY/N

Source

(1-4)

Type of food Eaten

UsualfoodY/N

Source

(1-4)Maize Dairy products

(milk,butter)Wheat VegetablesBarley FruitTeff Wild foods (roots,

berries)Sorghum Other (specify)Beans/pulsesEggsMeat

HOUSEHOLD SURVEYIDENTIFICATIONSurvey date: ____________ Cluster No: ___ Woreda:_________________________PA ________________ Ketena __________ Ola _____________________________Name of interviewer: _________________________________________________________Name of respondent: _________________________________________________________

Information on children under 5 years of age: Number of under 5’s __________________Child 1 name: ______________ Child No: ______ Sex: _____ (M/F) Age _______Child 2 name: ______________ Child No: ______ Sex: _____ (M/F) Age _______Child 3 name: ______________ Child No: ______ Sex: _____ (M/F) Age _______Child 4 name: ______________ Child No: ______ Sex: _____ (M/F) Age _______Child 5 name: ______________ Child No: ______ Sex: _____ (M/F) Age _______

DEMOGRAPHY

1. Head of household 1. Male 2. FemaleIf female why? (tick relevant box)

1 Husband died/divorced 2 Husband migrated3 Second/third wife 4 Other (specify)

2. Number of people living in the household0-5 years 6-54 years 55+ years

3. Have any children been born to this household in the past 12 months (Gana)?Yes No

4. Has anyone died in this household in the past 12 months (Gana)?Yes No

5. Details of deceased

CATEGORY 1 2 3 4 5AGE 0-12 months 13-36

months37-59 months 5-54 years 55+ years

CAUSE OF DEATH Disease Accident Malnutrition Other(specify)

Sex (M/F) Age at death (1- 5) Cause of death (if known) (1- 4)

6. ELDERLY INFORMATIONNO NAME AGE MUAC Number of

meals/dayNUTRITIONAL

STATUS

7. In good years, what activities provide households with the most food or cash on average? (tick)

1. Sell cattle/other animals 4 Sell grass2. Sell agricultural produce 5 Sell water3. Sell milk/other dairy products 6 Migrate and send money4. Sell firewood Other (specify)

Pastoralist Agro-pastoralist Agriculturist

8. What activities provide the households with food or cash now? (tick)

1. Sell cattle/other animals 4 Sell grass2. Sell agricultural produce 5 Sell water3. Sell milk/other dairy products 6 Migrate and send money4. Sell firewood Other (specify)

LIVESTOCK & CROPS

9. How many cattle have died over the past six months? ________

10. How many cattle do you have left? (write the number of each)

Cattle Goats Shoats Camels Donkeys/asses/horses

11. How much land do you own?

None 0-< 5 ha 5-10 ha >10 ha

12. Do you have children who participate in a school feeding programme? Yes No

COMMUNITY INTERVIEW QUESTIONNAIRE

IDENTIFICATION

Survey date: ____________ Cluster No: ______ Woreda: ___________PA ____________________ Ketena __________ Ola _______________No of households: ________ Ola population _____

Name of interviewer: __________________________________________________

Interviewees Present _____________________________________________________

LIVELIHOOD INFORMATION

1. In good years, what activities provide households with the most food or cash on average? (tick)

1. Sell/consume own cattle/other animals 4 Other (specify)2. Sell/consume agricultural produce 53. Sell/consume milk/other dairy products 6

Pastoralist Agro-pastoralist Agriculturist

2. What activities provide the households with food or cash now? (tick)

1. Sell/ consume cattle/other animals 4 Sell grass2. Sell/ consume agricultural produce 5 Sell water3. Sell/ consume milk/other dairy products 6 Migrate and send money4. Sell firewood Other (specify)

LIVESTOCK & CROPS

3. How many cattle have died over the past six months? ________

4. How many cattle does the community have left? (write the number of each)

Cattle Goats Shoats Camels Donkeys/asses/horses

5. What are the main problems affecting the livestock of the moment ? (tick)

Shortage of grass Other (specify)Shortage of waterDisease: (specify)

6. Has the community planted any crops in the past 3 months? (circle) YES NO

WATER7. Where do people get drinking water from in normal times? Tick & write return walking time (hrs)

Protected well Unprotected well Protected spring Unprotected spring Pond

8. Where do you people get drinking water from now? Tick box and return walking time (hrs)

Protected well Unprotected well Protected spring Unprotected spring Pond

FOOD CONSUMPTION & SECURITY

9. What are the main foods consumed in this area in good times?KEY 1 2 3 4

Source Own produce Purchased Aid (specify donor) Other (specify)

Type of food Eaten Source(1-4)

Type of food Eaten Source(1-4)

Maize Dairy products(milk,butter)

Wheat VegetablesBarley FruitTeff Wild foods (roots, berries)Sorghum Other (specify)Beans/pulsesEggsMeat

10. What are the main foods consumed now in this area?KEY 1 2 3 4

Source Own produce Purchased Aid (specify donor) Other (specify)Type of food Eate

nSource

(1-4)Type of food Eaten Source

(1-4)

Maize Dairy products(milk,butter)

Wheat VegetablesBarley FruitTeff Wild foods (roots, berries)Sorghum Other (specify)Beans/pulsesEggsMeat

11. What coping mechanisms or unusual behaviours have occurred in the area in recent months?

Migration Higher death rate Sale of assets (personal)

Sale of assets (productive) Consumption of wild foods Closure of schools

School feeding programme YES NO Other:

COMMUNITY HEALTH

12. Is there evidence of unusual outbreaks of human diseases in the area? YES NOIf yes, what type of diseases:1. ________________________ ________________________2. ________________________ ________________________

13. Approximately how many people have died in the ola in the previous 6 months? _______

14. Number of under 5’s _______ Number of elderly _____ Other _______

15. In order of priority, who is given food first:

16. under 5yrs school age children adults elderly 17. Is priority given to male female

APPENDIX 3

Analysis by cluster

Number and percentage of children with global malnutrition per cluster

Woreda PA Name ClusterNo

No ofmalnourished

Clustersize

% ofcluster

Teltele Gendile 1 4 63 6.3

Teltele Jerarsa 2 10 65 15.4

Teltele Bullo Danbi 3 5 63 7.9

Teltele Billa 4 10 63 15.9

Teltele Kulcha 5 8 61 13.1Teltele Kulcha 6 7 65 10.8Teltele Kulcha 7 7 63 11.1Teltele Folatelle 8 12 60 20.0Teltele Folatelle 9 5 65 7.7

Teltele Folatelle 10 8 63 12.7

Teltele Ibsa 11 8 61 13.1Teltele Ibsa 12 10 65 15.4Teltele Watwonto 13 6 65 9.2Teltele Millemii 14 9 55 16.4Teltele Millemii 15 7 65 10.8Yabello Gegna 16 3 60 5.0Yabello Gegna 17 2 65 3.1Yabello Gegna 18 2 62 3.2Yabello Surupa 19 1 57 1.8Yabello Surupa 20 2 65 3.1Yabello Bildim Rasso 21 11 65 16.9Yabello Towayo 22 4 65 6.2

Yabello El Wayo 23 9 64 14.1Yabello Derito 24 7 64 10.9Yabello Derito 25 8 64 12.5Yabello Yubda 26 6 65 9.2Yabello Obda 27 6 65 9.2Yabello Didyabello 28 17 65 26.2

Yabello Didyabello 29 13 65 20.0Yabello Didyabello 30 16 65 24.6

TOTAL 1898