Report No. ET

MALNUTRITION IN ETHIOPIACurrent Interventions, Successes, Cost-Benefit Analysis, and the Way Forward

DRAFT NOT FOR CITATION

December 2007

AFTH3Human Development DepartmentAfrica Region

Document of the World Bank

This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations and conclusions expressed in this paper do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work.

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CURRENCY AND EQUIVALENT UNITS(Effective Dec 18, 2007)

Currency Unit = Ethiopia Birr (ETB)US$1 = 9.0900 BirrUS$1 = 0.6312 SDR

FISCAL YEARJuly 8 – July 7

WEIGHTS AND MEASURESMetric System

Vice President : Obiageli Katrya EzekwesiliCountry Director : Kenichi OhashiSector Manager : Laura Frigenti

Task Leader : Andrew Sunil Rajkumar

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ACKNOWLEDGEMENTS

This report was prepared by a team comprised of Andrew Sunil Rajkumar (AFTH3, Task Team Leader), Jessica Barney (Consultant), Chris Gaukler (Consultant), David Lawson (Consultant) and Eskender Tesfaye (Consultant), with contributions from Jack Fiedler (Consultant), Hailay Teklehaimanot (Consultant), Yemane Yihdego (Consultant) and Caroline Poeschl (Consultant).

The report was prepared under the general guidance of Ms. Laura Frigenti (Sector Manager, AFTH3), Mr. Kenichi Ohashi (Country Director, AFC06), and Trina Haque (Lead Economist, AFTH3). Invaluable comments were received from the Ethiopia country team and others, in particular Harold Alderman and Marito Garcia.

The Peer Reviewers for this report are Meera Shekar (Senior Nutrition Specialist, HDNHE) and Menno Mulder-Sibanda (Senior Nutrition Specialist, AFTH2).

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Table of ContentsACKNOWLEDGEMENTS.........................................................................................................................IV

ACRONYMS...............................................................................................................................................VII

GLOSSARY...................................................................................................................................................X

EXECUTIVE SUMMARY........................................................................................................................XII

1 INTRODUCTION.................................................................................................................................1

1.1 BACKGROUND................................................................................................................................11.2 MALNUTRITION: DEFINITION, CAUSES, AND CONSEQUENCES......................................................11.3 ETHIOPIA’S SITUATION..................................................................................................................6

1.3.1 Current National Indicators: Micronutrients...........................................................................71.3.2 Current National Indicators: Breastfeeding..........................................................................101.3.3 Ethiopia from a Regional and World Perspective..................................................................131.3.4 Ethiopia over time..................................................................................................................151.3.5 Nutrition in the PASDEP........................................................................................................20

1.4 FOOD SECURITY VERSUS NUTRITION SECURITY.........................................................................20

2 CURRENT PROGRAMS IN ETHIOPIA........................................................................................22

2.1 CURRENT PROGRAMS AFFECTING NUTRITION IN ETHIOPIA........................................................222.2 PROGRAMS THAT GIVE FOOD OR CASH......................................................................................22

2.2.1 FSP - Food Security Project...................................................................................................222.2.2 EFA—Emergency Food Aid...................................................................................................232.2.3 TSFP—Targeted Supplementary Feeding Programme..........................................................232.2.4 PSNP—Productive Safety Net Programme............................................................................242.2.5 CTC—Community-Based Therapeutic Care..........................................................................242.2.6 CHILD—Children In Local Development (school feeding program)....................................252.2.7 MERET—Managing Environmental Resources to Enable Transition to more sustainable livelihoods.............................................................................................................................................25

2.3 PROGRAMS THAT DO NOT GIVE FOOD OR CASH, OTHER THAN THOSE FOCUSING ON COMMUNITY VOLUNTEERS........................................................................................................................26

2.3.1 EOS—Enhanced Outreach Strategy for child survival..........................................................262.3.2 HEP—Health Extension Programme.....................................................................................262.3.3 WASH—Water Supply, Sanitation, and Hygiene...................................................................272.3.4 EPI—Expanded Programme on Immunization......................................................................27

2.4 PROGRAMS WITH A STRONG COMMUNITY VOLUNTEER FOCUS..................................................282.4.1 ESHE—Essential Services for Health in Ethiopia.................................................................282.4.2 CBRHA – Community-Based Reproductive Health Agents....................................................282.4.3 CGP-FSP – Child Growth Promotion Component of the Food Security Project..................28

3 MALNUTRITION TRENDS AND ASSOCIATIONS AND NUTRITIONAL INDICATORS. .33

3.1 TRENDS IN MALNUTRITION IN ETHIOPIA.....................................................................................333.2 NUTRITION TRANSITION..............................................................................................................383.3 ASSOCIATIONS WITH CHILD MALNUTRITION..............................................................................403.4 LINKS BETWEEN FOOD SECURITY STATUS AND MALNUTRITION.................................................423.5 CONCLUSIONS AND POLICY IMPLICATIONS.................................................................................46

4 INFLUENCING FACTORS ON MALNUTRITION: A FURTHER FOCUS.............................48

4.1 BREASTFEEDING PRACTICES........................................................................................................484.2 VITAMIN A INTAKE.....................................................................................................................554.3 IODINE INTAKE............................................................................................................................584.4 IMMUNIZATION............................................................................................................................59

5 COST EFFECTIVENESS AND BENEFIT-COST ANALYSIS....................................................61

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5.1 COST EFFECTIVENESS AND BENEFIT-COST ANALYSIS: WHAT IS FEASIBLE AND WHAT IS NOT615.2 COSTING OF CURRENT INTERVENTIONS AND EFFECT ON CHILD MORTALITY............................635.3 COSTING OF POTENTIAL INTERVENTIONS AND EFFECT ON MORTALITY.....................................675.4 QUALITATIVE ASSESSMENT OF AN INTERVENTION’S IMPACTS...................................................685.5 IMPACT ON ECONOMIC PRODUCTIVITY.......................................................................................715.6 IMPACT ON MENTAL ABILITY......................................................................................................725.7 TOTAL IMPACTS (MORTALITY, PRODUCTIVITY, AND MENTAL ABILITY)...................................735.8 COMMUNITY VOLUNTEER PROGRAMS........................................................................................795.9 THE HEALTH EXTENSION PACKAGE – HEALTH EXTENSION WORKERS......................................845.10 SUMMARY AND POLICY RECOMMENDATIONS.............................................................................86

6 ETHIOPIA’S WAY FORWARD......................................................................................................88

6.1 FACTORS AFFECTING PROGRAM DESIGN AND HARMONIZATION................................................886.1.1 Linkages Between Different Programs...................................................................................886.1.2 Nutritional Surveillance.........................................................................................................926.1.3 Targeting of Food Aid............................................................................................................936.1.4 Overall Targeting of Programs Affecting Nutrition...............................................................98

6.2 HEALTH EXTENSION WORKERS.................................................................................................1056.3 THE ENHANCED OUTREACH STRATEGY (EOS).........................................................................1096.4 MICRONUTRIENTS......................................................................................................................112

APPENDICES.............................................................................................................................................113

APPENDIX 1: BIBLIOGRAPHY...................................................................................................................113APPENDIX 2: SUPPLEMENTAL TABLES.....................................................................................................120APPENDIX 3: ASSUMPTIONS FOR COSTING IN CHAPTER 5.......................................................................123Appendix 4: Maps....................................................................................................................................130

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ACRONYMSBCA Benefit-Cost AnalysisBCG Bacille Calmette-Guerin (TB immunization)BCR Benefit-to-Cost RatioBF BreastfeedingBW Birth weightCARE Cooperative for Assistance and Relief Everywhere, Inc.CBRHA Community-Based Reproductive Health AgentCEA Cost-Effectiveness AnalysisCGP Child Growth PromotionCHILD Children In Local Development (school feeding programme WFP)CHOICE Choosing Interventions that are Cost EffectiveCHP Community Health Promoter (ESHE)CSA Central Statistical AuthorityCSB Corn Soya BlendCTC Community-Based Therapeutic CareCV Community VolunteerCVI Chronic Vulnerability IndexDHS Demographic and Health Survey

DPPA/B/D Disaster Prevention and Preparedness Agency (federal; formerly DPPC for Commission)/Bureau (Regional)/Desk or Delegate (Zonal, Woreda).

DPT Diphtheria, Pertussis, and TetanusEBF Exclusive BreastfeedingEFA Emergency Food AidEHNRI Ethiopian Health Nutrition Research InstituteENCU Emergency Nutrition Coordination UnitEOS Enhanced Outreach Strategy for child survivalEEOS Extended EOSE/EOS Both EOS and EEOSEPI Expanded Programme on ImmunizationESHE Essential Services for Health in EthiopiaEWS Early Warning System (DPPA)FDA Food Distribution Agent (from TSFP)FMOH Federal Ministry of HealthFS Food SecurityFSP Food Security ProjectGDP Gross Domestic ProductGoE Government of EthiopiaHEP Health Extension Programme

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HEW Health Extension WorkerHH HouseholdHP Health Post (part of Health Extension Programme)IDA Iron Deficiency AnemiaIDD Iodine Deficiency DisorderIMC International Medical CorpsIMR Infant Mortality RateIR Islamic ReliefITN Insecticide Treated Nets (malaria prevention)IUGR Intra-Uterine Growth RetardationLBW Low Birth weightMDG Millennium Development Goals

MERET Managing Environment Resources to Enable Transition to more sustainable livelihoods (WFP)

MT Metric TonsMUAC Mid-Upper Arm CircumferenceNCHS National Center for Health StatisticsNGO Non-Governmental OrganizationNMR Neonatal Mortality RateNNS National Nutrition StrategyNS Nutrition SecurityODA Official Development AssistanceOTP Out-Patient Therapeutic Programme (home-based care)PASDEP Plan for Accelerated and Sustained Development to End PovertyPLW Pregnant and Lactating WomenPLWHA People Living With HIV/AIDSPPM Parts Per MillionPRRO Protracted Relief and Rehabilitation Operation (WFP)PSNP Productive Safety Nets ProgrammeRH Reproductive HealthRHB Regional Health BureauSC Stabilization Centre (in-patient care of CTC)SCUS Save the Children – United StatesSD Standard Deviation (statistics)SNNPR Southern Nations, Nationalities, and Peoples RegionSSA Sub-Saharan AfricaTB TuberculosisTSFP Targeted Supplementary Feeding ProgrammeTTBA Trained Traditional Birth AttendantsU5MR Under-5 Mortality RateUNDP United Nations Development ProgrammeUNICEF United Nations Children’s FundUSAID United States Agency for International DevelopmentVAD Vitamin A DeficiencyWASH WAter, Sanitation, and Hygiene

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WAZ Weight for Age Z-scoreWB World BankWFP World Food ProgrammeWHO World Health OrganizationWMS Welfare Monitoring Survey

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GLOSSARY

Anemia

Low level of haemoglobin in the blood leading to reduced capacity to carry oxygen to tissues and organs; can have various causes, most commonly a consequence of Iron Deficiency (IDA). Symptoms are decreased energy, mental capacity, and increased maternal mortality.

Body Mass Index

BMI is an index of fatness. It is calculated by weight in kilograms divided by height in meters squared. Both high and low BMIs are associated with poor health. Normal range for a healthy adult is 18.5 to 24.9. Below 18.5 is too lean, while above 25 is considered overweight. Greater then 30 is considered obese, and greater then 40 morbidly obese.

Complementary Foods

Formerly called ‘weaning foods’. Foods that are introduced while a child continues to breastfeed. It is recommended they are started at 6 months of life and are fed 2 to 3 times per day with increasing consistency as the child grows.

Exclusive Breastfeeding

When an infant is fed only breast milk. No water, tea, gruel, or other animal milk. EBF is recommended for the first 6 months of life.

Food SecurityAvailability, access, and utilization of sufficient food by all people at all times for an active, healthy life.1 (see Nutrition Security)

Gini CoefficientA measure of income inequality ranging from 0 (perfect equality) to 1 (perfect inequality).

Moderate Malnutrition

A common benchmark used in health and nutrition studies. It is technically defined as a child with <-2 z-scores or <80% median weight-for-height and/or presence of bilateral oedema. (see z-score, Malnutrition, and Percent Median)

Global Stunting/Wasting/Underweight Rate

Also referred to “total stunting/wasting/underweight rate” or simply “stunting/wasting/underweight rate”. A common benchmark used in health and nutrition studies. It is technically defined as a child who has <-2 z-scores or <90% median height-for-age. (See Stunting)

Infant Mortality Rate

Probability of dying between birth and exactly 1 year of age expressed per 1,000 live births.

Iodine Deficiency Disorder

Disorder caused by a deficiency of Iodine in the diet; IDD spectrum includes, goitre, hypothyroidism, impaired mental function, stillbirths, abortions, congenital abnormalities, and neurological cretinism.

Low Birth weightInfant born weighing less then 2,500 grams (5.5 pounds). In rural areas it is estimated by ‘relative size’ to other babies by the birth attendant or mother.

Malnutrition

An imbalance between the body’s needs, usage, and intake of nutrients. The imbalance can be caused by poor/lacking diet, hygiene issues, disease states, lack of knowledge, cultural practices, etc. Underweight, stunting, wasting, obesity, and vitamin and mineral deficiencies are all forms of malnutrition.

MUAC

Mid-Upper Arm Circumference is one of the anthropometric measures used in assessing nutritional status. It is always measured on the left arm of children under 5 years and pregnant and lactating women. It is easier and faster to utilize and train for then weights and heights.

1 Benson 2006.

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Neonatal Mortality Rate

Probability of dying in the first 28 days of life expressed per 1,000 live births.

Nutrition SecurityWhen a HH attains secure access to food coupled with a sanitary environment, adequate health services, and knowledgeable care2. (see Food Security)

Percent3 Median

Method of comparing an observation to the population. Assigned a percentage from the median. Less then 80% of median is considered poor. Used in targeting and as admission criteria because of ease of calculating in the field.

Severe Stunting/Wasting/Undeweight Rate

A common benchmark used in health and nutrition studies. It is technically defined as a child who has <-3 z-scores or <80% median height-for-age.

Stunting

When a child has low stature compared to other children his age because of inadequate nutrition, care, and environment. A proxy measure for long-term malnutrition. Defined as less then two standard deviations below the median (minus 2 z-scores).

Under-5Mortality Rate

Probability of dying between birth and exactly 5 years of age expressed per 1,000 live births.

Under-nutrition Not getting enough nutrients for a healthy body; can result from low intake, malabsorption during disease, or extreme losses such as during diarrhoea.

UnderweightWhen a child has low weight compared to other children his/her age. One way to measure acute malnutrition. Defined as less then two standard deviations below the median (minus 2 z-scores).

Vitamin A Deficiency

Form of malnutrition resulting from inadequate intake or high loss of Vitamin A. Symptoms include growth retardation, night blindness in mild deficiency, and xeropthalmia (drying of the cornea), which leads to complete blindness.

WastingWhen a child has a low weight for their current height. Used as a proxy measure of acute malnutrition. Defined as two standard deviations below the median (minus 2 z-scores).

Z-score3

Unit of measure used often in nutrition and health field. The deviation of an individual’s value from the median value of the reference population, divided by the standard deviation of the reference population. Tells you where one observation lies in reference to the population. Minus 2 z-scores is considered low.

2 Benson 2006.3 Z-Score criteria always yield a greater prevalence of malnutrition than use of the percent-of-median criteria. This is because the former takes into account variation in the standard deviation of weight at different heights, making it more statistically valid (DPPC 2002). The WHO recommends use of z-scores since these are the most age independent method of presenting indices. In addition, individuals with indices below the extreme percentiles can be classified more accurately.

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EXECUTIVE SUMMARY

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1 INTRODUCTION

1.1 BACKGROUND

1.1 Ethiopia is Africa’s oldest independent country and has a plentiful stock of natural resources. However, it is ranked 170 out of 177 on the United Nations Development Programme’s (UNDP) Human Development Index4. Within Ethiopia’s borders are a varied climate and diverse agro-ecological zones, providing the country with a variety of agricultural products.

1.2 Currently, Ethiopia has a population of 71.1 million, but it is estimated to grow to 93.8 million by 2015.5 Almost 85% of Ethiopians live in rural areas, with the majority relying on rain-fed agriculture and livestock rearing for their livelihood. Ethiopia is divided into 11 geographic areas (9 regions and 2 city administrations). They are Tigray, Afar, Amhara, Oromiya, Somali, Benshangul-Gumuz, Southern Nations, Nationalities and Peoples (SNNPR), Gambela, Harari, Addis Ababa and Dire Dawa. Each region is divided into zones, then woredas, then kebeles or peasant associations, the latter containing on average 5,000 people.

1.3 There is little doubt that Ethiopia has the capacity to produce enough food for itself and even for export6, but it imports food to feed its people. The country is plagued by a reputation of incessant droughts, famines, and emergencies as much as it is consistently affected by these realities. This status was earned due to years like 2006 which started with droughts and ended with severe flooding.

1.2 MALNUTRITION: DEFINITION, CAUSES, AND CONSEQUENCES

1.4 Malnutrition is a commonly misused and misunderstood term. At times it is transient, like an acute disease that runs its course, but more often it is a chronic, lifelong condition that begins early in childhood, continues into old age and is often passed on to the next generation. Malnutrition can be defined simply as when a body does not get enough nutrients. Despite the simplicity of this definition, confusion remains. The complications lie in how, when, why, and where malnutrition happens. As such, malnutrition can refer to low height-for-weight, low height-for-age, low birth weight babies, high maternal mortality, various anemias, growth failure, xeropthalmia (vitamin A deficiency blindness), or even obesity.

1.5 Nutrients refer to more than just calories, fat, and protein. They also include, in particular, the various vitamins and minerals required by the body for proper functioning. For example, a child may have sufficient calories for energy, but insufficient zinc for proper growth and immune function. This could be because of a low variety in their diet and common bouts of diarrhea leading to depletion of key minerals. For adults, a malnourished woman is more likely than an adequately nourished one to have a low birth weight (LBW) baby and to die during delivery. In turn, LBW babies are

4 UNDP, 2006.5 World Development Indicators, 2004.6 Benson, 2006.

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more likely to become children who are stunted, that is, to have an abnormally low height for their age. A stunted girl will then have a higher likelihood of complications during pregnancy and delivery as well as a greater chance of having a LBW baby, beginning the sequence again. Figure 1.1 shows this.

Figure 1.1: Intergenerational Link of Malnutrition

Source: ACC/SCN-IFPRI (2000).

1.6 Most under-nutrition happens during pregnancy (referred to as Intra-Uterine Grow Retardation, IUGR) and the first 2 years of life. This early damage is irreversible after the child reaches 24 months. Thus this window is a key time for intervention. IUGR leads to higher rates of infant mortality rates, higher rates of low height-for-age, LBW, and premature delivery. As an example, stunting is a common outcome for a child facing poor nutrition in utero or during his first 2 years of life, and it is estimated that in Ethiopia the height deficits in children can be as much as 11 centimeters by 24 months. This irreversible loss will affect the child’s health for the rest of his life; if it is a girl it will also affect her future children. Below, in Figure 1.2, is a graph showing stunting and underweight rates by age in months in Ethiopia. The ‘2-year window’ of opportunity to prevent stunting is universal and illustrated clearly here. By 24 months, the damage is largely done and the rates level off.

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Figure 1.2: Stunting and Underweight rates and age—The Critical Window

0

10

20

30

40

50

60

70

3 7.5 10.5 15 21 30 39 54

Age in Months

% o

f Chi

ldre

n

StuntingUnderweight

Source: Ethiopian PROFILES (2005).

1.7 There are many basic and underlying causes of malnutrition. The conceptual framework in Figure 1.3 illustrates this very clearly. A child’s health status greatly impacts his nutritional intake potential: the number of times a child is sick per month will affect the quantity of nutrients. Infectious disease plays a large role in determining a child’s nutritional status: continual bouts with disease deplete the store of nutrients in the body and can affect the quality and quantity of nutrient absorption. Environmental factors make Ethiopia a hazardous environment for children: oftentimes livestock is housed in the same room where children sleep and smoke from cooking fires burned in the home hangs in the air. Additionally, a mother’s education level, rural infrastructure, access to information, cultural beliefs and practices, access to health care, and access to potable water are important factors that affect nutritional status. These ‘basic causes’ underlie the origins of malnutrition and serve as the basis for chronically nutritionally insecure societies.

1.8 This framework confirms a central theme of this report: nutritional insecurity is related to but not the same as food insecurity, and a multi-sectoral approach is needed to address it; relying only on food interventions is not sufficient. This conclusion has been reached not just by many studies worldwide but also in a seminal paper by Pelletier and others (1995). Although somewhat old, the main findings of the paper remain very relevant today, and underline the findings of this section.

1.9 In recognition of the role malnutrition plays in promoting development and equality, one of the indicators used to measure progress for the first Millennium Development Goal (MDG) is the percentage of under-5 children that are

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underweight. The aim is to halve this indicator in all countries between 1990 and 2005. Thus malnutrition has been designated the “non-income face of poverty” on the way to achieving the MDGs; the first MDG also aims to halve the number of people living in poverty.7 While it is encouraging that many countries are on track to reaching the poverty goal, the general consensus is that many regions and countries are off-track for reaching their non-income poverty target. In this report we keep an eye on underweight as an indicator of nutrition status, but we also disaggregate this indicator into its component parts – stunting and wasting.

Figure 1.3 : UNICEF Conceptual Framework of the Causes of Childhood Malnutrition adapted for Ethiopia

Source: CSA, USAID, & ORC Macro (2001).

1.10 There are many aspects of malnutrition, and a range of indicators is utilized to adequately measure and assess its prevalence. Among these commonly used indicators are the rates of stunting, wasting, and underweight among under-5 children. These refer to abnormally low height-for-age, weight-for-height, and weight-for-age respectively. In the case for stunting it is common to refer to either : (i) the “global stunting rate” (alternatively termed the “total stunting rate” or simply “stunting rate”); or (ii) the “severe stunting rate”. Similar distinctions apply

7 Specifically, the first MDG aims, between 1990 and 2005, to halve: (i) the proportion of the population with less than $1 (in Purchasing Power Parity terms) of income a day; (ii) the “poverty gap ratio”; (iii) the share of the poorest quintile in total national consumption; (iv) the percentage of under-5 children who are (moderately or severely) underweight; and (v) the proportion of the population below the minimum level of dietary energy consumption.

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for wasting and underweight rate8. In the context of Ethiopia, the “global stunting rate” is the percentage of under-5 children that have a height-for-age that is less than two standard deviations below that of the reference population. The “severe stunting rate” is the percentage of under-5 children that have a height-for-age that is less than three standard deviations below that of the reference population. Similar definitions apply for the rates of wasting (abnormally low weight-for-height) and underweight (abnormally low weight-for-age). The reference population for these definitions is not the population of Ethiopia, but rather a population with a distribution of heights, weights and ages that is considered normal by international standards. These references are used worldwide so that rates of wasting and stunting are comparable across countries and regions.

1.11 Until recently, the internationally accepted definition of a “normal” reference population, with associated “normal” age-specific distributions of heights and weights, was based on standards developed by the National Center for Health Statistics (NCHS) in the US. The World Health Organization has recently developed new standards. However, NCHS standards are still often used, especially to examine trends or to make comparisons across time. The malnutrition statistics cited throughout this report are all based on NCHS standards.

1.12 Unless otherwise stated, the rate of stunting, wasting or underweight in this report refers to the global rate for under-5 children. Stunting is utilized as a measure of long-term or chronic malnutrition, while wasting is a measure of more transient or short-term, acute malnutrition. Stunting is a permanent condition; a child who is stunted will become an adult who is also forever stunted. Wasting is transient and can be brought on, for example, by a sudden shortage or withholding of food, among other ways. Wasting is reversible; but stunting, after a certain point, is not. Underweight is a composite measure that is the combination of stunting and wasting; if stunting and wasting measures are separately available, then it is common to focus just on these two measures.

1.13 While there is some correlation between stunting and wasting rates, this correlation is only partial. Areas with high stunting rates often have relatively low wasting rates, and vice versa. This is clearly seen from data on stunting and wasting in Ethiopia that are presented below. Chapter 3 shows, for example, that regions in Ethiopia with the highest stunting rates do not have the highest wasting rates, while those with the highest wasting rates do not have the highest stunting rates. However, there are certainly connections between the two. A child’s linear growth, i.e., stunting, is affected by repeated bouts of illness and inadequate dietary intake, as well as deficiencies in essential micronutrients, including zinc. It is therefore an indicator of the cumulative impact of illness and dietary intake in a surviving child over time. Acute weight loss, i.e., wasting, is provoked by food withholding and poor absorption, which is mostly due to acute illness. Linear growth is directly affected by this, and in the absence of catch-up growth, will ultimately lead to stunting. Hence, while geographical correlation may be weak, the two indicators are not unrelated, and potentially can be demonstrated in a longitudinal type of analysis.

8 See glossary for more definitions and explanations.

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1.14 Areas with high stunting rates often have relatively low wasting rates, and vice versa. This is clearly seen from data on stunting and wasting in Ethiopia that are presented below. Chapter 3 shows, for example, that regions in Ethiopia with the highest stunting rates do not have the highest wasting rates, while those with the highest wasting rates do not have the highest stunting rates.

1.3 ETHIOPIA’S SITUATION

1.15 Malnutrition is one of the main health problems facing children and adults in Ethiopia9 and is a contributing factor in more than half of all child deaths. Nine out of ten child deaths in Ethiopia are due to only five conditions: pneumonia, malaria, diarrhea, neonatal problems and measles.

1.16 Altitude and climate also play a role on child mortality and nutrition security and given Ethiopia’s unique mix of highland and arid areas, these are an important factors in nutrition outcomes. At high elevations there is an increased need of Iron by women and children. Arid or semi-arid areas can lower agricultural production levels. The arid and semi-arid areas (below 1600 meters above sea level) cover nearly 40 percent of the country and are found in the northern, northeastern, and eastern lowland regions. This has an impact on food availability. The sub-moist, moist, and sub-humid areas, covering about 54 percent of the country, consist of the northern, central, western, and eastern mid- to high-altitude regions. With a growing period of 61 to 240 days, these areas are the most important rain-fed agriculture and livestock production areas and accommodate over 80 percent of the rural population. These zones also cover the highland areas, which are exposed to serious natural resource degradation10.

1.17 All of the aforementioned factors play a role in the level of malnutrition in a given area, but Ethiopians may also face further challenges, such as:

Recurrent shocks including droughts, floods, and unrest that disrupt and deteriorate livelihoods and thus a population’s resilience to shocks.

Small landholdings: greater then 60% of households (HH) involved in farming cultivate less then one hectare of land.

Inadequate or inappropriate agricultural practices: the majority of agriculture is rain-fed while there remains great potential for irrigation systems (see Map 1.1 in the appendix).

80% of the Ethiopia is said to be about a half-day walk to the nearest all weather road11.

Living at high altitudes, which can lead to higher numbers of LBW babies and increased need of calories and Iron for children (see Map 1.2 in the appendix).

9 Benson 2006.10 Solomon 1993.11 Joint Evaluation of Effectiveness and Impact on the Enabling Development Policies of the WFP: Ethiopia Country Study. Volume 1. December 2004.

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1.3.1 Current National Indicators: Micronutrients

1.18 Micronutrient deficiencies are some of the most widespread disorders in Ethiopia. Iodine Deficiency Disorders (IDD), Vitamin A Deficiency (VAD), and Iron Defciency Anemia (IDA) afflict a high proportion of the population and cause billions of birr in lost earnings to the poorest households. Due to IDA, IDD, and stunting alone, Ethiopia will lose an estimated 144 Billion Birr between 2006-201512 or an estimated 10% of GDP. Table 1.1 shows some of the indicators used to evaluate Ethiopia’s progress as well as providing a nutritional snapshot of its current situation comparing rural and urban populations. This data was collected as part of the 2005 Ethiopia Demographic and Health Survey (DHS).

Table 1.1 Rural and Urban indicators, 2005Indicator Urban Rural

Adequately iodized salt in the home 21% 19.7%Children aged 6-35 months who:

Ate vitamin A-rich foods in the previous 24 hours 44.2% 24.5%Ate Iron rich foods in the previous 24 hours 28.7% 9.9%

Women with children aged <3 years who:Ate vitamin A-rich foods in the previous 24 hours 54.4% 31.5%Ate Iron rich foods in the previous 24 hours 31.5% 12.8%

Women who reported night-blindness in previous pregnancy13 3.1% 6.4%Children aged 6-59 months with Anemia 46.8% 54%Women with Anemia 17.8% 28.2%

Source: CSA & ORC Macro (2006).

1.19 IDD is known to decrease mental abilities, permanently affecting mental capacity and thus the productive capacity of a society as well (see Table 1.2). Unfortunately, utilization of iodized salt, a simple and cost effective intervention (see Chapter 5), is very low. The data presented in Table 1.1 show that about one-fifth of households were utilizing adequately iodized salt in 2005, according to the DHS. A separate survey conducted 2005 by the Ethiopian Health and Nutrition Research Institute concluded that only 4% of households used adequately iodized household salt14. Although there is some dispute as to what the true figure is, clearly the prevalence of adequately iodized household salt in Ethiopia is very low. The same EHNRI survey also found that the rate of IDD based on measurement of urinary iodine levels, considered a more reliable method of IDD detection than goiter prevalence, was alarmingly high at 80%.

Table 1.2: Consequences of MalnutritionIndicator of Malnutrition

Consequences Ethiopian Facts

Stunting Decelerated growth; decelerated brain development; decreased

18 billion birr was lost between 2000 and 2005 from stunting; it is estimated 44 billion birr will

12 Ethiopian PROFILES.13 Sign of Vitamin A deficiency.14 EHNRI, FMoH, and UNICEF. Iodine Deficiency Disorders National Survey in Ethiopia. (2005).

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productivity as a stunted adult; maternal mortality increases for stunted women; 1.4% decrease in activity for 1% decrease in height

be lost between 2006 and 2015

Vitamin A Deficiency(VAD)

Women: night blindness and spontaneous abortion;Children: growth retardation, increased susceptibility to infection, night blindness, and total blindness; 23% of children’s death can be attributed to VAD

61% of children in Ethiopia have VAD

Iodine Deficiency(IDD)

Goitre, hypothyroidism, impaired mental function, stillbirths, abortions, congenital abnormalities, and neurological cretinism15; IQ is decreased by 10 to 15 points

4.1 million Ethiopian children were born with intellectual disabilities between 2000 and 2005; another 15 million will be born between 2006-2015; between 2000 and 2005 11.3 billion birr were lost; it is estimated 64 billion birr will be lost between 2006 and 2015

Iron Deficiency Anemia(IDA)

decreased blood flow to body organs and tissues resulting in decreased energy; decreased ability to concentrate and impaired cognitive development; increased maternal mortality; IQ is descreased by about 10 points

54% of children and 27% of women in Ethiopia have IDA; it is estimated 36 billion birr will be lost between 2006 and 2015

Zinc Deficiency Loss of appetite; stunting; skin rashes; slowed wound healing

Zinc status is very difficult to assess, however it is estimated 21.7% of the population is at risk for deficiency16

1.20 Vitamin A contributes significantly to immune system function and VAD can lead to growth retardation, susceptibility to infection, and blindness (see Table 1.2). A meta analysis of randomized community-based trials found a 23% reduction in the mortality rates of children between 6 and 59 months17. The prevalence of VAD in Ethiopia is strikingly high, estimated at 27%18. Despite the availability of vitamin A rich foods such as pumpkin, spinach, eggs, mangos, carrots, and organ meats in Ethiopia, only a small portion of rural women consume one of these foods often. Figure 1.4 shows the prevalence of vitamin A-rich foods consumed in the last 24 hours by children and the percentage of children who received a vitamin A supplement in the last six months.

15 A form of iodine deficiency passed on to a fetus which leads to mental handicap, stunted growth, malformations in the bones, and early death. It is not treatable or reversible. 16 Hotz 2004.17 Beaton citation18 Profiles citation

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Figure 1.4: Vitamin A status by wealth quintileVitamin A indicators

0

10

20

30

40

50

60

Lowest second Middle Fourth Highest

Income quintile

% o

f chi

ldre

n

Consumed food rich inVitamin A in past 24 hrs

Given Vitamin A supplementin past 6 months

Source: CSA & ORC Macro (2006).

1.21 There is a striking difference between the number of children in the highest wealth quintile receiving vitamin A through both food and supplements and the number of children in the lowest. However, regardless of wealth, vitamin A consumption is very low in Ethiopia, to which the high rate of VAD attests.

1.22 IDA, which is the number one cause of anemia, is found in 54% of children and 27% of women in Ethiopia. This leads to a lower productivity and a decreased ability to concentrate, both of which have high economic consequences (see Table1.2). Figure 1.5 gives the prevalence of IDA by wealth quintile broken down by its different degrees of severity – mild, moderate, and severe. While mild IDA afflicts a roughly equal proportion of children from each quintile, moderate and severe IDA is relatively higher among the lower wealth quintiles. Despite the severity of these numbers, they fair well when compared to other sub-saharan countries. This can probably be attributed to the consumption of teff, a local grain variety that is very rich in iron.

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Figure 1.5: Iron Deficiency Anemia status by wealth quitileIDA Prevalence

0

5

10

15

20

25

30

35

Lowest second Middle Fourth Highest

Income quintile

% o

f chi

ldre

n

Mild

Moderate

Severe

Source: CSA & ORC Macro (2006).

1.3.2 Current National Indicators: Breastfeeding

1.23 Child feeding practices are heavily influenced by culture, traditions, and availability of alternatives. Introduction of appropriate breastfeeding (BF) and complementary feeding19 practices are key to child survival. They are therefore surveyed and also a central theme of many projects. BF trends tend to be divergent, in that urban babies tend to fair worse (Table 1.3). This is probably because where breast milk alternatives are available, they are more often used. In the absence of public information on the beneficts of BF, women will continue to practive suboptimal BF behavior. This is despite exclusive BF being the cheapest and most healthy alternative.

1.24 A very large proportion of women in Ethiopia do not practice appropriate BF behavior. About a third of babies do not receive BF within one hour of birth (Table1.3). There are significant proportions that continue to exclusively breastfeed well after their babies turn six months in age, even though breast milk cannot provide sufficient, calories, protein, vitamins and minerals at that point.

Table 1.3: Breastfeeding Practices in Urban/Rural Ethiopia% of babies

ever BF% of babies who were BF

within 1 hour of birth% of babies given pre-

lacteal feeds20

Urban 95% 64.8% 38.3%Rural 96% 69.5% 28%

19 The additional foods added to a child’s diet to compliment the breast milk starting at about 6 months of age.20 Pre-lacteal feeds are defined as anything other then breast milk given to a newborn before the initiation of breastfeeding. Examples are animal milk, water, and tea.

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Source: CSA & ORC Macro (2006).1.25 compares BF practices in 2000 and 2005, which have mixed results. First, the chart shows an improvement in the addition of complementary foods at 6 months; however it also shows a decrease in the number of children exclusively breastfeed for the first 6 months of life. Seecond, there is also an increased number of children, ages 6 to 9 months who are not breastfed at all, a worrisome development.

Figure 1.6: Trends in Infant Feeding Practices for Ages 0-5 months and 6-9 months

Source: CSA & ORC Macro (2006).

1.26 It is estimated that in Ethiopia that there are about 50,000 infant deaths a year attributable to poor BF habits,21 that is to say 18% of all infant deaths every year. Inappropriate BF behavior also has a range of other harmful effects (Table1.4). The common practice of giving pre-lacteal feedings has several deleterious effects, including delaying feeding of colostrum, possible introduction of bacteria, and if animal milk is fed, introduction of large proteins that can cause bleeding in the intestine. Colostrum, or the yellow milk, is vital to newborns. It contains antibodies from the mother, which boosts the child’s immune system, as well as elements that help the gut finish developing. Non-sterile water, introduces bacteria, viruses, and other infections to the newborns system before it is sufficiently developed to handle them.

1.27 Most inappropriate BF behavior is clearly due to lack of knowledge regarding appropriate BF behavior, rather than practical or financial constraints in practicing such behavior. This is supported by the fact that there is no evidence of a positive relationship between wealth and optimal breastfeeding behavior. The last point is explored in Chapter 4. One may conjecture that many women in Ethiopia cannot introduce appropriate complementary foods at the right time because of financial constraints, or are unable for financial reasons to avoid work and exclusively breastfeed their babies for the first six months. If this conjecture is true, then wealthier women who 21 Ethiopian PROFILES.

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face less financial constraints would practice more optimal BF behavior than poorer women; yet this relationship is not exhibited by the data. Furthermore, the one-third or so of women who are providing water or other liquids rather than breast milk within one hour of birth (Table 1.3) are probably doing so because of lack of knowledge regarding optimal BF practices, rather than because of financial or other reasons.

1.28 Programs where community volunteers educate women on appropriate BF behavior have been very effective in changing practices, showing that lack of knowledge regarding optimal BF behavior is the main constraint preventing appropriate behavior. These programs have also been shown, furthermore, to be very cost-effective. Chapter 4 discusses the success of the Community Health Promoter program of the NGO Essential Services for Health in Ethiopia (ESHE) in changing behavior. Chapter 5 shows that this program is very cost-effective: for optimal BF promotion, there is a cost per beneficiary of $0.55 US cents, cost per capita of $0.034, and cost per death averted of between $51.37-$62.79. These minimal costs will affect child survival, as well as nutrition security, and long-term productivity because the children will have a healthier start to life.

1.29 The consequences of inappropriate BF practices are far reaching and detrimental. It is difficult to quantify these affects, and they can be assumed to be underrepresented in data. The table below shows the three key behaviors and their associated consequences that are generally the focus of BF education. These three behaviors, initiation within one hour of delivery, EBF for 6 months, and proper introduction of complimentary foods at 6 months, are often are also the key practices that have been focused on in research. Table 1.4 lists some of the consequences when these practices are not followed.

Table 1.4: Consequences of Inappropriate BF Behavior Behavior Consequence of malpracticeInitiation within one hour of birth

Precious colostrum is lost depriving a child of his immune boosting antibodies; dehydration if a child is given nothing or pre-lacteals that can induce diarrhea

Exclusive BF for 6 months Introduction of other liquids or foods before the gut is developed increases intestinal bleeding, food infections, and diarrhea

Introduction of complimentary foods

At 6 months breast milk is no longer a sufficient source of calories, fat, protein, and vitamins and minerals; growth failure begins here secondary to inadequate energy intake

3.30 shows number of deaths averted if the recommended behaviors are followed. The first column, baseline, is the number of under-5 deaths. The second column is the number of deaths less the children who would have been saved had BF been initiated in the first hour of life. The third column shows less the amount of children if EBF were practiced by mothers. If all mother initiated BF within one hour of delivery, under-5 deaths could be decreased by 23,000 per year or 5.5%. If mothers all practiced EBF until 6 months, under-5 deaths could be decreased by 77,000

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per year or 21%. And if mothers introduced proper complimentary feeding at 6 months, 104,000 under-5 children could be saved a year, or 30.6% of deaths averted.22

Figure 1.7: Number of Under-5 Deaths Averted with Proper Feeding Behaviors2324

444421

386340

0

50

100

150

200

250

300

350

400

450

500

Base

line

Initi

atio

n of

BF

in fi

rst d

ay

Excl

usiv

e BF

Corre

ct c

ompl

emen

tary

feed

ing

Thou

sand

s

Optimal BF Practice

Num

ber o

f Und

er-F

ive

deat

hs

Note: estimates are based on results from Jones (2003) and Edmund (2006) and assume about 3.36 million births per year for five years.

1.3.3 Ethiopia from a Regional and World Perspective

1.30 Ethiopia’s level of nutrition security, or more appropriately phrased its level of nutritional insecurity, is best understood in context of its neighboring countries. Ethiopia’s status in comparison with its neighbors as well as sub-saharan african countries (SSA) and other developing countries25 regarding water supply, sanitation, and immunization coverage is presented in Table 1.5.

22 This figure for the number of under-5 children saved if optimal BF was practiced is more than the figure of 50,000 mentioned earlier for the number of infants (those under 1 year of age) saved. This is because suboptimal BF increases the risk of death not only during infancy but also in the later under-5 years.23 24 These numbers are different from those mentioned above: they refer to all under-five mortality, not just infant mortality.25 As defined by UNICEF. Source, State of the Worlds Children 2007. Statistical tables.

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Table 1.5: Water Supply, Sanitation and Immunization Indicators for Ethiopia and Elsewhere

Country/Region

% of Pop using

improved water source

% of Pop using

adequate sanitation facilities

% of children who at 1 year have the following immunizations:

DPT3 Polio3 Measles

Ethiopia 22 13 69 66 59Eritrea 60 9 83 83 84Kenya 61 43 76 70 69Sudan 70 34 59 59 60Somalia 29 26 35 35 35SSA 55 37 66 66 65Developing Countries 30 50 75 76 75

Source: CSA & ORC Macro (2006).

1.31 Ethiopia is lagging behind when compared to Sudan, Eritrea, and Kenya, and indicators are worse in Ethiopia than in SSA or developing nations as a whole. Table 1.5 shows Ethiopia significantly behind in improved water source use as well as proper sanitation facilities. For immunizations, although behind a few of its neighbors, Ethiopia is on par for SSA, but well short of targets to achieve coverage rates of 90% or more. Table 1.6 below shows traditional nutrition and health indicators for various countries and regions. The neonatal mortality rate (NMR) and stunting rate are substantially higher in Ethiopia compared to its neighbors and other developing countries.

1.32 Wasting, on the other hand, is below the levels of Somalia, Sudan, and Eritrea, but above levels in SSA and developing nations as a whole. The under-5 mortality rate (U5MR) and infant mortality rate (IMR) are higher than all neighbors aside form Somalia, and on par for SSA. Maps 1.1 and 1.2 show how Ethiopia emerges as one of the worst few countries worldwide in terms of overall malnutrition rates.

1.33 The figures on stunting and wasting in Ethiopia in Table 1.6 were taken from the 2005 DHS. These are considered the most suitable for cross-country comparisons. However, DHS data do not allow comparisons over a long period of time since only two surveys have been conducted, the other being in 2000. For comparisons over time, as in the next section and elsewhere in this document, data from successive Welfare Monitoring Surveys (WMS) are presented. Data from these surveys use the same nutritional indicators and reference population. Hence, exlucding minor differences in data collections methods, we are able to compare results. The figures for stunting from the latest WMS – conducted in 2004 – are similar to those from DHS 2005. But the wasting rate according to WMS 2004 is 7.9%, significantly lower than the 10.5% rate found in DHS 2005.

Table 1.6: Health and Nutrition Indicators for Ethiopia and ElsewhereCountry/Region U5MR IMR Neonatal MR Stunting

%Wasting %

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Ethiopia 164 109 51 47 10.5Eritrea 78 50 25 38 13Kenya 120 79 29 30 6Sudan 90 62 29 43 11.9Somalia 225 133 49 23 17SSA 169 101 44 37 9Developing Countries 83 57 33 31 10

Source: CSA & ORC Macro (2006).

1.3.4 Ethiopia over time

1.34 When historical data is reviewed, Ethiopia has improved. Indeed, many indicators have had positive progression, especially economic ones. Table 1.7 below shows the GDP per capita since 1994 with the official development assistance (ODA) flows. GDP per capita stayed steady for one decade, increasing suddenly over the last two years.

Table 1.7: GDP and ODA IndicatorsYear 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005GDP per capita 109 112 122 127 115 119 123 129 128 122 135 146

ODA flow (millions)  n/a 876 849 637 648 n/a 693 1080 1307 1504 1823 n/a

Source: World Development IndicatorsNote: GDP per capita is in constant 2000 USD.

1.35 Concurrent with improvements in the economy, the U5MR has improved (Table 1.8). In 1960, Ethiopia’s U5MR was an astounding 294 deaths per 1,000 live births, by 2004 it had almost halved to 166. This is great progress for Ethiopia. However, it should be noted that this progress still leaves it with an U5MR about two times the average rate of other developing countries.

Table 1.8: Under-5 Mortality Rate over TimeYear 1960 1995 1996 1997 1998 1999 2001 2002 2003 2004 2005

U5MR 294 195 177 175 173 176 172 171 169 166 164Source: UNICEF. State of the World’s Children reports 1997 through 2007.

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3.31 As will be demonstrated further in section 3.1, stunting and underweight prevalence have improved significantly since 1996, especially in urban areas (Table 1.9). Rural areas are slower to respond, but both stunting and underweight have dropped significantly in the last decade. Wasting has not had the same fate, with a rise in rates in the late nineties that has not corrected it self to pre-1996 levels as of 2004. shows the percent of stunting at the national level, and by rural versus urban children. There is a clear decline in levels, and it is evident that urban children faired better.

1.36 Figure 1.9 shows the drastic rise in wasting from 1996 to 1998. Though decreasing since 1998, pre-1996 levels have not been attained. Note the stagnant and slight increase in stunting among urban children between 2000 and 2004, while the rate for rural children declined further. This could be because the majority of interventions are targeted to rural areas. This is, in turn, due to the higher malnutrition rates in rural areas, but this graph shows us that urban children should not be ignored. Targeting will be discussed further in Chapter 6.

1.37 Figure 1.10 presents the prevalence of underweight. As was mentioned before, underweight is a composite index for malnutrition, combining measures of wasting and stunting. This can easily be seen here as the level of underweight decreases substaintially as stunting is decreasing, but the leveling off of wasting rates has limited the decrease in underweight prevalence It is this indicator against which progress towards the first MDG will be measured.

Table 1.9: Prevalence of Wasting, Stunting, and Underweight by Gender, Place of Residence and over Time26

Wasting Stunting Underweight

National Level B

oys

Girl

s

Bot

h

Boy

s

Girl

s

Bot

h

Boy

s

Girl

s

Bot

h

1996 7.8 6.9 7.3 67.6 63.8 65.7 47.8 42.9 45.41998 10.7 8.4 9.6 55.9 53.5 54.7 46.5 43.2 44.92000 10.2 8.9 9.6 58.1 55.3 56.7 45.9 44.1 45.02004 8.6 7.9 8.3 48.3 45.4 46.9 37.6 36.1 37.1Rural                  1996 8.0 7.2 7.6 68.4 64.8 66.6 49.3 44.0 46.71998 10.8 8.6 9.7 57.4 55.0 56.2 47.9 44.7 46.32000 10.4 9.2 9.8 59.4 56.3 57.9 47.6 45.6 46.72004 8.8 8.1 8.4 49.9 47.1 48.5 39.1 38.3 38.7Urban                  1996 6.4 4.1 5.3 61.0 55.5 58.4 35.1 33.6 34.41998 9.8 7.2 8.5 42.1 38.9 40.5 32.8 28.7 30.72000 7.0 5.8 6.4 44.2 44.7 44.4 26.7 27.4 27.02004 6.9 6.0 6.5 31.1 27.9 29.6 21.5 20.0 20.8

Source: CSA (2004).

26 CSA. WMS 2004.

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Figure 1.8: Percent Stunting from 1996 to 2004 at National level, and Rural and Urban

25303540455055606570

1996

1998

2000

2004

1996

1998

2000

2004

1996

1998

2000

2004

National Rural Urban

% S

tunt

ing

Boys

Girls

Both

Source: CSA (2004).

Figure 1.9: Percent Wasting from 1996 to 2004 at National level, and Rural and Urban

4

6

8

10

12

1996

1998

2000

2004

1996

1998

2000

2004

1996

1998

2000

2004

National Rural Urban

% W

astin

g Boys

Girls

Both

Source: CSA (2004).

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Figure 1.10: Percent Underweight from 1996 to 2004 at National level, and Rural and Urban

0

10

20

30

40

50

60

1996

1998

2000

2004

1996

1998

2000

2004

1996

1998

2000

2004

National Rural Urban

% U

nder

wei

ght

Girls

BoysBoth

Source: CSA (2004).

1.38 The Gini coefficient27, derived from the data of various Household Income, Consumption and Expenditure Surveys, contains some interesting trends. Figure1.11, below, shows the changes in GINI coefficient over one decade. The GINI coefficient is a measure income inequality; a score of zero means perfect equality, while 1 means perfect inequality. The level has stayed about the same for rural areas over the last ten years, while urban areas have worsened.

Figure 1.11: Gini Coefficient in Rural and Urban Areas from 1995 to 2005.

00.10.20.30.40.5

Rur

alU

rban

Tota

l

Rur

alU

rban

Tota

l

Rur

alU

rban

Tota

l

1995/6 1999/2000 2004/05

Gini Coefficient

Gini Coefficient

27 Measure of inequality. See Glossary.

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Source: PASEP (2007).3.32 shows the percentage of the population with access to safe drinking water from 1996 to 2004. As Table 1.5 above showed, Ethiopia fares worse in adequate water and sanitation compared to its neighbors, but here we can see there have been improvements over the past 8 years. Other notable accomplishments pointed out in the include:

With regard to expansion of rural drinking water supply schemes, construction of 553 deep wells, 1,581 shallow wells, and 150,904 hand-dug wells, 3,977 spring development were undertaken.

In respect to urban drinking water supply, pre-design studies for 266 projects, construction of 44 projects and rehabilitation of 46 projects have been undertaken.

Water supply systems were built or rehabilitated in 83 towns, benefiting some estimated 1.6 million people, studies or design work are underway for another 47 towns.

Figure 1.12: Percent Population with Access to Safe Water Sources

0102030405060708090

100

1996 1998 2000 2004

Perc

ent Rural

UrbanNational

Source: PASDEP (2007).

1.39 To summarize this section, there are noticeable improvements in Ethiopia. However, a wide range of services and improvements have still not reached large segments of the population. Stagnation in wasting rates for urban children is of concern, as well as water and sanitation availability in rural areas. Stunting rates have fallen substantially, but remain among the highest in the world.

1.3.5 Nutrition in the PASDEP

1.40 The National Nutrition Strategy (NNS) needs to be urgently approved and implemented, as called for in the government’s key planning and policy document PASDEP (the Plan for Accelerated and Sustained Development to End Poverty). This strategy was drafted in 2005, but still has not been officially approved; this needs to

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be urgently done. The PASDEP states that a Coordinating Agency for adoption of the strategy should have been established by 2004/05. This has yet to be done, but urgently needs to be, for reasons discussed in Chapter 6.

1.4 FOOD SECURITY VERSUS NUTRITION SECURITY

1.41 Malnutrition and its consequences are best understood according to the notion of nutrition security (NS). NS can be defined as “when a HH attains secure access to food coupled with a sanitary environment, adequate health services, and knowledgeable care28.” The answer to malnutrition is not simply addressing the issues surrounding food security (FS), as is commonly assumed. Rather, we need to acknowledge and treat NS. FS is merely the ‘availability, access, and utilization of sufficient food by all people at all times for an active healthy life.’29 Although NS is affected by FS, it is also influenced by a range of other factors including appropriate breastfeeding, other feeding and child care practices; hygiene; health status and health interventions; immunizations; the perceived status of women in society, and adequate water and sanitation. While it is true that FS plays a pivotal role in the nutritional status of a country, these other factors affecting NS must also be addressed to be able to achieve NS.

1.42 Understanding NS, then, is fundamental to gaining an understanding of the many facets of malnutrition and key to alleviating and preventing it. A sustained multi-sector approach is critical, including interventions to address food, appropriate child care behavior, appropriate behavior regarding breastfeeding and complementary feeding of under-2 children, hygiene, education, improved access to potable water, medical care, and mosquito nets, among others. A program whose goal is to treat FS will not necessarily decrease malnutrition in an area without first understanding and then addressing the NS issues involved. By way of example, providing more food to vulnerable HHs does increase the available calories per person, but does not address the problem of contaminated water that causes high rates of diarrhea, nor any of the several other factors that often lead to malnutrition in vulnerable HHs.

1.43 It is useful to understand the links between FS and the commonly used malnutrition indicators of stunting and wasting rates. Wasting is more related to the current provision and absorption of adequate food than stunting. Areas with high food insecurity tend to have higher wasting rates than food-secure areas, but stunting rates in poorer countries are often high to a similar degree in both food-insecure as well as food-secure areas. This is because stunting is an indicator marking the cumulative impact of illness and dietary intake in a surviving child over time. Wasting is provoked by food scarcity or witholding and poor absorption and often happens at the same time (see Chapter 1). The weak correlation between FS and NS, especially as measured by the rate of stunting, is demonstrated in Chapter 3 using Ethiopia-specific data.

28 Benson 2006.29 Benson 2006.

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1.44 Stunting and even wasting rates can often be substantially improved by education regarding appropriate feeding and childcare behavior, immunizations, improved water and sanitation, and other interventions, even without changing the amount of food provided. In successful large-scale programs addressing malnutrition in other countries, such as those in Thailand, several states in India, and Bangladesh, there are a range of interventions other than provision of food that have been employed. Children are typically weighed by trained community volunteers every month to three months; if they are found to be underweight, then the immediate recourse is not for the program to provide food. Instead, counseling is provided to the mother and other caregivers on appropriate behavior regarding breastfeeding, other feeding, hygiene and child care, and the situation is monitored over time. If the child continues to have an abnormally low weight, then food is provided.

2 CURRENT PROGRAMS IN ETHIOPIA

2.1 CURRENT PROGRAMS AFFECTING NUTRITION IN ETHIOPIA

2.1 Ethiopia is currently served by hundreds of programs, some of which aim to affect malnutrition and others which target one of the basic or underlying causes. These projects focus on food distribution, environmental clean up, water access, veterinary care, primary education, primary health care, adult literacy programs, and many more. Most of these programs do not have ‘decreasing malnutrition’ in their objectives, but in the end will affect child and maternal nutrition status. This chapter highlights a few of these programs, specifically the larger programs affecting malnutrition or health outcomes. It is recognized, however, that there are many other programs that affect Nutrition Security (NS), and they cannot all be explained in this report. Tables at the end of this chapter summarize the information presented herein.

2.2 PROGRAMS THAT GIVE FOOD OR CASH30

2.2 Among programs that give food or cash to beneficiaries it is important to recognize the difference between programs that give them for the explicit purpose of improving nutritional indicators and those that do not. Of the programs listed in this section, only the Targeted Supplementary Feeding Programme and Community-Based Therapeutic programs centers have such objectives. For the others, improvements in nutritional indicators are a byproduct of their main objective of supplying food to the beneficiaries.

30 Table 2.11 has a listing of the program details for each of the programs listed in this section.

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2.2.1 FSP - Food Security Project

2.3 The Food Security Project is a key project for the Ethiopian government. The central aim of the FSP is to help vulnerable, food-insecure communities to increase their incomes and build their assets. It does this by providing funds and technical assistance to communities to enable them to do things for themselves rather than having things done for them. Child growth is a key goal of the food security program, and child growth is more than the availability of food, or even the availability of income. One of the objectives of the FSP is to protect and promote child growth and development, by enhancing HH and community decision making and action on infant and young child feeding and other caring practices. The project has six broad components:

1) Funds to communities/kebeles - the majority of the project;2) Community-based child growth promotion - community funds and capacity

building;3) Capacity building funds to woredas, regions, and Federal Ministries for

specific, project-related activities;4) Investments undertaken at the federal and regional levels to study and launch

initiatives and policies to lower transaction costs in food marketing;5) Investments in communications to ensure transparency; and6) Administration of the flow of funds, monitoring and evaluation.

2.2.2 EFA—Emergency Food Aid

2.4 The meher assessment, conducted in November/December, produces results that are used as a broad national estimate of emergency food aid needs for planning and resource mobilization purposes, but specific allocations of food aid resources are determined and made only after more specific area-by-area and case-by-case assessments are performed to determine acute needs. Food requirements for 2007 are estimated at 106,921 metric tones. This is less than previous years. For the period 2005-2007 the average amount of food aid required in Ethiopia has been 307,221MT.

2.2.3 TSFP—Targeted Supplementary Feeding Programme

2.5 In March 2004, the Enhanced Outreach Strategy (EOS) for child survival began; a key component to that program is the TSFP. TSFP is a partnership between the Disaster Preparedness and Prevention Agency (DPPA), Federal Ministry of Health (FMOH), Regional Health Bureaus (RHB), World Food Programme (WFP), and UNICEF. Specifics on the EOS program will be given in Section 2.3. Here we will discuss the food distribution arm of the program. Beneficiaries of TSFP include children less than 5 years with a mid-upper arm circumference (MUAC) of less then 12 centimeters and/or bilateral oedema and pregnant or lactating women (PLW) with a MUAC less then 21 centimeters who are identified during bi-annual screenings. The beneficiaries receive a food ration every three months. Each beneficiary receives a ration of 25kg of blended food (Famix or CSB) and three liters of vegetable oil. Currently there are 264 woredas in the TSFP program.

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2.6 TSFP is not intended to treat severe malnutrition rather is a preventative measure and provides treatment for moderate malnutrition. In each woreda, 10 to 12 food distribution sites are established and run by local women called food distribution agents (FDA). In addition to distributing food the FDAs are also involved in communication of proper nutrition and feeding techniques. They deliver specific messages in an easy to understand manner for the recipient of the aid. To facilitate the uptake of these messages, the TSFP also distributes posters to each site. These posters, which are written in Amharic, Oromifa, Somali, and Afaric, inform the beneficiaries about proper food preparation techniques and ration sizes. The main objectives of TSFP are to:

Prevent the deterioration of the nutritional condition of children under 5 years and PLW

Prevent severe malnutrition Rehabilitate moderately malnourished Provide supplementary food and promote key nutrition and health messages

2.2.4 PSNP—Productive Safety Net Programme

2.7 In 2004, the introduction of the PSNP marked a dramatic shift in they way the government of Ethiopia (GoE) sought to handle it’s chronically food-insecure populations. The PSNP marks a shift in policy and action from relief response to sustainable development oriented programming. The PSNP provides a way for chosen families to achieve a way out of the cycle of insecurity by focusing on asset creation to stabilize their livelihoods and strengthening their ability to cope with shocks. The program employs a combination of geographic, administrative and community-based targeting to identify consistently vulnerable HHs. These HHs include orphans, PLWs, elderly headed HHs, other labor-poor, high-risk HHs with sick individuals (such as people living with HIV/AIDS), and female headed HHs with young children.

2.8 The PSNP consists of a labor-intensive public works component for HHs with labor and a direct support component to assist more vulnerable, labor-poor HHs. Some beneficiaries receive cash transfers while others receive in-kind transfers. Public works are chosen based on the environmental rehabilitation needs of the community and are chosen by the community. PSNP currently takes place Tigray, Amhara, Oromiya, SNNP, rural Harari, and Dire Dawa.

2.2.5 CTC—Community-Based Therapeutic Care

2.9 CTC is the main approach employed in Ethiopia for the treatment of severe malnutrition. CTC is a new type of program and replaces the old treatment through therapeutic feeding centers. This approach provides a shorter time of inpatient care and has the potential to increase coverage greater than that obtained through typical facility-based care. The methodology is based on early detection and assessment of severely malnourished children in the community and home-based management of children without complications. Children with complications, specifically a loss of appetite or

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concurrent infections still need facility based treatment. What we refer to as CTC in the Ethiopian context is slightly different than the strict definition of CTC. According to the Valid International31 definition, a CTC must comprise a Stabilization Center for cases of complicated malnutrition, an Outpatient Therapeutic Program, Community Mobilization, and a Supplementary Feeding Program to treat moderate cases of malnutrition. In Ethiopia it is common practice to have only an Outpatient Therapeutic Program and Community Mobilization, hence it is this abbreviated version of CTC that is referred to in this report. In places where we refer to a Therapeutic Feeding Program (TFP), it is also this practice we are referring to.

2.10 CTC has strong community volunteer focus for mobilization. Within a woreda there are several CTC sites and one stabilization center. Children are referred to the CTC centers and screened. Those with severe malnutrition qualify for the program. If they have no complications they are put in the out-patient program: they are given a take-home nutritional supplement that is a highly fortified peanut butter paste32. The mothers return each week for their ration and health education lessons. Where resources permit, families are also given a ration of corn-soya blend (CSB) to help decrease leakage of the nutritional supplement to other family members as well as treat moderate malnutrition in the home. Children with severe malnutrition and a complication are referred to an in-patient program called the stabilization center. There the children are fed therapeutic milks in addition to receiving medical treatment. When the appetite returns, the children are released to the out-patient program. CTC is revolutionary because it drastically decreases the time children must spend in in-patient care, thereby decreasing exposure to other sick children, time mothers must stay away from their families, and cost.

2.11 Generally, CTC programs are initiated with the help of an NGO and then handed over to the RHB. These are termed institutionalized CTCs in this document. Two NGOs that are well known for their CTC programs in Ethiopia are Save the Children US and Goal; their modalities are described in Table 2.11.

2.2.6 CHILD—Children In Local Development (school feeding program)

2.12 In 2002 the GoE and WFP began a school feeding program entitled CHILD. This program is targeted at schools in Afar, Oromiya, SNNP, Tigray, and Somali regions provides meals of Famix or CSB for primary school children. The key objectives are to increase attendance as well as improve the children’s ability to concentrate and participate while at school. The schools were chosen using the “Chronis Vulnerability Index” (CVI)33 and, among other critera, gender ratio and accessibility. The program focuses on schools with grades 1-8.

31 Valid International is a leading NGO in the design of CTC programming.32 The most common brand name is PlumpyNut. 33 The Chronic Vulnerability Index CVI) started in 1999. The CVI results from a multi-agency project tasked with the development of a Woreda level baseline of areas needing assistance. Due to a lack of data, however, some regions were not represented in developing the CVI, including Afar and Somali. Nine variables were ultimately chosen and used to develop a list of the most vulnerable Woredas. The list was given to the Regional offices, who had a say in the final decision as to which Woredas should be on the list. This list was used in the implementation of MERET and the school feeding program.

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2.2.7 MERET—Managing Environmental Resources to Enable Transition to more sustainable livelihoods

2.13 MERET was rolled out in 2002 as a food for asset creation program. MERET operates in 72 woredas in five of Ethiopia’s regions. The program provides three kilograms of wheat per day of labor. Participating HH are chosen by local committees within the CVI chosen woredas. Public works projects are identified by local committees and include small roads, dam checking, compost making, and whatever the community identifies as a need.

2.3 PROGRAMS THAT DO NOT GIVE FOOD OR CASH, OTHER THAN THOSE FOCUSING ON COMMUNITY VOLUNTEERS34

2.3.1 EOS—Enhanced Outreach Strategy for child survival

2.14 EOS began in March 2004 as a pilot program with the aim to stem the need for yearly emergency action in chronically vulnerable woredas. EOS is a partnership between the GoE, FMOH, RHB, DPPA, UNICEF, WFP, and various NGOs on the ground. The target population is 6.7 million children aged 6 to 59 months and 1.5 million PLW living in the 32535 most food-insecure woredas. These woredas are in 57 zones and 10 regions of the country.

2.15 EOS is a large-scale mobilization program, unlike any other endeavor in Ethiopia. The specific objectives are as follows:

At least 90% of children 6-59 months given vitamin A every 6 months in the targeted woredas.

Ensure access by children 6-59 months to the following key child survival interventions in the targeted woredas:

De-worming Screening for acute malnutrition and referral to the nearest feeding

centre when appropriate Social mobilization for routine immunization and immunization

against measles for children under two year old Information, education, and communication on infant and young child

feeding; promotion of hand washing, and HIV/AIDS prevention Referral to the TSFP and TFP for moderately and severely

malnourished children 6-59 months and PLW (where being implemented).

2.16 In addition to the above items, EOS also distributes insecticide treated nets (ITN) in areas of endemic Malaria. An abridged version of EOS, called Extended EOS (EEOS), is implemented in most woredas in Ethiopia. It includes all parts except the nutritional screening, and there is no link to the TSFP. 34 Table 2.12 has a listing of the program details for each of the programs listed in this section.35 As defined by UNICEF.

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2.3.2 HEP—Health Extension Programme

2.17 In response to the country’s health crisis, in 2003 the government introduced the Health Extension Program (HEP) as part of the primary health care service. The HEP is a pioneering health service delivery program that aims for universal coverage of primary health care. The program gives priority to the prevention and control of communicable disease through active community participation, with the goal of providing equitable access to health services. The program is based on expanding physical health infrastructure by building Health Posts (HP) in rural areas and developing a cadre of Health Extension Workers (HEWs) who will provide basic curative and preventive health services in every community. To support the HEWs in their work, 50 community volunteers (CV) per HEW will be trained in the kebeles.

2.18 The HEP will place two government-salaried female HEWs in every kebele, with the aim of radically shifting the emphasis of the country’s healthcare system to prevention and to improve uneven resource distribution. HEWs are given extensive training in four health areas as well as personal development training. Table 2.10 describes the 16 health packages the HEWs are asked to focus on in their communities.

Table 2.10 H ealth Extension Workers’ 16 PackagesBuilding and Maintaining a Healthy Home

Adolescent Reproductive Health

Construction, usage, and maintenance of a sanitary latrine

First Aid

Control of Insects, Rodents, and other biting species

Family Planning Vaccination servicesHIV/Aids and TB Prevention and Control

Food Hygiene and Safety Measures

Maternal and Child Health

Solid and liquid waste management Malaria Prevention

Personal Hygiene Nutrition Water supply safety measures Health Education

2.19 HEWs are seen as possible leaders and organizers for many programs in rural Ethiopia. Links between the HEWs and community volunteers from various NGO and RHB projects are a possible way forward. More on this is covered in Chapter 6 (Section 6-2).

2.3.3 WASH—Water Supply, Sanitation, and Hygiene

2.20 The WASH program is collaboration between the Ministry of Water Resources, Ministry of Health, the World Bank, African Development Bank, UNICEF, the UK’s Department for International Development, and other donors. The development objective is to increase sustainable water supply and sanitation services for both rural and urban areas through improved in capacity at all levels. WASH committees are formed at the community level and volunteers are trained and work with HEWs. Woreda, zone, and regional levels all have WASH committees and specified tasks to accomplish program objectives.

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2.3.4 EPI—Expanded Programme on Immunization

2.21 The EPI program was initiated in Ethiopia in 1980. EPI targets all children in need of immunizations. Currently, EPI provides vaccines for six preventable diseases: measles, diphteria, pertussis, tetanus (DPT), polio, and tuberculosis (BCG). Ethiopia has plans to introduce other vaccines such as such as hepatitis B (HepB) and hemophilus influenzae type b (Hib).

2.4 PROGRAMS WITH A STRONG COMMUNITY VOLUNTEER FOCUS36

2.4.1 ESHE—Essential Services for Health in Ethiopia

2.22 In November 2003 John Snow, Incorporated, the Academy for Educational Development, and GoE began the ESHE program. The ESHE project is focused on strengthening health workers’ skills, improving community and HH practices, and assisting in health sector reform. ESHE works in 64 woredas in the three most populous regions of Ethiopia: Amhara, Oromiya, and SNNPR. These woredas were selected jointly by RHB and United States Agency for International Development (USAID) for intensive community mobilization and health system strengthening. These 64 woredas comprise 15 million people.

2.23 A key component of project activities is the Community Health Promoter Initiative. ESHE works with regional and woreda health offices to enable community volunteers to improve community and HH practices and support HEWs. Community Health Promoters (CHPs) mobilize communities for immunization outreach, promote optimal nutrition practices, and improve hygiene and sanitation practices. They also encourage caretakers to seek care when danger signs are present in sick children.

2.24 ESHE also works with RHBs to develop standards of care for child health services that are made accessible to all health workers. Finally, ESHE works with the GoE to increase health sector financial recourses. This work involves collaboration between FMOH, RHBs, and regional finance bureaus.

2.4.2 CBRHA – Community-Based Reproductive Health Agents

2.25 Pathfinder International has worked on reproductive health in Ethiopia since 1964. Their latest program is the Community-Based Reproductive Health Agents (CBRHAs). The CBRHAs conduct home visits to disseminate information as well as attend religious and social community gatherings to spread messages. They provide information on reproductive health, family planning, and methods of contraception. They are working on linking with HEWs and often overlap with ESHE woredas.

2.26 Pathfinder works with the RHBs, the Ministry of Justice and local NGOs, specifically faith-based ones, as they try to bring about positive change in communities. Pathfinder also organizes trainings and donates equipment. 36 Table 2.13 has a listing of the program details for each of the programs listed in this section.

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2.4.3 CGP-FSP – Child Growth Promotion Component of the Food Security Project

2.27 The Ministry of Agriculture and Rural Development along is implementing a Food Security project supported by several donors including the World Bank, the Canadian International Development Agency, Italian Cooperation and the UK Department for International Development. This project, which began in 2002, includes a Child Growth Promotion (CGP) component. However, the CGP did not begin until 2005. The project’s objectives are: (1) support rural HH; (2) increase employment; (3) reduce food costs; (4) improve nutrition in children under two years of age and PLW. The project’s components include:

1) Funds to communities/kebeles; 2) Community-based child growth promotion; 3) Capacity building funds to woredas, regions, and Federal

Ministries for specific project-related activities; 4) Investments at the federal and regional levels to study and launch

initiatives and policies to lower transaction costs in food marketing; 5) Investments in communications to ensure transparency; and6) Financial administration, monitoring, and evaluation.

2.28 The CGP targets 751 kebeles in 50 woredas in four regions: Amhara, Oromiya, SNNPR, and Tigray. CGP relies on trained community volunteers with two models: (1) in Amhara, Oromiya, and Tigray, child weighing and counseling is conducted by Health Animators trained for 30 days; (2) in SNNPR, child weighing and counseling is conducted by Health Extension Agents with support from Health Promoters trained for two days in about five sessions at 1-2 month intervals. In both models, during monthly weighing and counseling sessions, the volunteer working with the mother, records the child's weight on a growth chart, and jointly evaluates the weight gain by making a comparison with previous weights and the growth curve of the reference population. Volunteers also make home-visits, discuss child growth trends with community leaders and members, and prepare reports for monitoring, evaluation, and supervision purposes.

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Table 2.11 Programs that Give Food or Cash in lieu of Food

Program/Intervention

Agencies Handling

Year Began Brief Description Woredas Covered Target Beneficiary

Group

Estimated Total Number Beneficiaries 2007

PRRO--Refugees WFP N/A Provides food for refugees in Ethiopia unable to procure their own Camps in Ethiopia Refugees 104,100

Emergency Food Aid WFP N/A Provides food for relief and livelihood protection in time of

crisis..

Projected to be in mainly Somali and Oromiya regions.

Vulnerable HHs facing a shock N/A

Productive Safety Nets

(PSNP)GoE February

2005

Focuses on asset creation at the HH level; two components: 1) Labor intensive public works programs; and 2) Direct support to HHs. Can be participating in other programs at the same time.

Chronically food-insecure woredas in Tigray, Amhara, Oromiya, rural Harari, Dire Dawa, and SNNPR

Vulnerable HHs within food-insecure woredas defined by number for times the woreda has received Emergency Aid in the previous 5 years; Targeting done using community task forces in each community; a list is created of HHs

7.2 million

TSFPGoE,

UNICEF, WFP

March 2004

One of three components EOS. Using the EOS screening lists, provides supplementary food to identified beneficiaries. Each beneficiary receives a ration of 25kg of blended food (Famix or CSB) and three liters of vegetable oil every three months.

Vulnerable woredas identified by UNICEF; 264 of the EOS woredas in ten regions receive TSFP.

Children under 5 with MUAC <12 cm and/or bilateral oedema and PLW with MUAC < 21 cm

544,000 children under five and 256,000 PLW

CTC (NGOs)

IMC, CARE, Concern/Valid, ACF, GOAL,

SCUS, IR

2000

A child feeding program with two parts:1) In-patient care or Stabilization Centre; and 2) Out-patient care or OTP. This is the only program treating severe malnutrition. Uses PlumpyNut as take home treatment and special milks during in-patient treatment.

N/AChildren under 5 years of age with moderate to severe malnutrition.

46 woredas in 2006

MERET GoE, WFP 2002Food for asset creation; three kg wheat/day of labor on a locally identified needed project (e.g. small roads, dam checking, compost making).

72 woredas in five regions

HHs chosen by local committees within woredas chosen by CVI 609,574

School Feeding or CHILD GoE, WFP 2002

Provides meals (Famix or CSB) and, at times, take home rations to primary school children in order to increase their attendance and ability to concentrate and participate.

Schools in Afar, Oromiya, SNNP, Tigray, and Somali regions

Chose Primary Schools (grade 1-8) using CVI 437,633

Urban HIV/AIDS GoE, WFP 2002 Gives food adequate for one month for bed-ridden PLWHA

or AIDS orphans (at least one parent) 14 urban centersTarget HHs with bed-ridden PLWHA and/or AIDS orphans specifically female-headed HHs

111,000

Table 2.12: Programs that Don’t Give Out Food or Cash in lieu of Food

Program/Intervention

Agencies Handling

Year Began Brief Description Woredas

CoveredTarget Beneficiary Group

Estimated Total Number Beneficiaries 2007

EOS GoE, UNICEF

March 2004

Every six months provides: vitamin A, Measles vaccination, mebendazole (de-worming), and screening for malnutrition with referral to supplementary food and therapeutic food distribution for those who qualify.

325 woredas chosen by UNICEF

Children 6 to 59 months and PLW

6.7 million children under five and 1.5 million PLW

Other immunizations

(EPI)

GoE, WHO, UNICEF 1980

Immunization program with goal of 90% coverage. Currently provides immunizations for Measles, Diphteria, Pertussis, Tetanus (DPT), Polio, and Tuberculosis (BCG). Plans to implement Heptatits B (HepB) and Haemophilus influenzae (Hib) vaccines. All woredas

All non-immunized children, specifically under-fives N/A

HEP/HEWs(see separate table

on HEWs in Chapter 6)

GoE, 2003

Extensive public health program aimed at bringing health care to the rural areas. Goals are preventative, promotive, and basic curative. Key to the program is Health Extension Workers (HEW) who implement 16 packages.

CVI-listed woredas

The community they live and work in N/A

Emergency Non-Food Aid GoE, WFP N/A

Provision shelter, water, first aid, and search and rescue. What is delivered depends on crisis and the needs of the population. N/A

HHs and communities facing a shock N/A

Table 2.13: Programs with a Strong Community Volunteer Focus

Program/Intervention

Year Began Brief Description Incentives for the volunteers Number of

volunteers Woredas Covered Target Beneficiary Group

ESHE 2003

Community Health Promoters (trained volunteers) sensitize their communities to various health messages. CHPs encourage small, doable actions that will empower the community. Key task is to act as role models.

CHPs are not required to change their routine and are only expected to act two hours a week. They are not paid for their time.

About 18,000 CHPs have been trained

64 woredas in Amhara, Oromiya, and SNNP regions

Whole community where the CHPs live

CBRHA N/A

Community-chosen volunteers (CBRHAs) council women house-to-house on contraceptives, sanitation, nutrition, etc. Plan to phase out when awareness and demand has been created.

CBRHAs work several days a week and receive a substantial incentive package of: training with per diems, transport allowance (42-70ETB), shoes and uniforms.

Over 10,000 CBRHAs

Over 250 woredas in Amhara, Oromiya, and SNNP; to a lesser extent in Tigray, Benshangul-Gumuz, and Addis Ababa.

Communities where they live--specifically women and religious leaders

IMC June 2004CTC program with a goal of 4-5 volunteers per kebele. In SNNPR used already trained volunteers getting per diems.

Already receiving incentives from other programs. Started a mother-to-mother referral program; mothers at the CTC were given some training and sent home with a certificate.

 11 woredas in Oromiya and 5 woredas in SNNPR

Children 6 to 59 months who are severely malnourished and their mothers

CTC - Save the Children

US2005 CTC programs. Identifies already trained local

volunteers and utilizes them.

Uses volunteers already receiving incentives e.g. EOS, Malaria, etc., who get per diems.

   

Children 6 to 59 months who are severely malnourished and their mothers.

CTC - Goal 2005CTC Programs. Recruits existing volunteers and keeps in close contact with the kebele health persons for mobilization.

Uses volunteers already receiving incentives and provides health care free of charge to their family and gives T-shirts to volunteers.

2,134 volunteers

1 woreda in Oromiya and 5 woredas in SNNPR

Children 6 to 59 months who are severely malnourished and their mothers.

Child Growth Promotion

Component of the FSP

2002Child growth promotion program focuses on growth monitoring and nutrition education to under-2s.

In-service training quarterly and skill building through on-the-job training.

Between 5 to 8 per kebele--e.g. 3755 - 6008 volunteers.

751 kebeles in 50 woredas in Amhara, Oromiya, SNNP, and Tigray

Children under 2 years in chosen kebeles

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3 MALNUTRITION TRENDS AND ASSOCIATIONS AND NUTRITIONAL INDICATORS

3.4 As already highlighted in previous chapters, Ethiopia has one of the highest child malnutrition rates in the world. Its extreme vulnerability to recurring droughts, coupled with its dependence on rain-fed agricultural production for survival, as well as the generally poor access to adequate health care, safe water and sanitation, makes the Ethiopian population especially susceptible to both long-term and transient malnutrition.37 In this chapter we focus further on malnutrition, firstly providing a disaggregated regional focus before focusing on the determinants of malnutrition. Beyond this we then adopt a specific approach to look at programsimilar to that in the United States similar to that in the United States similar to that in the United States -specific attributes of malnutrition, for example focusing on food-secure versus non-food-secure woredas and considering the differences across malnutrition levels.

3.1 TRENDS IN MALNUTRITION IN ETHIOPIA

3.2 As explained in Chapter 1, child stunting, which is measured as abnormally low height-for-age in under-five children, is an indicator of poor long-run nutritional status or chronic malnutrition and is relatively unrelated to current food influences. Generally, stunting is irreversible. Child wasting, measured as abnormally low height-for-weight in under-five children, is an indicator of acute or more transient malnutrition. This form of malnutrition is more subject to the current level of food influence, but it should also be remembered, as has been noted elsewhere in this report, that there are a broad range of non-food influences, such as hygiene, sanitation, care during illness, and infant and young child feeding practices, that influence all types of malnutrition. Wasting is usually reversible, if the factors that triggered it in the first places are reversed.

3.3 Table 3.14 and Figure 3.13 display the prevalence of malnutrition as measured by Wasting, Stunting, and Underweight over the period 1983 to 2004, based on all available Welfare Monitoring Survey (WMS) data. It can be seen that rural children are more prone to all kinds of malnutrition. Boys are also indicated to be more vulnerable to malnutrition than girls with respect to the three indices, although from the latest round of data we can see that this gender gap is marginal.

3.4 The results of successive WMS surveys have indicated that there is a substantial decrease in the rate of stunting in both urban and rural areas over the last ten years or so. The national trend for wasting has been more mixed in the

37 Children between six and 24 months were found to experience about 0.9 cm less growth over a six-month period in communities where half the crop area was damaged compared to those without crop damage (Yamano, Alderman and Christiaensen, 2005).

44

medium-term, however. The prevalence of wasting rose slightly from 1996 (7.3 percent) to 2000 (10 percent) for both male and female children, before falling to 8 percent in 2004. The prevalence of stunting exhibits a sharp decline over the past eight years, falling from 65.7 percent in 1996 to 46.9 percent in 2004. This is a very favorable trend, given that from the early 1980s until around 1997 the data show that the stunting rate was stubbornly high – among the highest in the world38 – and furthermore on a rising trend, going from 60% in 1983 to 67% 1997.

3.5 From 2000 to 2004 a substantial decline in the level of underweight has also occurred. This follows from the trends observed in stunting and wasting rates; the level of underweight is a composite indicator, incorporating the degree of stunting as well as of wasting.

3.6 Despite these encouraging improvements, it should be recognized that stunting rates in Ethiopia remain very high by developing country as well as regional standards. As shown in Chapter 1, the stunting rate in Ethiopia is higher than in neighboring countries like Sudan and Somalia and is much higher than the developing country average (see Table 1.6). The prevalence of wasting compares favorably with some of Ethiopia’s neighbors, but is still high compared to the rest of Sub-Saharan Africa (see Chapter 1).

Figure 3.13: Prevalence of Malnutrition over Time

Source: CSA (Ethiopia) (2004).

3.7 The national estimates of child stunting and wasting prevalence mask significant urban-rural and regional variations. For example, and as noted in the 2004 WMS, perhaps the largest and most persistent disparities in child nutritional outcomes in

38 Christiaensen and Alderman, 2004.

0

10

20

30

40

50

60

70

1996 1998 2000 2004 1996 1998 2000 2004 Rural Urban

%

WastingStuntingUnderweight

45

Ethiopia exist between rural and urban areas. For the four most recent years for which we have data, child stunting prevalence in rural Ethiopia is 63 percent, versus 50 percent in urban areas. The average disparity in wasting prevalence between rural and urban areas is propotionally similar, with the prevalence averaging nine percent in rural areas and seven percent in urban areas.

3.8 Gender-based disparities are relatively small in Ethiopia, in keeping with the trend in other countries. Malnourishment among boys is slightly larger than among girls. Averaging across four years for which we have data, male stunting prevalence has averaged 63 percent, or four percentage points higher than the prevalence among girls. Similarly, while nine percent of boys in Ethiopia are wasted, only eight percent of girls are. This gender gap has been narrowing significantly over time, as shown by the latest round of data in 2004.

3.9 The improvements in stunting and wasting can be seen from Maps 3.1 through 3.6 in Appendix 4, which are based on WMS data from 2000 and 2004. The downward trends in stunting and wasting rates are very clear and encouraging.

3.10 If we summarize findings by region, we find the prevalence of wasting is highest (16.2 percent) for children in Afar region (Table 3.14 and Figure 3.14). Somali and Tigray regions have a prevalence rate of more than 10 percent. The lowest prevalence of wasting is indicated for Addis Ababa (about 5 percent). Oromiya and Benshangul-Gumuz regions have moderate prevalence of wasting among children (about 9 percent)39. If we consider the disaggregation of malnutrition by woreda we can also see, to some degree, that the split of wasting is roughly representative of the aforementioned regional distribution.

3.11 Stunting levels are highest in Amhara region (58.3 percent) followed by SNNPR. (47.0 percent) and Tigray (45.0 percent), as can be seen from Table 3.14 and Figure 3.15. The lowest level of stunting is registered in Addis Ababa (22.7 percent). The proportion of stunted children in the rest of the regions ranges from 26 percent in Dire Dawa to 37 percent in Somali region. Once again, this distribution across regions is roughly reflected in the map of stunting rates in 2004 in the appendix.

3.12 From these regional figures on stunting and wasting rates, it is clear that there is not a large degree of inter-regional correlation between stunting and wasting. This underlines the principle – mentioned elsewhere in this report – that there is a difference between long-term acute malnutrition as measured by stunting, and shorter-term acute malnutrition as measured by wasting. As explained in Chapter 1, stunting is much less related to food security (FS) than wasting; addressing FS is more likely to reduce wasting than stunting. Ultimately, one needs to address stunting and wasting, as well as other aspects of malnutrition. This means addressing FS as well as nutrition security (NS).

39 CSA WMS 2004

46

Table 3.14: Child Malnutrition 1983-2004 – Global Acute IndicatorsStunting Underweight Wasting

  1983 1992 1996 1997 1998 2000 2004 1996 1997 1998 2000 2004 1983 1992 1996 1997 1998 2000 2004Gender    Male 61 66 67 71 56 58 48 49 48 45 46 38 9 9 8 9 10 10 9Female 59 63 64 64 54 55 46 45 45 40 44 37 8 7 7 7 8 9 8Residence:    Urban 58 55 41 44 30 34 37 30 27 21 … … 6 9 8 6 7Rural 60 64 67 69 56 58 49 48 48 44 47 39 8 8 8 8 9 10 8Region:    Tigray 73 76 58 57 41 55 54 53 53 42 … … 9 10 14 12 12Affar … … 48 61 57 42 41 45 34 31 29 34 … … 18 8 10 11 10Amhara … … 73 75 65 65 56 55 51 49 53 49 … … 9 8 10 11 14Oromiya … … 60 62 50 54 41 39 42 38 40 34 … … 8 7 8 9 10Somali … … 60 65 45 48 45 45 58 40 37 51 … … 3 10 10 12 24Benshangul-Gumuz 59 63 51 51 40 46 44 46 44 44 … 9 4 14 12 16SNNPR 68 66 57 56 52 49 48 40 46 35 … 6 7 7 9 7Gambela 36 48 48 41 29 31 40 40 32 27 … 8 12 8 13 7Harari 54 58 38 47 39 29 30 21 28 27 … 5 7 5 5 9Addis Ababa … 46 52 33 37 18 23 33 19 18 11 … 5 9 4 5 2Dire Dawa … 49 65 34 40 31 38 40 27 31 30 … 14 7 10 12 11Education of Female Adult  No formal education … … 67 69 57 …   49 48 45 …   … … 8 8 10 …Some primary … … 60 62 49 …   38 44 35 …   … … 6 8 9 …Some post primary … … 48 51 38 …   26 32 24 …   … … 5 8 6 …Total 60 64 66 67 55 57 47 47 47 43 45 37 8 8 8 8 9 10 8Note: No data for 1983 and 1992 Underweight Source: Abridged from Christiaensen and Alderman (2004).

47

Figure 3.14: Prevalence of Wasting by Region

Source: CSA (Ethiopia) (2004).

Figure 3.15: Prevalence of Stunting by Region

Source: CSA (Ethiopia) (2004).

3.13 Finally, the prevalence of underweight by region is shown in Figure 3.16. As expected, these regional figures reflect the corresponding regional prevalences of both stunting and wasting, since both of these together are incorporated in the underweight indicator of malnutrition. There is a 12.7 percent underweight incidence in Addis Ababa but the proportions that are underweight goes as high as 45.4 percent for Amhara region.

48

A significant difference is also observed between urban and rural areas of regions. As shown in Figure 3.4, the prevalence rates of underweight of rural children ranges from 28.4 percent in Harari region to 46.3 percent in Amhara region while in urban areas it ranges from 12.2 percent in Addis Ababa to 32.1 percent in Afar region (WMS 2004).

Figure 3.16: Prevalence of Underweight by Region

Source: CSA (Ethiopia) (2004).

3.2 NUTRITION TRANSITION

3.14 The double burden of malnutrition includes both sides of the spectrum: under- and over-nutrition. What has come to be known as the ‘nutrition transition’ refers to the shift in diet in developing countries from traditional foods to highly processed foods high in sugar, fat and salt. The outcome is a society with stunting and obesity, with vitamin deficiencies and chronic diseases such as Diabetes and heart disease. This ‘double burden’ puts considerable strain on government resources. More importantly, in developing nations the rise in obesity and non-communicable diseases generally goes unnoticed as the focus remains on the undernutrition. Obesity and chronic disease first rise in urban areas, where historically there is little attention paid. Rates of diet related chronic disease soar unbeknownst to health ministries worried about wasting and stunting rates in rural areas. The figure below shows the rates of underweight as well as overweight in many developing and transitional countries.

49

Figure 3.5: Nutrition Transition

Source: FAO. FOCUS: The Developing World’s new burden: Obesity.

3.15 As the economy, infrastructure and trade further develop, the ‘westernization’ or ‘urbanization’ of the diet tends to occur. With this comes the rise in obesity, often seen in the same homes as those of stunted children. It seems illogical to discuss obesity in a paper about present day Ethiopia; however one would be wise to learn from neighboring countries. Kenya is currently facing this double burden that comes with development. India, whose malnutrition rates rival those of Ethiopia, is feeling this heavy burden on it’s health care system. Currently, the double burden is minimal in Ethiopia, but it can be safely assumed in 10 to 15 years this will be a significant concern.

3.16 Any long-term planning for Nutrition Security in Ethiopia must include how Ethiopia will face this double burden. Nutritional interventions, when planned appropriately, can be useful for both under- and overnutrition. As the nutrition surveillance system is put in place, it should not leave out the urban areas and should measure not only MUAC for wasting rates, but also the body mass index40 of women to assess for obesity. MUAC can also be used to assess for obesity, though the cutoff points are not as well established as with undernutrition. The nutrition transition that will take place in Ethiopia needs to be kept in mind while policies are being put in place.

3.3 ASSOCIATIONS WITH CHILD MALNUTRITION

3.17 Work prior to this report that has analyzed the determinants of child malnutrition in Ethiopia has often been dominated by the usage of Welfare 40 A standardized ratio of weight to height that is often used as a general indicator of fatness, e.g. health. Calculated as weight in kilograms divided by the square of the height in meters (kg/m 2). A BMI between 18.5 and 24.9 is considered normal for most adults. Higher BMI's may indicate that an individual is overweight or obese.

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Monitoring Surveys, and, as is usual, often used a combination of stunting and wasting rates by z-score and adopted models that focus on children aged below 60 months. Common results have found that the key determinants of long-run child nutrition outcomes in Ethiopia include the following: household income, female adult education, community nutritional knowledge, and food prices. For this work we are able to provide a relatively unique focus on some of the community health-based variables, using data from the DHS of 2005. The full regression results are presented in Appendix 2.

3.18 We adopt the usage of two anthropometric measures, height-for-age and weight-for-height, as dependent variables in the regressions. The use of weight-for-height as an appropriate variable in this type of analysis may be questioned; the onset of severely low weight-for-height is very rapid, while the variables against which it is regressed are relatively fixed. Thus, this format runs the risks of regressing what is in effect a flow variable on stock variables. However, despite this caveat, the information extracted from such an analysis can still provide useful insights A third anthropometric measure, weight for age, is commonly used in the analysis of nutrition – and has been examined in the descriptive section of this chapter. However, as weight-for-age combines the information from both weight-for-height and height-for-age, it generally provides little additional information and will therefore not be used for this section of the analysis.41

3.19 A common finding in anthropometric regression analysis is that there is limited catch up growth after the age of three years. What is meant by this is that the coefficients on the age variables suggest that a malnourished child’s standardized weight or height deteriorates up to the age of three, and only slightly improves thereafter. Thus, and as is commonly highlighted, interventions to improve children’s nutritional status must be targeted to those less than 3 years of age. However, in our analysis we go one step further and break down the age categories of children into 6 month categories.

3.20 We find that the very early period of life (up to 24 months) is relatively healthy for Ethiopian children in regards to wasting. From the DHS survey data we know that the median duration of breastfeeding is 25.8 months, while the mean duration is 25.5 months (there appears to be little difference in the duration of breastfeeding by sex of the child). This length of period is clearly exhibited in the results. Immediately after the weaning period there appears to be a negative shift downwards in current health, with a higher probability of being reported sick and lower weight-for-height, ceteris paribus. One explanation for this pattern is that young children in this age range become more exposed to infection as they gain mobility, while deficiencies in family diet may have more adverse effects as they become less reliant on breast milk.

3.21 The age effects on height-for-age behave rather differently, falling continuously during the weaning period (rather than exhibiting a one-off downward shift) and not bouncing back to the same extent after the children turn 2 years of 41 Another drawback to the weight for age measure is that it is unable to distinguish between chronic and acute malnutrition.

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age. This pattern reflects child height acting as more of an indicator of long-term or accumulated health and nutrition, and is commonly found in developing countries. Past episodes of disease or poor nutrition may continue to affect height, even when the child is currently unaffected by disease or dietary deficiencies.

3.22 As is commonly found, increasing the welfare status, as measured by income, of the household that a child is in is associated with reduced child malnutrition. However, and in line with prior Ethiopia-specific work, the associations are not particularly large. For example, if a child were to live in the highest wealth quintile compared with the lowest, the associated increase in their height-for-age or weight for age z-score would be only 2.7% and 1.3%, respectively, and, interestingly, this is only the case for boys.

3.23 This finding highlights an increasingly frequent observation that economic growth alone will not suffice to reduce child malnutrition in Ethiopia. Since wealthier households generally purchase and consume larger quantities of food, this finding also underlines a theme that appears throughout this report: that food security (FS) is certainly correlated with nutrition security (NS), but the correlation is not particularly large. As has been stressed on a number of times in this report, a multi-faceted approach is needed to address NS in Ethiopia, going beyond interventions that only tackle food insecurity.

3.24 Considering the household public goods, and in particular the presence of a flush toilet in a household42, this has a positive association with child height and weight, particularly for girls.43 Of the other significant variables we were also able to include information on whether afterbirth care was received for the child, if a two month check-up post birth had taken place, and the amount of iodine found in salt (measured in parts per million). The most striking finding from these variables was the consistent finding regarding the differences between boys and girls in relation to afterbirth care. For example, girls that have received afterbirth care are 1.8% more likely to be less stunted than those who have not. Hence, and as indicated by other studies, if mothers obtain their information regarding the benefits of afterbirth care, then this is likely to have benefits of increasing a child’s health status.

3.25 Increased iodine in salt also appears to have some positive association with malnutrition. Although none of the findings are statistically significant we do find that, relative to households that were found to have 30 milligrams of iodine per million in salt, children with less than this amount appear in general to have lower wasting and stunting averages.

3.26 Interestingly, prior econometric evidence has also looked at the benefits of food aid. These studies have found that food aid has helped reduce child malnutrition, though its effectiveness in protecting child growth from shocks has been somewhat muted due to inflexible targeting rules in the face of shocks.

42 Only 1.5% of the population has access to flush or pour toilets according to the 2005 Ethiopian DHS.43 Access to other sources of drinking water were found to have little influence on both children’s height. and weight. They were subsequently omitted from the analysis.

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Children in communities that received food aid grew on average two cm faster in a six month period than if no food aid would have been available44. This helps compensate poor child nutrition and growth in communities that are targeted for food aid. In addition, the total amount of food aid appears on average sufficient to offset the negative effects of damage to the harvest, i.e., through drought or flooding, on child growth in food aid receiving communities. This result is encouraging as it indicates that food aid has indeed been effective in protecting early childhood growth from income shocks in food-aid-receiving communities.

3.27 Yet at the same time, in practice, food aid provision patterns in Ethiopia appear to be largely determined by factors other than shocks, and many communities that experience shocks do not receive food aid. Certain woredas have been labeled as the “Food-Insecure” woredas, and they appear to consistently receive food aid. Conversely, the so-called “Food Secure” woredas are much less likely to receive food aid, even though the available evidence shows that many of these also have high proportions of food insecure people. The “Food Insecure” woredas have generally been identified based on targeting or selection mechanisms applied in the past; some of them appear to receive food aid almost automatically in a year of adverse weather conditions. Yet it is not clear that they are the woredas that are the most affected by the particular pattern of shocks that takes place in any particular year with adverse conditions. Furthermore, among these so-called “Food Insecure” woredas, there are woredas that appear to receive food aid continuously, every year. Conversely, the so-called “Food Secure” woredas which receive food aid only occasionally, or sometimes not at all, often have significant proportions of food insecure people, as indicated by data analysis highlighted below.

3.28 In sum, while food aid has helped to reduce child malnutrition in Ethiopia, food aid targeting tends to be inflexible in the face of shocks. Given the large impact of shocks on child malnutrition, food aid targeting rules more responsive to shocks, as well as other insurance mechanisms, are called for. This would likely help substantially to reduce child malnutrition. Targeting issues are examined in greater detail in Chapter 6, for food aid as well as for several of the other interventions that affect nutrition.

3.4 LINKS BETWEEN FOOD SECURITY STATUS AND MALNUTRITION

3.29 This section attempts to explore the quantitative relationship between food security and nutrition security, using woreda-level data on food aid as well as household and individual level data from the 2004 Welfare Monitoring Survey (WMS) which had national coverage.45 A useful question in the WMS survey that helps in the analysis of this section is one that asked each household head whether or not the household had experienced food shortage in the previous 12 months. If the answer given was yes, the respondent was asked how many months of food shortage had been experienced. Although there is always some subjectivity associated with such self-

44 Yamano, T., Alderman, H., & Christiaensen, L., (2005).45 More precisely, all regions were covered except Gambella.

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reported data, these data – in the absence of better alternatives – can be taken as useful if somewhat rough indicators of households’ food security status.

3.30 Data from the WMS show a very clear and strong positive relationship between the wasting rates among under-5 children – both global and severe – and the self-reported number of months of food shortage experienced by a household within the previous 12 months. This can be seen from Table 3.2 and Figure 3.5. The global wasting rate in 2004 among children from households with 7 to 12 months of self-reported food shortage was about double that of the rate among children from households that reported no food shortage. The severe wasting rate among this first category of children was about two and a half times that of the latter category of children.

3.31 The results illustrates the importance of providing food through properly targeted programs, as one vital category of interventions against wasting. But wasting rates are still very high among children from households that experienced no food shortage within the previous 12 months, underlying the vital importance also of interventions that do not provide food. The global and severe wasting rates in 2004 among children from households that reported no food shortage within the previous 12 months were 7.7% and 1.4% respectively, which are still high by international standards. This illustrates the vital importance, in the fight against malnutrition, of not just providing adequate food to households, but also addressing other factors such as those related to health, water and sanitation, child care and appropriate child feeding practices.

3.32 The data show no clear relationship between the stunting rates among under-5 children and the self-reported number of months of food shortage experienced by a household within the previous 12 months (see Table 3.2 and figure 3.5). This could be due to the fact that the food shortage variable in this analysis measures food shortage within the previous 12 months, and not medium-term of longer-term food shortage. Stunting among under-5 children, on the other hand, reflects the impact of an accumulation of factors over the previous few years – specifically, up to five years, depending on the age of each child at the time of the survey. Thus, it should be more illustrative to restrict the analysis to children aged less than one or two years at the time of the survey.

Table 3.15: Malnutrition Rates in 2004, Among Under-5 Children From Households With Varying Degrees of Self-Reported Food Insecurity

Number of Children in

Sample

Stunting Rate in 2004

Wasting Rate in 2004

Global Severe Global SevereAmong Under-5 Children From Households That Experienced No Food Shortage In Previous 12 Months1 8,406 44.4% 21.6% 7.7% 1.4%Among Under-5 Children From Households That Experienced 1 to 3 Months of Food Shortage In Previous 12 Months 1 1,634 51.0% 28.8% 9.4% 2.3%

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Among Under-5 Children From Households That Experienced 4 to 6 Months of Food Shortage In Previous 12 Months 1 826 54.2% 28.8% 12.0% 2.0%Among Under-5 Children From Households That Experienced 7 to 12 Months of Food Shortage In Previous 12 Months 1 311 46.3% 22.0% 15.5% 3.7%Notes: 1. According to self-reported data from the WMS 2004. Source: Calculations using data from the WMS 2004.

3.33 But even when the analysis is restricted to just under-2 children or just under-2 children, the data show no clear relationship between stunting rates and the self-reported number of months of food shortage within the previous 12 months (see Table 3.2). This underlines the importance of non-food factors on stunting, but there are some important caveats that should be made regarding the data. Unsurprisingly, the relationship between food shortage and wasting is much clearer than that between food shortage and stunting. This illustrates the point that addressing non-food factors is especially important in combating the high stunting rates in Ethiopia. But it should not be concluded that food shortages do not affect stunting. Rather, the relationship between the two is clearly more complex and more indirect than the relationship between food shortage and wasting. Furthermore, the results for the category of households that experienced 7 to 12 months of food shortage are less reliable due to the small sample sizes (108 children for under-2 children and 49 for under-1 children). If this category is ignored, then one does largely see a positive relationship between stunting rates and the extent of food shortage. In addition, there is likely a significant degree of subjectivity in the estimation by households of the number of months experienced of food shortage, and it is possible this could be skewing the results.

Figure 3.5: Malnutrition Rates in 2004, Among Under-5 Children From Households With Varying Degrees of Self-Reported Food Insecurity

0%

10%

20%

30%

40%

50%

60%

GlobalStunting

SevereStunting

GlobalWasting

SevereWasting

Among Children FromHouseholds With NoFood Shortage

Among Children FromHouseholds With 1 to 3Months Food Shortage

Among Children FromHouseholds With 4 to 6Months Food Shortage

Among Children FromHouseholds With 7 to 12Months Food Shortage

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Table 3.3: Stunting Rates in 2004, Among Under-2 and Under-1 Children From Households With Varying Degrees of Self-Reported Food Insecurity

Among Under-2 Children Among Under-1 ChildrenNumber

of Children

Global Stunting

Severe Stunting

Number of

ChildrenGlobal

StuntingSevere Stunting

Among Children From Households That Experienced No Food Shortage In Previous 12 Months1 2890 43.2% 21.3% 1332 30.0% 13.2%Among Children From Households That Experienced 1 to 3 Months of Food Shortage In Previous 12 Months 1 549 52.0% 29.5% 244 42.8% 24.8%Among Children From Households That Experienced 4 to 6 Months of Food Shortage In Previous 12 Months 1 256 56.2% 29.5% 127 42.3% 19.0%Among Children From Households That Experienced 7 to 12 Months of Food Shortage In Previous 12 Months 1 108 45.1% 20.4% 49 35.4% 10.5%Notes: 1. According to self-reported data from the WMS 2004. Source: Calculations using data from the WMS 2004.

3.34 The general finding that Ethiopia’s high malnutrition rates are explained only partly by food shortages, with a huge amount attributable to other non-food factors, is an overarching theme of this report. The finding is in line with previous analysis done on Ethiopia as well as other poorer countries, and echoes the seminal work of Pelletier et al (1995), illustrated in Box 3.1.

Box 3.1: Previous Analysis of the Relationship Between Nutrition Security and Food Security

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3.5 CONCLUSIONS AND POLICY IMPLICATIONS

3.35 Although there appears to have been substantial reductions in levels of malnutrition, especially since 2000, stunting indicators, that are potentially the best indicators of long term or accumulated health and nutrition, indicate that almost half of Ethiopian children remain malnourished. It has already been noted that early childhood malnutrition impairs children’s cognitive ability, delays their school enrolment and attainment in school, but it also increases the risk of future illness.

3.36 According to the analysis of this chapter, the impact of increased welfare status of a household on child malnutrition is positive, but the effects are not particularly large, indicating that economic growth cannot be expected to substantially reduce child malnutrition. Of course on top of this, economic growth and increased household welfare are not always well correlated, a finding that has been played out in other countries. Substantial progress toward the goal of Nutrition Security can only be made by interventions that target measures other than household income and household food security. According to the data work

In their seminal paper, Pelletier et al (1995) use results from the 1992 Rural Nutrition Survey to demonstrate that child nutritional status is “weakly and inconsistently associated with the size of the family’s cultivated area.” This lack of a relationship between areas of food security and the prevalence of malnutrition reveals food alone is an insufficient predictor of nutritional status. As they say, “high levels of chronic malnutrition exist in food deficit and food surplus regions alike.” The two figures below, which were compiled from Pelletier et al’s Table 2, are a striking exhibition of this fact. They show the prevalence of stunting and wasting are virtually unaffected by the size of a family’s cultivated area. (The wasting rate does decrease by two percentage points, but there are only six out of eight-teen regions where there is a significant negative association; eleven Woredas show no association.)

Wasting Rate Stunting Rate

01234

56789

Cultivated Area (ha)

Was

ting

Rat

e

0

10

20

30

40

50

60

70

Cultivated Area (ha)

Stun

ting

Rat

e

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presented above, gains could be made from a focus on health policy such as after birth care, and iodine content in salt.

3.37 Combined with prior evidence about adult education attainment, one can assume that other policies needed to achieve NS should include increasing parental and especially female adult education; strengthening households’ ability to reduce crop damage caused by pests and droughts; and interventions to improve sanitary conditions and health infrastructures. For example, it was clear from the analysis above that there were nutrition-related benefits experienced in children (especially girls) receiving after birth check-ups. Obviously this may be both related to the education/informational benefits received by mothers, as well as the quality of current health services.

3.38 The findings presented here clearly indicate that the correlation between food insecurity and nutritional insecurity is only partial, with a very large component of malnutrition – including wasting – attributable to factors other than inadequate food provision. The overall results confirm the critical importance of non-food factors in the causation of malnutrition, such as factors related to health and knowledge regarding appropriate child care practices.

4 INFLUENCING FACTORS ON MALNUTRITION: A FURTHER FOCUS

4.1 In the previous chapter we provided a detailed analysis regarding firstly the geographical distribution of malnutrition in Ethiopia followed by a comparison of

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malnutrition issues across, for example, food-secure and food-insecure areas. In this chapter we further highlight issues that are of major importance with regards to influencing the path of malnutrition in Ethiopia. We review much of the country-specific evidence that is appropriate for consideration in formulating many of the interventions associated with any child health government policy. In particular the focus is on breastfeeding and related health knowledge, vitamin A, and micronutrient intake.

4.1 BREASTFEEDING PRACTICES

“Put Your Baby on the Breast Immediately After Birth, even Before Placenta Is Expelled, to Stimulate Your Production of Milk”

4.2 It was seen from the first chapter that breastfeeding practices are remarkably important with respect to child health status and malnutrition. Information relating to mothers’ current breastfeeding status of all children less than five years of age was analyzed using data from the Demographic Health Surveys (DHS), and it was found that exclusive breastfeeding declined slightly among children less than six months while timely complementary feeding increased between the years 2000 and 2005.

4.3 Delving further into the data, we can see geographically, across the country, that there is some variation in the median months of BF (Figure 4.17 and Table4.16). Overall, the median duration of breastfeeding was found to be 25.8 months, with relatively little difference in the duration of breastfeeding by sex of the child. Rural children appear to be breastfed for slightly longer duration than urban children, as are children living in SNNP compared with children in other regions.

4.4 The data from the 2005 DHS show that, perhaps paradoxically, optimal BF behavior is more common among less educated mothers than more educated ones. Also, to the extent that there is a relationship between wealth and optimal BF behavior, the two appear to be negatively related. These points are illustrated in Figures 4.2 to 4.5. Figure 4.18 and Figure 4.19 show that the proportion of mothers that provides breast milk within an hour of birth – one of the key components of optimal BF behavior – is highest among mothers with the lowest levels of formal education, as well as the poorest mothers.

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Figure 4.17: Average Length of Breastfeeding by Region

05

10152025303540

Region

No. o

f Mon

ths

Source: CSA & ORC Macro (2006).

Table 4.16: Breastfeeding (%) Practice Disaggregated By RegionAny

Breastfeeding(median months)

ExclusiveBreastfeeding

(median months)

PredominantBreastfeeding

(median months)RegionTigray 25.9 1.6 6.3Afar 24.5 0.4 0.7Amhara 36 4.3 7.1Oromiya 24.6 1.6 3.4Somali 21.8 0.5 2.9Benishangul-Gumuz 23.1 1.6 4SNNP 26.1 1.8 3.2Gambela 36 1.6 4Harari 20.6 0.8 3.1Addis Ababa 25.7 0.6 0.9Dire Dawa 20.3 0.5 5Wealth QuintileLowest 25.1 0.7 3.4Second 27.1 2.6 5.2Middle 25.4 3.0 4.6Fourth 25.9 2.4 4.5Highest 25.3 3.2 2.2

Source: CSA & ORC Macro (2006).

4.5 Figure 4.20 shows that the median amount of time spent on exclusive breastfeeding is lowest among the most educated mothers. According to the WHO

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and other health authorities, mothers should spend six months on exclusive breastfeeding. Figure 4.19 shows that the median period spent breastfeeding varies relatively little by wealth index. The median amount of time spent on exclusive breastfeeding does increase when one moves from the first to the third wealth quintile, but it peaks there and then falls when one moves from the third to the fifth quintile.

Figure 4.18: Breastfeeding Initiation by Education Level

0%10%20%30%40%50%60%70%80%90%

100%

No Education Primary Secondary ofHigher

Education Level of Mother

% o

f Mot

hers

Child breastfedduring first hour

Child breastfedduring first day

Source: CSA & ORC Macro (2006).

Figure 4.19: Initiation of Breastfeeding by Wealth Quintile

0%10%20%30%40%50%60%70%80%90%

100%

Lowest Second Middle Fourth Highest

Wealth Quintile of Mother

% o

f Mot

hers

Child breastfedduring first hour

Child breastfedduring first day

Source: CSA & ORC Macro (2006).

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Figure 4.20: Breastfeeding Practices by Education Level

0%

5%

10%

15%

20%

25%

30%

No Education Primary Secondary ofHigher

Education Level

% o

f Mot

hers

Any Breastfeeding

Exclusive BreastfeedingPredominant Breastfeeding

Source: CSA & ORC Macro (2006).

4.6 However, we can potentially learn significantly more regarding breastfeeding practices by extending beyond descriptive analysis to including econometric regression work, as in Appendix 2. Regression results indicate that slightly different factors influence the lengths of breastfeeding for boys compared with girls. For example, if a household is headed by a female, then this significantly reduces the number of months that a boy is breastfeed compared with girls. Similarly for the heads of households that have completed higher education, compared with no or primary level education, boys in such households are significantly less likely have a reduced breastfeeding period, with simulations suggesting that this may result in as much as a halving of the period of breastfeeding. Of course one should bear in mind that, in addition to the factors that are measured and analyzed, there are a wide variety of factors that influence the length of breastfeeding, such a timing of next pregnancy and maternal illness. It is these factors that can lead to the length of exclusive breastfeeding, which are in turn influenced by the underlying factors of household wealth and the level of education of the primary female care giver.

4.7 According to the aforementioned descriptive data, wealth appeared to have a relatively inconclusive impact on the period that a child is breastfeed. The econometric results provide a further insight with regards to this. They show a gender distinction between boys and girls, with increases in wealth quintiles clearly being statistically associated at 10% with a decrease in the length that a boy is breastfeed.

4.8 However, perhaps most starkly out of all the statistically-orientated results and perhaps of most interest are the community-based health variables and in particular distance to the nearest health centre. For children who live in households that find distance to health centre to be only a ‘small problem’, compared with for

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example a ranking of ‘a big problem’, the girls experience a significant reduction in the time spent breastfeeding. Once again, for boys distance to health centre appears to have no association with this. One cannot automatically discard the possibility that this variation in impact is not due to differnences in demand for health services among HHs as opposed to differences in distance.

4.9 Given that the aforementioned has largely focused on the length of time spent breastfeeding, we can potentially learn significantly more regarding the importance of breastfeeding or at least breastfeeding practices, throughout Ethiopia, by considering more varied data. In particular data from the Essential Services for Health in Ethiopia (ESHE) project is especially valuable in informing us regarding insights for at least some regions. As noted in Chapter 2, ESHE runs a program whereby community volunteers referred to as Community Health Promoters promote optimal BF behavior in communities, among other things.

4.10 Box 4.2 and Table 4.17, derived from the ESHE mid-term report46, suggest that the program has had a significant impact in increasing the practice of optimal BF behavior. After the establishment of ESHE activities, there was an increase in the proportion of mothers exclusively breastfeeding until the age of six months (Box 4.2) and a substantial increase in the prevalence of breastfeeding within one hour of delivery (Table 4.17).

Table 4.17: ESHE - Proportion of Children Aged Under 1 Year Whose Mothers Initiated Breastfeeding within 1 Hour of Delivery

Region Baseline (2004) Mid-line (2006) P ValueAmhara 23% 60% <0.001Oromiya 43% 77% <0.001SNNPR 45% 50% Not significant Source: ESHE (2006).

Box 4.2 Bottle Feeding?

46 ESHE 2006.

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Source: ESHE (2006).

4.11 Another important issue in child nutrient intake is colostrum – the first milk that comes in the first 2 to 3 days after delivery. This is imperative to child survival due to the immunization effect of passing the mother’s immune system to the child and also helps finish the development of the gut. Once again using ESHE-based data we find, as highlighted in Table 4.18 and Box 4.2 that in both SNNPR and Oromiya the change in behavior was significant – from 62% at the baseline to 71% in the current community assessment. The percentage of colostrum given in Oromiya in 2006 was also higher relative to the regional baseline and the baseline of the DHS 2005.

Box 4.3 Yellow Milk – Oromiya

Source: ESHE (2006).

Table 4.18: ESHE - Proportion of Children Who Were Given Yellow Milk (Colostrum)

Region Baseline (2004) Mid-line (2006) P-ValueAmhara 57% 50% Not significantOromiya 62% 71% <0.01SNNPR 35% 45% <0.001Source: ESHE (2006)

4.12 Another important topic for childhood nutrition and survival is complementary foods, as was discussed in Chapter 1. There is more on this in Box4.4.

4.13 The evidence provided in this section underlines one of the the main messages of the first chapter: optimal BF behavior can be significantly influenced by programs where mothers are educated regarding appropriate BF practices which

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can have a large impact on child mortality and nutrition indicators. The relationships shown regarding wealth and optimal BF behavior, as well as regarding mothers’ education levels and optimal BF behavior, indicate that much of sub-optimal BF behavior is due to a lack of knowledge rather than practical or financial constraints. The ESHE results show how a community volunteer program could have a substantial impact on promoting optimal BF behavior, and Box 4.5 shows how such behavior can strongly impact child mortality and child nutrition. Chapter 5 will illustrate how interventions like ESHE, which promote optimal BF behavior, are highly cost-effective.

Box 4.4 The Benefits of Introducing Complementary Foods – Oromiya

Source: ESHE (2006).

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Box 4.5: CASE STUDY: Determinants of Malnutrition in North Wollo, Ethiopia, 2002

A study from Gubalafto woreda, North Wollo zone, Amhara region surveyed 1,471 households with children under age 2 being interviewed, weighed and measured, in addition to mothers’ MUAC also being taken, and a series of focus group discussions. The major findings were:

Breastfeeding: Approximately 60-70% of mothers with infants age 5 months reported that they exclusively breastfeed. Overall it was reported that infants less than six months not exclusively breastfed were five times more likely to be malnourished than exclusively breastfed infants of the same age. A small percentage of mothers (somewhat less than 10%) reported giving newborn babies butter or sugar water (pre-lacteal feed) in the first few days of life.

Complementary Food: Only 49% of all mothers knew the correct age to start complementary feeding. At 8-10 months of age, 20% of the mothers interviewed stated that in the 24 hours prior to the interview their child had only received breast milk. During focus group discussion, some mothers said that a reason for the delay in supplementing breast milk with complementary foods is the risk of diarrhea and some mothers said that it was less expensive to give breast milk than complementary foods

The typical first complementary food offered to infants is liquid-softened bread (kita, chibito, or injera) made from sorghum, teff, or wheat. Chibito bread flour will have added to it either sesame and/or linseeds. When queried, only about two in three mothers (68%) stated that they give green vegetables to young children.

Mothers’ Absence from Child: The study found overall that whether a child was exclusively breastfed was associated with a mother’s absence from her infant for two hours or more. Women of poor and medium economic status spent on average 20 hours/week more time away from home and their infants than better-off women. Although women of all economic status in Gubalafto woreda participate in farm work, the study observed that women of poor and medium economic status are far more likely to be additionally involved in cash-producing activities outside the home such as collecting of firewood and/or dung for sale.

Also the study indicated that mothers in the poor economic group are on average back to farm work at about three to four months post-partum. Mothers in the better-off economic group are more privileged and able to take more time-off (returning to farm work at about 6 months post-partum), permitting more quality time for both optimal breast feeding and other infant care. Source: Kuhl, J. J., (2006).

4.2 VITAMIN A INTAKE

“When Your Baby Is 6 Months Old, Make Sure She Receives Vitamin A Supplementation Every Six Months to Make Her Strong’

4.14 Micronutrients, and in particular vitamin A, can be a key components to the health of mother and child. Vitamin A is an essential micronutrient for the immune system (see Table 1.2). For example, severe vitamin A deficiency (VAD) can cause eye damage. VAD can also increase severity of infections such as measles and diarrheal diseases in children and slows recovery from illness.

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4.15 Generally the availability of experimental evidence on the use of micronutrient supplements provides unambiguous evidence on the relationship of mortality and vitamin intakes in many environments, including ones that show few clinical symptoms of deficiencies. The potential to reduce child deaths by distributing vitamin A on a biannual is particularly dramatic; meta-analysis of field trials indicates that such provision of vitamin A can reduce overall child mortality by 23%47.

4.16 As perhaps expected, vitamin A concentration in human milk is higher in developed countries as in developing countries. This holds true even among the wealthier populations of developing countries, as shown in a comparative study by Bendech (2000) that examined vitamin A levels in the breast milk of affluent and disadvantaged mothers in Ethiopia and their counterparts in Sweden. Vitamin A levels measured at 0.5 to 1.5 months after childbirth were shown to be significantly higher in the Swedish women (47.8 ± 16.2) than in the Ethiopian women, whether affluent (36.2 ± 7.7) or disadvantaged (29.0 ± 9.5). Similarly, the proportion of retinylesters48 in the milk was significantly higher among the Swedish mothers than among the two Ethiopian groups, and the difference was greater among the disadvantaged mothers49.

4.17 For a further focus on vitamin A, once again DHS 2005 provides us with a broad geographic picture of Ethiopia. Table 4.19 summarizes all the essential consumption and supplementation data on vitamin A, for Ethiopia, disaggregated by region and wealth. Overall consumption of vitamin A-rich foods is higher among mothers residing in urban areas, mothers living in Gambela, mothers with at least secondary education, and mothers in the highest wealth quintile. Urban residence, education, and wealth also exert a positive influence on the consumption of vitamin A-rich foods. Consumption of such foods is highest in Addis Ababa, Gambela, and Tigray and lowest in SNNP and Somali.

47 Beaton et al 1993. 48 One of the chemical forms of Vitamin A.49 Bendech et al 2000:31.

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Table 4.19: Vitamin A (%) and Micronutrient Intake Disaggregated By Region and Wealth Quintile

 

Mother Consumed

Fruit-/Veg-rich in vitamin A in past

24 hours

Last-born child consumed food rich in vitamin A in past

24 hrs

Last-born child given vitamin A supplement in past 6 months

RegionTigray 9.5 25.1 65.3

Affar 11.4 9.3 33.3Amhara 13.2 19.2 43.2

Oromiya 33.2 26.4 43Somali 4.6 7.9 38.8

Benshangul-Gumuz 27.8 31.1 27.4SNNP 57.4 35.4 49.9

Gambella 56.5 38.2 39.1Harari 42.7 33.9 36.7

Addis Ababa 35.9 37.9 53.2Dire Dawa 28.8 23.9 46.7

Wealth Quintile Lowest 19.7 16.9 39.5Second 31.6 26.1 42.1Middle 31.3 24 45.6Fourth 26 28.9 49.6

Highest 39.8 37.9 55.4Overall 31.1 26 45.8

Source: CSA & ORC Macro (2006).

4.18 Nearly half of children age 6-59 months received a vitamin A supplement in the six months before the survey. Differences in the consumption of vitamin A supplements by gender, birth order, breastfeeding status and mother’s age at birth are small. Rural children are much less likely to receive vitamin A supplements than children in urban areas. Children residing in Benshangul-Gumuz are least likely to receive vitamin A supplements compared with children in the other regions. Vitamin A supplementation in children rises as mother’s education and household wealth increases50.

4.19 Focusing purely on wealth quintiles and various aspects of vitamin A consumption we can see from Figure 4.21 below that in all instances the proportion of children and mothers both supplemented and consuming vitamin A increases relatively dramatically throughout the wealth quintiles.

50Source: CSA & ORC Macro (2006)..

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Figure 4.21: Vitamin A Consumption and Supplementation by Wealth Quintile

0

10

20

30

40

50

60

Lowest Second Middle Fourth Highest

Wealth Quintile

%

Mother Consumed Fruit/Vegrich in vitamin A in past 24hours

Last-born child consumedfood rich in vitamin A in past24 hrs

Last-born child given vitaminA supplement in past 6months

Source: CSA & ORC Macro (2006).

4.20 Considering ESHE-based data, when we consider vitamin A coverage, from the baseline to the mid-line surveys there were significant increases in vitamin A to children. The same was not true however for post-partum women, which is another target group of ESHE. This is most likely attributable to the EOS campaigns that had started during this time and was mentioned by ESHE in their reports. This is further discussed in Chapter 6.

4.3 IODINE INTAKE

4.21 As noted in Chapter 1, iodine is a vital nutrient that can be provided very cost-effectively through obligatory salt iodization as is done in many countries. Lack of iodine in utero has a range of negative effects, including reduced IQ, spontaneous abortions, and congenital abnormalities. (see Table 1.2). The Ethiopian DHS 2005 tested levels of iodine in cooking salt in households. Salt that contains at least 15 parts per million (ppm) of iodine was/is considered to be adequately iodized.

4.22 Of the households where this test was carried out, only about 20 percent had salt that was found to be adequately iodized51. Place of residence appears to make relatively little difference in iodine fortification levels, and there appears to be no substantive correlation between higher salt iodine levels and higher wealth (see Table 4.20). For example, for households in the lowest wealth quintile 22.1%, were found to have adequately iodized salt (more than 15 parts per million); while for households in the highest wealth quintile, 19.8% were found to have adequately iodized

51 The results showed 20% of HHs used iodized salt. This figure is lower than the same measurement in the 2000 DHS, which showed iodized salt prevalence at 28%.

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salt. From a regional perspective, households in Dire Dawa were found to be most likely to consume salt that is adequately iodized (62 percent) while households in Benishangul-Gumuz least likely (14 percent).

Table 4.20: Iodine Content of Salt in Households Disaggregated by Region and Wealth Quintile

None Inadequate AdequateRegion (0 ppm) (<15 ppm) (15+ ppm)Tigray 43.7 28.3 28Affar 39 38 23Amhara 53.4 31.7 14.9Oromiya 40.3 37.7 22Somali 41.8 33.6 24.7Benishangul-Gumuz 58.7 27.7 13.6SNNP 45.9 35.6 18.5Gambela 34.9 27.4 37.6Harari 41.5 29.7 28.8Addis Ababa 50.4 31.7 17.9Dire Dawa 8.3 29.4 62.3Wealth QuintileLowest 43.4 34.5 22.1Second 48.0 33.4 18.7Middle 44.0 36.2 19.8Fourth 45.9 35.0 19.1Highest 46.9 33.3 19.9

Source: CSA & ORC Macro (2006).

4.4 IMMUNIZATION

4.23 The ability of children to fight off disease is linked strongly to immunization levels. However, according to figures from 2005, immunization coverage for children from 12-23 months of age at the time of the survey ranged from 60% for BCG to 32% for all 3 doses of DPT. Only 20% of the children from 12-23 months of age were fully immunized (Figure 4.22), but the rate had improved from DHS 2000 of 14%.

4.24 There are notable changes in vaccination coverage over the time period 2000 to 2005 according to DHS data, with the overall picture not being uniformly positive. The percentage of children fully immunized by age 12 months increased from 7 percent to 17 percent between 2000 and 2005. The percentage of children age 12-23 months fully vaccinated at the time of the survey increased from 14 percent to 20 percent over the same period. However, the percentage of this age group who had received none of the six basic vaccinations increased from 17 percent to 24 percent.

4.25 Geographically we can see that there is a relatively large distribution for children that are fully immunized. For example, the percentage of children fully immunized ranges from a low of less than 1 percent in the Afar region to 70 percent

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in Addis Ababa. As would be expected, wealth also influences whether a child is immunized fully, with 25% of children in the lowest wealth quintile fully immunized compared with more than 52% of those in the highest quintile

Figure 4.22: Full Immunization Coverage by Region

0%10%20%30%40%50%60%70%80%

Tigr

ay

Afar

Amha

ra

Orom

ia

Som

ali

Beni

shan

gul-G

umuz

SNNP

RGa

mbe

la

Hara

riAd

dis

Abab

aDi

re D

awa

Region

% fu

lly v

acci

nate

d ch

ildre

n

Source: CSA & ORC Macro (2006).

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5 COST EFFECTIVENESS AND BENEFIT-COST ANALYSIS

5.1 COST EFFECTIVENESS AND BENEFIT-COST ANALYSIS: WHAT IS FEASIBLE AND WHAT IS NOT

5.1 This chapter performs Cost-Effectiveness Analysis (CEA) as well as Benefit-Cost Analysis (BCA) for a range of interventions affecting nutrition in Ethiopia – both existing interventions as well as interventions that do not currently exist but could potentially be introduced. CEA compares the cost of achieving a particular goal, such as averting a child’s death, for different interventions. The lower is the cost incurred to achieve that goal for a particular intervention, the more cost-effective is that intervention compared to others with respect to achieving that goal. With limited resources and with a particular goal in mind, the most cost-effective interventions should be chosen to achieve that goal. CEA is discussed in further detail below.

5.2 Benefit-Cost Analysis, on the other hand, quantifies the benefits of each intervention in monetary terms. The ratio of the benefits to the costs or the Benefit-Cost ratio (BCR) is assessed. If this ratio is more than one, then the intervention is desirable on the grounds of having large benefits compared to costs.

5.3 If one has several different outcome gains in mind, CEA should ideally be conducted with regard to each of those outcome gains. So, if one wants to focus on reducing child deaths, then comparing the cost per child death averted of a range of interventions is a useful exercise. But typically, one is at the same time interested also in other outcome gains, such as reducing child stunting or enhancing cognitive development in children. Ideally, one should then also compare the cost per unit/percentage decrease in stunting, or the cost per unit/percentage increase in labor productivity, for each intervention in the spectrum of interventions as well.

5.4 The difficulty is that we lack the quantitative impact data that would enable quantitative measures of cost effectiveness to be computed for all relevant interventions and outcome gains. Below we present quantitative estimates of the cost per child death averted for a range of interventions. However, for most of the interventions, we do not have the data needed to quantitatively compute other cost effectiveness measures, such as the cost per unit/percentage reduction in stunting, or the cost per unit increase in cognitive development in children.

5.5 We address this problem as follows: we compute and present the cost per beneficiary and the cost per capita of a range of interventions, based on the best available data that we have. We also present qualitative measures of the impact of

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each intervention along different dimensions. For each intervention, based on information obtained from the literature, we indicate whether it has a High, Medium or Negligible impact on each of several “good” outcomes: reducing Maternal Mortality, reducing Childhood Illness, Increasing Child Cognitive Development, and so on.

5.6 Where quantitative CEA estimates could be calculated, we attempted to also derive estimates of the Benefit-to-Cost ratio (BCR), focusing each time on different types of benefits. For example, where we could compute quantitative estimates of the cost per child death averted for an intervention, we also computed the BCR of this intervention with benefits calculated solely from valuing the child lives saved – referred to as the “BCR from reducing child and maternal mortality”. The value of a child life saved, or of a child death averted, was assumed in these cases to be equal to the discounted value in the child’s lifetime earnings.

5.7 Where other types of cost-effectiveness measures could be calculated, it was possible to compute BCR measures for other types of benefits. More precisely, for more limited subsets of interventions, we were able to compute estimates of the “BCR from increasing economic productivity” and the “BCR from enhancing child ability”. For these interventions, we were also thus able to compute the total BCR, i.e. the sum of the BCRs from reducing child and maternal mortality, from increasing economic productivity, and from enhancing child ability.

5.8 Nevertheless, there were some interventions for which no type of CEA estimate or BCR ratio could be calculated due to either a dearth of data or a lack or randomized, controlled trials demonstrating its efficacy. No estimates could be derived, for example, for more generalized programs affecting health and nutrition, such as WFP’s School Feeding program and Pathfinder’s Community-Based Reproductive Health Agents (CBRHAs).

5.9 In other instances, the BCRs are only partial. For example, while we calculated the benefits of bednet distribution to reduced child mortality and prevalence of low birth weight, we did not calculate the benefits due to the decreased number of days agricultural laborers are sick, thereby increasing agricultural productivity. Where benefits that were not included into the BCRs are well known, we have attempted to mention them in the text.

5.10 When using CEA, it is important to remember that there is no threshold of cost per outcome gain below which an intervention is classified as cost effective. Rather, there exists a spectrum of possible cost effective interventions, and policy makers are tasked with determining which are feasible to deliver. Health systems require managerial capacity to absorb funds and implement programs, and in many cases in developing countries it may be more efficient for the executing agencies to focus on several interventions rather than spread themselves thin. There are also political and other constraints that may make it difficult to choose one intervention over another one even if the former is more cost-effective than the latter.

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5.11 This chapter draws together data on costs of government, donor, and NGO programs affecting Nutrition Security (NS). It represents a unique attempt to apply CEA for a broad range of nutrition-related interventions in the specific context of Ethiopia. CEA has been done for many types of interventions at the regional and global level. For example, the World Health Organization has instituted its Choosing Interventions that are Cost Effective (CHOICE) program. CHOICE conducts “the general assessment of costs and health benefits” 52 across its 14 regions of focus. But each country has a unique situation, mix of interventions and associated costs, and Ethiopia is no exception.

5.12 Finally, it should be stressed that there is a range of assumptions that necessarily had to be made and that underlie the estimates presented in this chapter. The estimates presented here are indicative and are conditional on these assumptions. These assumptions are presented in detail in Appendix 3.

5.13 A final caveat is that we were not able to take into account the joint effectiveness of multiple interventions implemented simultaneously. This is because no information could be found on this, despite its importance

5.2 COSTING OF CURRENT INTERVENTIONS AND EFFECT ON CHILD MORTALITY

5.14 Table 5.21 presents the cost per beneficiary, cost per capita, cost per death averted and a qualitative assessment of current programs’ coverages in the woredas where they are located. “Current” programs or interventions refers here to programs or interventions currently in existence in Ethiopia. Where a program included more than one intervention, its component interventions have usually been disaggregated and costed separately. For the E/EOS program (the Enhanced Outreach Strategy and the Extended Enhanced Outreach Strategy) we present estimates with and without distribution costs. When the distribution costs were excluded, only the costs of the supplement and its transport to Ethiopia were factored in. For the definition of the “beneficiary” for each program, please see Appendix 3.

5.15 Given that the cost estimates for a program targeting a specific geographical area could not be provided in per capita terms by simply dividing by the entire national population, we calculated the per capita cost using the entire population of the woredas in which the program was located. This provides a more realistic picture of the costs of the program were it to be scaled-up. Of course there are difficulties given that different programs will have different coverages in the woredas they cover. But it was felt that the benefit of having a roughly accurate measure of per capita cost was preferable to none.

5.16 We calculated the benefits from reducing child and maternal mortality by estimating the discounted value of the lost lifetime earnings of each child and of each mother53. Calculating the economic value of a life is complex. We used a

52 Baltussen, R., Adam, T., Edejer, T.T., Hutubessy, R., Acharya, A., Evans, D. B., & Murray C. J. L., (2003)53

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conservatively high discount rate of 5% and valued each year of productive life at the real per capita GDP, which we assumed was $170 in 2007 and will stay constant for the period during which the benefits will accure The productive lifespan was assumed to last from 15 until 43 years of age. The value of a child’s life saved at two years of age was $1,320 while that of a mother’s life saved at 25 years of age was $1,987. The former is much higher because of the high discount rate and the large difference between the lengths of time the benefits start accruing; for children starting work at 15, it is 13 years, while for mothers it is the present year. See appendix 3 for more details.

5.17 As would be expected, programs with a strong community-based volunteer focus have some of the lowest costs per beneficiary54. ESHE, which promotes proper breastfeeding techniques and other practices consistent with the Essential Nutrient Actions, aims for a ratio of 1 volunteer per 50 households. Given that their target audience is the entire community, the beneficiary population is quite large: with an average rural household size of 5.2, there would be 1 volunteer for 260 individuals. Pathfinder, an NGO dedicated to enhancing knowledge of family planning methods and reproductive health, has trained about 10,000 CBRHAs and reaches almost 7 million people.

5.18 As can be expected, programs distributing food have higher costs per beneficiary ranging from $19.38 to $216.67 with an average of $73.28. The MERET program distributes only grain to its beneficiaries, while those receiving Emergency Food Aid are typically given a combination of grain, supplementary food, and oil. The higher costs of these programs are to be anticipated because the cost of the product and its transport to and through the country are quite high relative to other programs. However, they play an indispensable role in maintaining community health, especially during periods of emergency. Three programs disbursing food – PSNP, MERET, and School Feeding – did not have documented quantitative effects on mortality, preventing us from calculating the number of lives the programs saved.55

5.19 In addition to community-based volunteer-focused programs, other interventions with low costs per beneficiary include those of the E/EOS campaign, bednet distribution, and the EPI. As is commonly accepted, bednets are a very low-cost intervention at $0.54 per beneficiary per year. It should be noted that the E/EOS costs represent those for Amhara and Oromiya only. It is probable that these costs would change were the program to be costed for all the regions participating in E/EOS.

5.20 According to our figures, supplying vitamin A excluding distribution is the cheapest way to save a life, at a cost of only around $11. Both types of CTC programs and Save the Children US’s Trained Traditional Birth Attendants have very high costs per death averted, ranging from $620 to $870. Essential Services for Ethiopia in Ethiopia’s (ESHE) Community Health Promoters (CHP), which can save an under-5 life

54 Of course it is necessary to consider the differences between services delivered for each program. For example, CBRHAs are paid a higher per diem, but at the same time they are expected to donate more of their time than the CHPs of ESHE.55 The impact estimates for the two other food distribution programs, the TSFP and Emergency Food Aid, were based on estimates from studies found through a literature review and reasonable assumptions.

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through breastfeeding promotion for $50-60, is another of the lowest-cost-per-death-averted programs. The BCRs for reducing mortality match well with the cost per death averted – vitamin A without distribution and promotion of BF are the top two interventions.

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Table 5.21: Current Programs Costing

Program/Intervention

Coverage in Active Woredas

Cost per Beneficiary Cost per capita

Cost per death averted

BCR from reducing child and maternal mortality

Programs Giving Out Food (or Cash In Lieu of Food)PSNP High $34.94 $6.3428 NA  NAMERET High $39.60 $1.3320 NA  NASchool Feeding High $19.38 $0.7097 NA  NACTC: Typical NGO High $216.67 $1.8667 $836.80 1.65-2.01CTC: Institutionalized Low $102.96 $0.2453 $622.39 2.21-2.70Targeted Supplementary Food High $46.30 $0.9354 $705.54 1.95-2.39Emergency Food Aid High $53.11 $2.4704 $1,053.12 7.16-8.75

Programs Not Giving Out Food (or Cash In Lieu of Food) - Excl. Programs with Strong Community Volunteer Focus E/EOS (w/ distribution) Vitamin A High $0.29 $0.0417 $80.32 17.28-21.12 Deworming High $0.32 $0.2512 NA NA Measles High $0.50 $0.0600 $664.82 2.07-2.53E/EOS (w/o distribution) Vitamin High $0.04 $0.0058 $11.18 123.02-150.36 Deworming High $0.05 $0.0411 NA NA Measles High $0.13 $0.0151 $167.20 2.75-3.36Bednets High $0.54 $0.4986 $441.92 16.87-20.61Immunizations (EPI) High $4.33 $0.0695 NA NAHEWs Low $6.77 $6.7710 NA NAPrograms with Strong Community Volunteer Focus CHP (ESHE) Promotion of optimal BF High $0.55 $0.0341 $57.89 23.75-29.03 Promotion of hand washing High $0.36 $0.0227 $224.21 6.13-7.49 Promotion of construction and use of latrines High $0.03 $0.0227 NA NACBRHAs (Pathfinder) High $0.91 $0.7647 NA NATrained Traditional Birth At. (SCUS) High $12.81 $0.9775 $871.75 1.58-1.93

Note 1: These are estimates for various interventions currently in existence in Ethiopia. Coverage in active woredas was assessed qualitatively as either “High” or “Low”. “NA” is given for interventions where the effect on mortality could not be determined. Per capita coverage was determined using the populations of the woredas in which the program was located. Note 2: PSNP, Productive Safety Net Programme; MERET, Managing Environment, Resources, to Enable Transition to more sustainable livelihoods; CTC, Community Therapeutic Center; TSFP, Targeted Supplementary Food Programme; E/EOS, Extended/Enhanced Outreach Strategy; EPI, Expanded Programme on Immunization; HEW, Health Extension Workers; CHP, Community Health Promoter; ESHE, Essential Services for Health in Ethiopia; BF, Breastfeeding; CBRHA, Community Based Reproductive Health Agents; TTBA, Trained Traditional Birth Attendant.

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5.3 COSTING OF POTENTIAL INTERVENTIONS AND EFFECT ON MORTALITY

5.21 As was discussed in Chapter 1, micronutrient deficiencies are high in Ethiopia. Table 5.22 provides estimates similar to Table 5.21 for several, mostly micronutrient, interventions that are not currently implemented in Ethiopia. Deworming to pregnant women is listed in this table; this intervention is currently provided to under-5 children but not pregnant women as part of the E/EOS. These interventions are very cost effective. With the exception of supplying zinc supplements to children who are sick, the cost per beneficiary of each intervention is below $1. The target groups for each intervention are defined in Table 5.22. To maintain consistency with the E/EOS cost data, where beneficiaries are those receiving the treatment regardless of their deficiency status, the beneficiaries for the fortification programs are assumed to be all of those who will consume the fortified product.

5.22 Supplementation costs per beneficiary were determined by talking to procurement specialists at UNICEF as well as using the 2006 price per supplement as given by the International Drug Price Calculator56. To see the costs used in the calculations, see Appendix 3. In instances where more than one price was quoted per supplement, the lowest or second lowest price was used.

5.23 Program costs, including for transport from the selling to the buying country, as well as for internal transport to patient distribution sites and other administrative costs, can led to a dramatic increase in the total cost of a product after an item has been bought. As part of WHO’s CHOICE program, a study of 17 developing and developed countries was conducted to show the markup of program costs. These ranged from 17% in Denmark to 74% in Afghanistan.57 Given Ethiopia’s large geographic area, land-locked position, and generally poor network of roads, we assumed a value from the higher range, 50%, as representative of the markup for Ethiopia. Thus, a vitamin A supplement that costs $0.10 per capsule is assumed to cost $0.15 by the time it reaches the beneficiary. Additionally, it was assumed that distribution is 100% effective, i.e. there were no excess supplements purchased.

5.24 While a program’s estimated efficacy suggests a high impact on reducing malnutrition or child and maternal mortality, it is important to consider the potential coverage of a program. Treating children with zinc during bouts of diarrhea has a high efficacy in reducing under-5 mortality due to diarrhea, but when delivered through a system where health centers are not easily accessible and there is little awareness of the importance of treatment, the number of lives saved will be low. Below, we assume supplementation interventions delivered through the HEP will result in a medium level of coverage. Iodated oil capsules, which differ from the other supplementation programs in that they only need to be administered once per year, can easily be inserted into the existing mechanism of the E/EOS.

56 http://erc.msh.org/57 Johns, B., Baltussen, R., Hutubessy, R., (2003).

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Table 5.22: Potential Programs Costing

Program/Intervention

Possible/ Likely

Coverage in Active Woredas

Cost per beneficiary Cost per capita

Cost per death averted

BCR from reducing child and maternal

mortality Micronutrient SupplementationIron and folate: preg. women Medium $0.96 $0.0209 $306.13 3.88-4.74Iron and folate: 6-24 mos. Medium $0.50 $0.0325 N/AZinc: 6-24 mos. Medium $1.26 $0.0828 $496.33 2.77-3.39Iodated oil: preg. women High $0.32 $0.0078 $23.12 51.37-62.79Iodated oil: preg. women, 6-24 mos. High $0.32 $0.0397 $117.29 10.13-12.38Deworming: preg. women Medium $0.05 $0.0011 $0.80 746.43-912.31Food Fortification ProgramsSalt fortified w/ iodine High $0.05 $0.0500 $136.78 8.69-10.62Iodized salt fortified w/ iron High $0.45 $0.4500 $6,585.17 0.27-0.33Sugar fortified w/ vitamin A Medium $0.10 $0.0410 $82.12 16.75-20.47

Note: These are estimates for various programs that are not currently in existence in Ethiopia, but which could potentially be introduced. Possible coverage in active woredas is assessed qualitatively as either “High” or “Low”. Where there is no effect on mortality, “NA” is reported. The cost per death averted for iron and folate to pregnant women, and for iron in iodized salt, represent the costs only from averted maternal mortality. Per capita coverage was determined using the populations of the woredas in which the program would be located.

5.25 Some of these interventions have a high cost per death averted, such as iron and folate to pregnant women and iodized salt fortified with iron. Here, as we will see, the mortality benefits from the intervention are smaller than benefits measured along different dimensions such as productivity or ability. Also, iron and folate’s effects on maternal mortality produce a high cost per death averted because maternal mortality is fairly low so there are not that many mothers to save. There are also several very low cost per death averted interventions, such as iodizing salt and deworming pregnant women. The BCRs for these interventions also show some very high and some very low numbers. The highest are supplementation with iodine and deworming to pregnant women, and iron, which affects only maternal mortality is even below one.

5.4 QUALITATIVE ASSESSMENT OF AN INTERVENTION’S IMPACTS

5.26 Many interventions impact a person’s lifetime earnings or welfare, or impact society, though means other than reduced mortality. Table 5.23 is an attempt to consolidate information on the efficacies of different interventions along more dimensions than just mortality. The information for the table was pulled from the Disease Control Priorities in Developing Countries report58 and a review of the literature.

5.27 In general, one should think of vitamin A supplementation/fortification, optimal breastfeeding (BF), and zinc supplementation as having a strong effect on 58 Jamison, G. Breman, A Measham, G. Alleyne, M. Claeson, A. Lopez, C. Mathers, & M. Ezzati (Eds.), (2006). Disease control priorities in developing countries (pp. 271-286). New York, NY: Oxford University Press.

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reducing child mortality and illness. Deworming and Iron supplementation/fortification have large effects on the cognitive development and future productivity of a child, while iodine supplementation/fortification affects both child mortality and cognitive development.

5.28 The Generic Community Volunteer Program with a CGP Component is a conglomeration of activities using volunteer members of the community trained in basic health and nutrition information. These volunteers mainly focus their attention on pregnant women and children less than two years of age. A section below dedicated to community volunteer programs will expand on its activities.

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Table 5.23: Qualitative Assessment of Impacts

Program/Intervention Target group Maternal

Mortality LBW Neonatal Mortality U5MR Childhood

Illness59Childhood Growth60

Cognitive Development/

Function

Labor Productivity/

Education Outcomes

Current

Vitamin A Supplementation Neonates & Infants Low High High Low

Deworming Children High High HighBreastfeeding Children High High High NPotential

Iodine Supplementation 

PLW High High High High HighInfants HighChildren N Low

Iron/Folic Acid Supplementation  

PLW Low Low Low Low

Infants Low LowSchool Age Children Low Low

Vitamin A Supplementation  PLW High N

Zinc DisbursementsInfants High High High NChildren with Diarrhea High High N

Iron Fortification Universal High High High HighVitamin A Fortification Universal High High LowIodine Fortification Universal High High High N High HighDeworming  PLW High High High HighCommunity Volunteer Program with Child Growth Promotion

 PLW & children <2

Low Low Low Low High Low Low

Note: The table gives impacts of inventions by target group along several outcome dimensions. For interventions with a demonstrated lack of impact, “N” (for None/Negligible) is given. Lack of an entry means that no information was available.

59 Childhood illness is a qualitative measure indicating occurrence and severity of illness from birth until five years of age.60 Childhood growth is a qualitative measure of the height of a child; stunting is the result of less-that-average childhood growth.

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5.5 IMPACT ON ECONOMIC PRODUCTIVITY

5.29 Many of the deficiencies/issues the above interventions attempt to resolve work their detrimental effects entirely or partly through stunting and Low Birth Weight (LBW). These two outcomes result in significant economic losses throughout life, leading in turn to reduced economic productivity.61 Table 5.24 presents BCRs where benefits are calculated solely from arresting the losses in economic productivity that result from stunting and/or LBW, for those interventions with a demonstrated effect on reducing these outcomes. The TSFP, which almost certainly has an affect on a malnourished individual’s adult height, is a new program, and, as far as we know, its affect on stunting has not been quantitatively studied. Therefore it is not included in the table; several other interventions are also not included due to lack of information.

5.30 The effect of LBW on future earnings works through several channels, including decreased adult height and cognitive ability. Here we followed Behrman and others (2003) and assume that LBW reduces yearly earnings by 7.5%. Stunting reduces lifetime earnings on its own accord; LBW reduces lifetime earnings through the two mechanisms of increased rates of stunting as well as reduced cognitive ability. We do not separate the BCR from reduced LBW into sub-components due to decreasing stunting and due to increasing cognitive ability, but one could do so if one wanted; the final BCR would not change.

61 Alderman, H., Behrman, J. R., Hoddinott, J. H., (2003).

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Table 5.24: Impact on Stunting, LBW, and Economic Losses

Program/InterventionCost per Beneficiary

Cost per capita Impact on Stunting or LBW

Change in Lifetime earnings

BCR from increasing economic due to stunting or lbw

Emergency Food Aid $53.11 $2.4704cancels out the negative effect of a shock $37 0.26

Bednets $0.54 $0.4986 28% reduction of LBW $99 129.64Salt fortified w/ iodine $0.05 $0.0500 increases bw by 150g $34 4.20Iron and folate: preg. women $0.96 $0.0209 13% reduction in lbw $99 3.83Iodized salt fortified w/ iron $0.45 $0.4500 13% reduction in lbw $99 0.18

Note: costs for bednets are to pregnant women only, costs for Emergency Food Aid are for under-twos only

5.6 IMPACT ON MENTAL ABILITY

5.31 The effects of micronutrients on the mental ability of a child can be quite dramatic. Table 5.25 shows this by listing several current and potential interventions, along with BCRs calculated solely from the benefits due to normalization of an individual’s ability to function mentally. Such interventions can be very cost-effective and can have very high BCRs from the standpoint of enhancing ability. It has been shown that a change in one standard deviation in IQ can change yearly earnings by about 10%62.

Table 5.25: Impacts on Ability

Program/InterventionCost per Beneficiary

Cost per capita Impact on ability

Change in Lifetime earnings

BCR from enhancing child mental ability

Iron and folate: 6-24 mos. $0.50 $0.0325increases IQ in 30% of anemic children by 7.5 points $76

Iodized salt fortified w/ iron $0.45 $0.4500increases IQ in 30% of anemic children by 7.5 points $76

Iodated oil: preg. women $0.32 $0.0078 increases IQ in deficient children by 13.5 points $119 Iodated oil: preg. women, 6-24 mos. $0.32 $0.0397 increases IQ in deficient children by 13.5 points $119 Salt fortified w/ iodine $0.05 $0.0500 increases IQ in deficient children by 13.5 points $119

E/EOS: Deworming w/ dist. $0.32 $0.2512increases IQ in 50% of anemic children by 7.5 points $76

E/EOS: Deworming w/o dist. $0.05 $0.0411increases IQ in 50% of anemic children by 7.5 points $76

Note: It is assumed that a one standard deviation increase in IQ raises yearly earnings by 10%.

5.32 Iodine deficiency substantially decreases the IQ of an individual, impairing the ability to perform mentally as they grow older. By supplementing women these lost 62 Alderman, H., Behrman, J. R., & Sabot, R., (1996).

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earnings can be recuperated, resulting in the extraordinarily high BCR for ability of 455. Even when everyone in the population is supplemented, which results in benefits even higher benefits from increasing ability in school-aged children, the benefits are still about 90 times higher than the costs.

5.33 Decreasing anemia by supplementing young children with iron and folate is another hefty intervention, producing 23 times the economic benefits as the costs. But these results might want to be treated with some caution: a recent study63 has shown that iron supplementation in malaria-endemic areas can lead to increased child mortality.

5.7 TOTAL IMPACTS (MORTALITY, PRODUCTIVITY, AND MENTAL ABILITY)

5.34 Table 5.26 and Figure 5.23 show the total benefit-cost ratios for both current and potential interventions taking into account the affect of the intervention on mortality, growth, and mental ability. The values range from 1.75 for emergency food aid to over 829 for providing pregnant women with deworming medication. (Note that the latter was left out of the graph to show greater detail for the other observations.) The mean value is 102 and the median.18.6. When the high value for deworming to pregnant women is removed from the calculations, the mean becomes 67 and the median 13.4. Every intervention we have looked at has a BCR greater than one, indicating that each produces more economic gains than its inputs require. The extremely high BCR for deworming to pregnant women can be explained through the low cost of supplying only pregnant, rural women with one capsule, costing $0.05 per year. There is a dramatic difference between the costs of E/EOS components with and with out distribution. As an example of this, assume that the E/EOS takes place for the sole purpose of distributing vitamin A. If this was the case then there would be no distribution costs for the deworming and measles components, making their BCRs 368 and 3.0 instead of 60 and 2.3, respectively.

5.35 On the whole the most highly cost effective interventions consist of fortification and supplementation programs, and the E/EOS components without distribution costs. Emergency Food Aid and the TSFP fall below the mean and the median, but both provide more benefits than costs; in the case of Emergency Food Aid it is eight times as much. Both CTC programs and the iron fortification BCRs are also below the mean, although still very cost effective. The community-based volunteer programs are spread throughout the range, with optimal breastfeeding promotion having a high BCR and TTBAs the lowest BCR. Promotion of hand washing falls below the median.

5.36 So how does one determine which interventions are cost effective and which are not? One option promoted by the Macroeconomic Commission on Health argues that an intervention is cost effective if it costs less than three times GDP per capita64. Figure 5.25 goes further and depicts the cost per death averted for the interventions where this indicator is below one time per capita GDP. The graph includes all the interventions we are considering here. The graph depicts a similar ranking as that

63 64 WHO Commission on Macroeconomics and Health. (2001).

84

in Figure 5.23 where total BCRs were depicted, with many micronutrient interventions shown to be among the most cost effective interventions. Deworming pregnant women is the cheapest way to save the lives of children under five, representing its low costs of implementation and a high effect on reducing mortality.

Figure 5.23 Benefit-Cost Ratios for Current and Potential Interventions

0

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Note: Graph shows total benefit cost ratios (BCR) for current and potential interventions, from reducing child/maternal mortality, increasing economic productivity and enhancing child ability. Deworming medication to pregnant women, with a BCR of 829, has been omitted to show more detail for the other interventions.

5.37 Figure 5.25 shows the cost per death averted for the remaining interventions affecting mortality. Emergency Food Aid and Trained Traditional Birth Attendants are the most expensive ways to save a live.

5.38 These cost-effectiveness and BCR estimates should be interpreted with caution. It should not be assumed that interventions with lower estimates for the cost per death averted should be advocated at the expense of other programs. It is critical to also use other indicators to evaluate and compare programs. For example, CTC programs are expensive, high-cost-per-death-averted interventions. However, at present in Ethiopia, CTC programs are the foremost way of treating severe malnutrition, and there is no low-cost substitute. It should be emphasized that each of the interventions included in this analysis has been found to have a BCR above one, usually well above one, and each one serves an important purpose.

85

86

Table 5.26: Total Benefit-Cost Ratios from Reduced Mortality, Increased Economic Productivity, and Increased Child Ability

Program/Intervention

BCR from reducing child

and maternal mortality

BCR from increasing economic productivity

BCR from enhancing child

ability BCR totalCommunity ProgramsCTC: Typical NGO 1.65-2.01 NA NA 1.83CTC: Institutionalized 2.21-2.70 NA NA 2.45Targeted Supplementary Food 1.95-2.39 NA NA 2.17Emergency Food Aid 7.16-8.75 0.26 NA 7.42-9.01Programs Not Giving Out Food (or Cash In Lieu of Food) - Excl. Programs with Strong Community Volunteer FocusE/EOS (w/distribution) Vitamin A 17.28-21.12 NA NA 19.02 Deworming NA NA 60.19 60.19 Measles 2.07-2.53 NA NA 2.30E/EOS (w/o distribution) Vitamin A 123.02-150.36 NA NA 136.69 Deworming NA NA 368.00 368.00 Measles 2.75-3.36 NA NA 3.05Bednets 16.87-20.61 129.64 NA 30.43-33.72Programs with Strong Community-Volunteer FocusCHP (ESHE) Promotion of optimal breastfeeding 23.75-29.03 NA NA 26.39 Promotion of hand washing 6.13-7.49 NA NA 6.81Traditional Trained Birth At. (SCUS) 1.58-1.93 NA NA 1.75Micronutrient Supplementation ProgramsIron and folate: pregnant women 3.88-4.74 3.83 NA 7.71-8.57Iron and folate: 6-24 mos. NA NA 23.15 23.15Zinc: 6-24 mos. 2.77-3.39 NA NA 3.08Iodated oil: pregnant women 51.37-62.79 NA 455.34 506.71-518.13Iodated oil: pregnant women, 6-24 mos. 10.13-12.38 NA 89.77 99.90-102-13Deworming: pregnant women 746.43-912.31 NA NA 829.37Food Fortification ProgramsSalt fortified with iodine 8.69-10.62 4.20 71.27 84.16-86.09Iodized salt fortified with iron 0.27-0.33 0.18 1.67 2.12-2.18Sugar fortified with vitamin A 16.75-20.47 NA NA 18.61

Note: “NA” indicates the intervention has no effect on that outcome according to our definition here. The BCRs of Emergency Food Aid and Bednets are not additive as the different catagories of benefits are accuring to different target groups, which have different costs. The total BCRs are therefore the sum of the benefits divided by the sum of the costs.

87

88

Figure 5.24: Costs per Death Averted, for the More Cost-Effective Interventions

$0$20$40$60$80

$100$120$140$160$180

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5.39 Figure 5.26 compares the per capita cost of an intervention with the number of under-five lives the intervention would save were it to be scaled-up nation-wide. Some of the lowest cost per capita interventions are able to save the most lives. To make the numbers of lives saved comparable among interventions, they were scaled-up to assume that they were implemented nation-wide. The graph shows that providing deworming medicine to pregnant women and emergency food aid save the most lives. This shows that the efforts to include deworming medication distributionand to distribute emergency food aid during times of shocks, are on the right track.

5.40 This comparison of the interventions’ effects with the costs each program would incur if implementing it are a useful tool in the design of health system programs. It can provide suggestions as governments attempt to meet their MDG target on child mortality on a limited budget.

Figure 5.25: Costs per Death Averted, for the Relatively Less Cost-Effective Interventions

$0

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Figure 5.26: Number of Under-5 Deaths Averted and Cost Per Capita for Various Interventions

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020406080100120140160180 Thousands

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Cost per capita

Deaths avertedNote: The baseline for under-five deaths represents the number from 2005. Each of the possible scenarios is based on a scenario of scaling the program up nation-wide.

5.8 COMMUNITY VOLUNTEER PROGRAMS

5.41 Community volunteer (CV) programs play a large role in providing health and nutrition services in Ethiopia. Table 5.27 provides descriptions and program details for community-based volunteer programs examined in this study. It also provides details for a “generic community volunteer program with child growth promotion”. The major dimensions along which we are interested in this section are: number of days of pre-service and in-service training; per diem for training; and incentives, other than per diems, that might influence the performance of the CV.

5.42 The generic CV program is meant as an example of a program that would be fairly inexpensive but very useful for large-scale, rural implementation in Ethiopia. It is modeled along the lines of community-level programs that have been integral parts of large-scale and successful programs combating malnutrition in countries like Thailand and Bangladesh. The generic CV program presented here is similar in

content to ESHE’s Community Health Promoters (CHP) program, where community volunteers are trained in basic nutrition and health knowledge, such as on optimal breastfeeding and the importance of vaccinations, and asked to transfer this knowledge to the community during informal meetings.

5.43 But the generic program has an additional component – growth monitoring and promotion – that tasks the CV with the weighing and monitoring of all children less than two years of age. When a child is found to be faltering in his/her growth, the CV is supposed to counsel the parents of the child to determine the cause. If the faltering continues, the CV places the child in a targeted supplementary food program. The costs of the generic program are based on informed estimates.

5.44 Table 5.28 outlines specific costs per beneficiary of the CV-focused programs. Included among the beneficiaries are all those that lived in the kebeles covered by the program for at least one year. Since many of the programs in the table have been implemented for four years, we incorporate the costs four years of the generic CV program as well. Thus there are three years of in-service trainings, and four years of food costs65, which assume that two percent of children less than two years old required food and that the cost per child placed on food aid was $75. We decreased these costs by 10% per year over the four year period because fewer children each year would require it.

5.45 ESHE’s per-beneficiary costs are less than the costs per beneficiary for the CBRHA and TTBA programs. The breakdown in the table shows that payments for personnel are typically the largest component of a program’s cost. Pathfinder’s high supply costs are due to the $5 million in condoms that the CVs distribute annually. Estimates for transport, personnel, and overhead costs could not be made for the generic program.

5.46 One point of interest regarding EHSE’s program involves the recently implemented change in training strategy. Previously, EHSE’s training costs consisted of bringing EHSE facilitators and CV trainees to a central location in the woreda to be trained. There were significant cost outlays here that, if the government was expected to continue the program after ESHE leaves, would be a significant burden. From now on, ESHE has decided to decrease its training costs by about four times by instead having the CVs trained by the HEWs in the community. This would eliminate the per diems to trainees and trainers as well as the transport cost of the trainers. It would also eliminate the incentives such as shirts and umbrellas that ESHE now gives to the CVs for training. The new training strategy envisions HEWs conducting meetings with CVs on a more informal basis, perhaps discussing the material over a period of months rather than days. The impacts of this change in training are not known; whereas previously people were effectively paid for their participation, they will now receive nothing. It will be interesting to see whether ESHE will continue to maintain their relatively high level of impact.

Table 5.27 Community Volunteer Programs

65 Here we are assuming perfect food aid targeting. Given our finding presented earlier, this is probably not realistic, but for now, our closest estimate. Chapter 6 discusses targeting in greater detail.

Program Description Per diem (birr/day)

In-service training

CHPs (ESHE)

Supporting child survival strategy across EPI and IMCI programs based on the ENAs

through community volunteers trained to be role models and to transfer knowledge/practice

into the community

50 pre-service40 in-service

one day per quarter in-

service

CBRHAs (Pathfinder)

Improves knowledge of family planning methods by counseling through a

community-based volunteer who also distributes free

contraception

60 pre- and in-service one day per

quarter

TTBAs (Save the Children US)

Trains traditional birth attendants in methods of clean

delivery and basic ENA counseling to postnatal women

35 pre- and in-service

one day per month

Generic CV with CGP

Uses community volunteers to counsel pregnant and lactating

women and families with young children in the ENAs; and weighs and monitors /

promotes growth of children below two years of age

50 pre- and in-service

one day every other

month

Note: CHP, Community Health Promoter; ESHE, Essential Services for Health in Ethiopia; CBRHA, Community Based Reproductive Health Agent; TTBA, Trained Traditional Birth Attendant; CGP, Child Growth Promotion.

Table 5.28 Component Cost per Beneficiary for Community Volunteer Programs

Cost per Beneficiary BeneficiariesProgram Training Transport Supplies Personnel

Over-head Total

CHPs (ESHE)              BF 0.12 0.12 0.02 0.24 0.04 0.55 preg womenHand washing 0.08 0.08 0.01 0.16 0.03 0.36 preg womenLatrines 0.01 0.01 0.00 0.01 0.00 0.03 80% of the population

CBRHAs (Pathfinder) 0.04 0.06 0.63 0.18 0.02 0.93 entire population

TTBAs (Save US) 5.26 0.61 0.25 5.87 0.82 12.81 preg women

Generic CV with CGP            

preg women and children under two

without food 1.23   0.89        with food     2.33        

Note: The table depicts costs per beneficiary by component for the life of each project. The transport, personnel and overhead costs for the Generic CV program could not be estimated.

5.47 Table 5.29 presents the total cost and cost per beneficiary of the generic CV program when dimensions of cost are varied. It assumes the program will cover 150 woredas and that each woreda has a population of 150,000. As mentioned above, beneficiaries are pregnant women and children less than two years old. The program’s default or “starting” scenario is one where the per diem for training is 50 birr; there is a pre-service training period of 20 days; and there is in-service training of one day every other month, with each trainee obtaining a raincoat, a bag, and shoes.

Table 5.29 Cost Variations for Generic Community Volunteer Program

Cost per trainee per

yearTotal Cost

Change in Cost per Woreda

Total Change in Cost

Change per beneficiary

Per diems(pre and in-service), birr    

35 171.11 102,666.67 -44,000.00 -6,600,000.00 -1.0950 244.44 146,666.67 0.00 0.00 0.00

65 317.78 190,666.67 44,000.00 6,600,000.00 1.09Length of pre-service training, days    

10 55.56 33,333.33 -33,333.33 -5,000,000.00 -0.8320 111.11 66,666.67 0.00 0.00 0.00

30 166.67 100,000.00 33,333.33 5,000,000.00 0.83Frequency of in-service training sessions

    

monthly 266.67 160,000.00 80,000.00 12,000,000.00 1.98bimonthly 133.33 80,000.00 0.00 0.00 0.00Semi-annually 44.44 26,666.67 -53,333.33 -8,000,000.00 -1.32

Length of in-service training per session, days    

1 133.33 80,000.00 0.00 0.00 0.002 266.67 160,000.00 80,000.00 12,000,000.00 1.98

3 400.00 240,000.00 160,000.00 24,000,000.00 3.97Additional incentives

    

Hat 2.22 1,333.33 1,333.00 199,950.00 0.03Torch 5.56 3,333.33 3,333.33 500,000.00 0.08Shirt 2.00 1,200.00 1,200.00 180,000.00 0.03Raincoat, bag, shoes 4.44 2,666.67 0.00 0.00 0.00

Note: The table shows the change in the cost per beneficiary resulting from changes in different aspects of the generic community volunteer program. The default or “starting point” is a program that pays 50 birr per training-day, has 20 pre-service training days, and has bi-monthly in-service training for one day.

5.48 Variability of cost due to the length of time in pre-service and in-service training, as well in the per diem paid, is of particular interest. It is common sense that increasing training produces volunteers more adept at promoting their nutrition and health messages; but despite an extensive literature review, no studies documenting such an effect were found. In the end, it is a balance of costs and time. The literature does, however, mention the importance of per diems and other incentives for motivation and long-term survival of the program; incentives, such as t-shirts, are so common they are assumed to be entitlements by many in Ethiopia.

5.49 The table shows that decreasing the per diem by 15 birr will decrease the total cost of the program by about six and a half million dollars with the cost per beneficiary changing by $1.09. Increasing the pre-service training time by half will increase the total cost and cost per beneficiary by five million dollars and $0.83, respectively. Frequency and length of in-service training have a particularly strong affect on the cost of the program.

5.50 In order to estimate the effects of the generic program on the nutrition status of the woredas, we turned to the literature. It has been estimated that many such programs have a large impact in their first year followed by years with more moderate improvement.66 If this were to be the outcome of such a CV program in Ethiopia, Figure 5.27 presents what might be the results. It assumes a decrease of 8% in both moderate and severe malnutrition in the first year followed by four years of 2% decreases. Moderate malnutrition would fall by 6.2 percentage points from 27.3% to 21.2% and severe by 2.3 percentage points 11.1% to 8.3%. Another trend that has been noticed in programs such as these is the decrease in severe malnutrition at the expense of moderate malnutrition; while the severely malnourished children improve their status, they do not improve it enough to break the ranks of moderate malnutrition67.

Figure 5.27: Projected Effects of the Generic Community Volunteer Program

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5.9 THE HEALTH EXTENSION PACKAGE – HEALTH EXTENSION WORKERS

5.51 The Health Extension Package (HEP) represents a commitment by the government to expand access to health care. We include here a brief description of the costs for this program. A more extensive study might examine the impacts as well as the costs for each of the 16 packages that HEWs are supposed to implement.

Table 5.30: Cost Per Beneficiary for each of the 16 HEW Components

Component Cost per

66 Mason, J. B., Deitchler, M., Gilman, K., Shuaib, M., Hotchkiss, K., Mason, K., Mock, N., & Sethuraman, K., (2002).67 Shantha Vaidyananthan, Consultant, World Bank, personal communication, May 2007.

BeneficiaryMaternal & Child Health 1.71942Immunization 0.642464Family planning 0.915671Adolescent & RH 0.062379Nutrition 0.2295Family Health Service (FH) 3.569435 HIV/AIDS and other STI 0.598617 TB prevention and control 0.048517 Malaria prevention and control 2.112464 First Aid 0.176276Disease prevention and control 2.935874Safe excreta disposal 0.062379 Solid and liquid waste disposal 0.058914Water supply and safety 0.149017Food hygiene and safety 0.086638Healthy home environment 0.06931 insects and rodents control 0.051983Personal hygiene 0.051983Environmental Health 0.530223

Note: These are annual total costs, including medicine, wages, and training, where the training costs are annualized, assuming an HEW tenure of 10 years.Note: This data was collected and prepared by the XXX.

5.52 Table 5.30 presents the costs for each component of the HEP program. These include all costs, e.g. construction, personnel, training, supply and transport, and have been annualized where necessary. The most expensive of the three HEW areas of focus is the Family Health Services at $3.57 per beneficiary, with the cheapest is Environmental Health (Figure 5.28). A review of the HEW program showed a higher ability in Environmental Services and also that components in this area were more likely to be implemented than those in other, indicating it is a cost effective area. All of the components of HEP serve to better the nutrition security of Ethiopia, and in general these costs are low for a country-wide health program as extensive as HEP.

Figure 5.28: Cost per Beneficiary for the Three “Focus Areas” of the HEW

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5.10 SUMMARY AND POLICY RECOMMENDATIONS

5.53 In this chapter we have conducted CEA and have examined the BCRs for both current and potential interventions. We have also explored the cost by component, and effects of variations in dimensions of cost, for different community volunteer programs; and we have examined a cost breakdown of the HEP Package by component. Now we will try to distill some recommendations a policy maker might find useful in interpreting these results.

5.54 The first lesson is the extremely high cost effectiveness and extremely high benefit-cost ratios for micronutrient interventions. Seven of the twelve interventions above the median benefit-cost ratio are micronutrient interventions (Figure 5.23). These micronutrients increase economic gains through reducing mortality, increasing productivity, and increasing child ability. Iodine does all three, and supplementing pregnant women with iodated oil has a high benefit-cost ratio, 512. Even when the costs are increased to distribute capsules to children under 2 years of age, the benefits are still about 100 times greater than the costs.

5.55 Iron and folate supplementation to 6-24 month olds has a remarkable impact on their future productivity, resulting in benefits exceeding costs by 23 times. Deworming medicine and bednet distribution are not micronutrient interventions, but their economic benefits are very impressive: bednets and providing deworming medicine to pregnant women have economic gains that are 32 and 829 times higher, respectively, than the costs. The numbers presented in this chapter, focusing on the reduced mortality and increased ability in infants and young children, still do not paint the whole picture, since a variety of benefits have not been captured in the estimates.

5.56 A second lesson is the large gains to be had from community volunteer programs. CHP promotion of optimal breastfeeding was a high ranking intervention. Overall, our volunteer programs had benefits that exceeded costs by two to twenty-six times. It should also be remembered that it is difficult to quantify all of the benefits from

health and nutrition promotion, and so a variety of types of benefits have not been captured in our estimates. Volunteer messages comprise more than one specific component and their impacts can be diffused among the whole population rather than specific beneficiaries, substantially increasing the gains we have calculated here.

5.57 In particular, and following the experience of large-scale and successful programs combating malnutrition in countries like Thailand and Bangladesh, the generic community volunteer program we have portrayed could have a large impact on nutrition status in Ethiopia. Its volunteers would receive training two to ten times as long as the TTBAs of Save the Children US or ESHE’s CHPs, respectively, but its training cost would still be not much more than that $1 per beneficiary. Our table detailing variations in total cost and cost per beneficiary for changes in dimensions of cost could be a useful tool in the planning of such a generic CV program.

5.58 The third, and overall, lesson to be learned is that there are high levels of benefits compared to costs for all of the interventions we have considered. For each intervention the benefit-to-cost ratio has been computed at greater than one. For many, it is much greater. The Emergency Food Aid distributions and the TSFP, while having a relatively high cost per beneficiary compared to the other interventions analyzed, are still quite cost effective. CTCs, which are the only intervention available to treat severely malnourished children on a large-scale, are more expensive than other interventions, but have economic benefits that are higher than their costs by three to four times. The lowest benefit-cost ratio is for iron fortification of iodized salt at a relatively high cost of $0.45 per metric ton. Even here the benefits are still 100% higher than the costs.

5.59 A corollary to the above analysis is that several of the analyzed “potential” interventions, which are currently not being implemented in Ethiopia, should start to be implemented. These include, in particular, salt iodization, distribution of iodated oil capsules and deworming medicine to pregnant women, and iron and folate supplements to young children. Iodization of salt is the cheapest way to save under-5 lives and has a high benefit-cost ratio. Supplementing pregnant women with iodated oil capsules once a year is another high benefit-cost ratio, about 512. Deworming to pregnant women – provided once during pregnancy – would prevent 40% of infant deaths for about $0.05 per pregnant, rural woman, the lowest cost per beneficiary of any program. The E/EOS currently provides deworming medicine to under-5 children, but not to pregnant women.

5.60 The above programs have the important advantage that they would be able to reach a large fraction of the affected population. Salt is found in 99.9% of all Ethiopia homes. The existing structure of the E/EOS means it would be relatively simple to incorporate the iodated oil capsules and deworming medicine, which would be able to “piggy back” on the distribution already taking place.

5.61 Distributing iron and folate to young children would greatly increase their cognitive abilities, increasing societal benefits by 23 times more than the costs. Here though, initial coverage may be limited, since the tablets need to be taken once every few days, rather than just once or twice a year as in the case of iodated oil capsules and deworming to pregnant women. This would make distribution through the bi-annual E/EOS mass mobilizations problematic since compliance would be hard to ensure, and

improper compliance may be dangerous. Distribution would thus likely have to be done via regular visits by women or caregivers to health posts or heath centers who may be absent or located far from their homes. These capacity constraints on coverage would gradually be overcome as knowledge and the reach of health services are extended.

5.62 Although salt iodization and providing iodated oil capsules to pregnant women are both highly cost-effective, the former is more sustainable in the longer run and is much the preferred option. A policy of universal salt iodization would necessitate that the private sector produces and sells only salt that is adequately iodized, with the costs of iodization – which are low – being passed onto the consumer in the longer run. This is much more sustainable than providing iodated oil capsules to pregnant women, which would require sustained funding from the public sector or from donors. In the absence of salt iodization, iodated oil capsules should be provided to pregnant women as well as to under-2 children once every year through the E/EOS.

5.63 The community volunteer program suggested here shows the great potential to reduce malnutrition through community-based nutrition training. When implemented country-wide, as in Bangladesh and Thailand, such programs have been responsible for dramatic reductions in percentage of the population that is underweight and stunted, increasing by corollary, the other outcomes connected to these indicators, such as economic productivity and cognitive ability. Therefore, the 150 woredas we used as our starting point, should been seen as the first stage of a larger, country-wide program.

6 ETHIOPIA’S WAY FORWARD

6.1 FACTORS AFFECTING PROGRAM DESIGN AND HARMONIZATION

6.1.1 Linkages Between Different Programs

6.1 As has been mentioned a number of times already in this report, nutrition is affected by many factors other than food, with indicators such as wasting and especially stunting being high even in many food-secure areas of the country. Nutrition is also affected by interventions in the health, water, and education sectors, among others. One of the distinguishing features of nutrition is that it is multi-sectoral. For this reason a programmatic or sector-wide approach (SWAP) might be the most useful means of addressing malnutrition in Ethiopia. By providing a greater opportunity for agencies to harmonize their programs, a SWAP can provide an to opportunity to maximize the efficiency of program inputs.

6.2 To properly address nutrition in Ethiopia, it is vital to stress linkages among different sectors, sub-sectors, and programs and to adopt a harmonized approach. For Ethiopia and Nutrition Security (NS), this means collaboration and communication between the government agencies responsible for health, agriculture, water and sanitation, education, food security, and emergency response, as well as the multilateral and bilateral agencies, NGOs, and other actors working on these areas.

6.3 There is an urgent need to undertake efforts to strengthen the abovementioned linkages, which currently are not adequately strong. At present, different programs affecting nutrition tend to typically operate independently of each other. Chapter 2 has listed several different major programs affecting nutrition. Each of these programs currently operates more or less independently of each other. The harmonization of efforts through the use of a SWAP is one highly desirable way to achieve linkages.

6.4 Woredas of focus are typically chosen by each program independently of the others. When two or more programs overlap in the same woredas, there is usually no harmonized mechanism in place to select beneficiary households. At present, within a woreda served by two or more of these programs, one does not know which household is a beneficiary of which program. Setting up a harmonized procedure for choosing beneficiary households, including a common beneficiary database or a similar tool, would help very much in targeting resources as effectively a possible. This linking of existing databases or lists of beneficiaries would help determine where resources are being wasted with duplicate efforts, and would ensure that programs are targeting the households where the resources can have the most impact. Section 6.1.1 explores in more detail targeting of these different programs in Ethiopia.

6.5 In addition, there are other ways of increasing harmonization among different programs, especially those coexisting in the same woredas or kebeles. Many of the programs affecting nutrition have the same goals and could accomplish more if they were linked. For example, many of these programs use community volunteers, e.g. Pathfinder, Community-Based Therapeutic Care (CTC) projects, ESHE, and many others. 68 The training topics and time periods vary greatly among organizations, as was illustrated in Chapter 5, but the objectives are generally similar. These cadres of volunteers serve in their communities, but there are often two parallel systems of volunteers in the case of programs operating in the same woredas or kebeles. If the programs were coordinated, the same volunteers could have more intense, but harmonized, training and/or incentives, and accomplish the same tasks. Their level of understanding and ability to serve would increase as the inputs are shared among programs and channeled into fewer people to create fewer volunteers, but with greater expertise.

6.6 Implementation of two or more programs affecting nutrition in the same woreda or kebeles can be complementary. But if done in a manner that is not harmonized, the result may well be perverse, leading to a situation of diminishing returns: adding more programs stretches existing local capacity and reduces, rather than increases, the impact of each program. This is especially true in the case of the Health Extension Workers (HEWs) who are asked to play a coordinating role on the ground. In the case of the program involving community volunteers (CVs), such as ESHE and Pathfinder, the HEWs are often tasked with supervising the CVs. Yet HEWs are already overworked with their own “packages” that they have to implement, as discussed further below. Involving them further in two or more different CV programs, each with different mechanisms of operation and different types of training and roles of the CVs, is not desirable. Indeed, the risk is that this is overburdening them, and there may well be a situation where introducing new programs in the same woredas results in a reduced rather than increased impact of each program. Similar comments apply to woreda and kebele officials; introducing more programs

68 See Chapter 2.

would generally mean an additional burden for officials who already may be overburdened, resulting in diminishing returns.

6.7 Linkages between programs and the coexisting of different programs should also be taken into account much more when conducting monitoring and evaluation. Currently, those administering programs often conduct monitoring and evaluation in a manner without taking into consideration the impact of other coexisting programs. Strategies for monitoring and evaluation should explicitly take into account the coexistence in many cases of two or more programs affecting nutrition.

Box 6.6 Program Coordination and Linkages in SNNPRFrequently when one is researching health and nutrition indicators and programs, SNNPR comes to the forefront. In many documents and by many of the stakeholders in NS, SNNPR is lauded for it’s successes in programming, targeting, and coordination. This is shown in the EOS results, as their coverage numbers have improved with each round (see section on EOS later in this chapter). Often, with implementation, SNNPR takes the time to critique and then adapt methods specifically for its population. For example, they use the HEP standards for their HEWs, but added a requirement of 75% of their time spend in the field. Various key stakeholders were asked about SNNPR, and how they accomplish such a high level of collaboration. Some of the reasons put forth are listed below. SNNPR is one of the regions with a fully functioning regional ENCU office. This office meets every month with the regional minister of health, and the child survival team. This meeting is attended by all NGOs and UN organizations acting in the region. Hot spots are discussed, recent assessments and surveys are put forth, and programming is coordinated between the woredas. People commented that all of the government offices in Awassa, seem to be very organized. If information is needed, they generally can obtain it quickly and are aware of what is going on in their sector. Furthermore, all surveys and emergency interventions are overseen by the regional ENCU office; often a member of the office is present during assessments. Most programs are in SNNPR and Oromiya, thus most of the comparisons are with Oromiya. Perhaps, closer comparison to Tigray or Afar would show just as high a level of collaboration in those regions. The regional capitol of Awassa, is well placed for access and communication for NGOs, UN offices, and donors. Administrative boundaries in SNNPR are drawn along ethnic boundaries, which have decreased in-fighting and improved working relationships in government offices. During the green famine in the nineties, substantial amount of resources were poured into SNNPR for capacity building at all levels. During the 1960’s and 1970’s, there was a massive missionary campaign in parts of SNNPR. This has lead to high levels of education in rural areas where schools were built and are still maintained in many areas.

It would serve Ethiopia well to further investigate methods used in SNNPR to ascertain which truly helped in the development of the system, how the system is run, and lessons that can be learned to extend across the country. Many aspects are possibly not transferable, but those that are should be investigated and possible implementation in other areas researched.

6.8 Linkages between different programs need to be strengthened on the side of donors as well as of the government. On the government side, agencies in the Health and Agriculture Ministries are both key in order to have a strong impact on reducing malnutrition. Yet they have no clearly defined roles at present, and the structure is not amenable to these different agencies working together in a harmonized fashion. Just as

donor agencies administering different programs tend to operate independently of each other, different government agencies working to address nutrition tend not to work in a harmonized fashion.

6.9 Some of the issues here have been helped by the creation of the Emergency Nutrition Coordination Unit (ENCU) at the Federal level. A regional ENCU has also been created and is fully functional and with a full complement of staff in several regions; there is some evidence that this has played a role in increasing harmonization of the various nutrition-related programs, at least in SNNPR (see Box 6.1). The ENCU is jointly run by the government’s Disaster Prevention and Preparedness Agency and UNICEF, and has the mandate to monitor the nutrition surveys and emergency interventions in Ethiopia.

6.10 While the ENCU plays a key role and plays it very well, it operates with limited resources and a somewhat mandate and thus is able at present to play only a limited role in increasing coordination between different nutrition-related programs. Its focus is generally only on the woredas where emergency situations are occurring or have occurred. It is able ultimately to play a role only for a limited number of woredas and only for collaboration between the DPPB/D, RHB, and the implementing NGO. Unfortunately, the ministries for education and water and sanitation are generally not involved in ENCU work.

6.11 Given these difficulties, it is clear that there is a urgent need for a process and mechanism to substantially improve linkages among different programs and agencies. Among other things, a high-level cross-sectoral coordination body or council that ensures that different agencies work together in addressing malnutrition is a top priority. This type of body is called for as part of the National Nutrition Strategy, and should have been established by 2004/05 according to the PASDEP, the government’s overall strategy document. In practice, this body has not yet been established. Currently in order to have a large enough clout to be able to truly increase the extent of harmonization between different agencies, this body should ideally be housed at a high level, such as within the Prime Minister’s Office. The creation of a national coordination body needs to be put against the negative experience of setting up national councils in the 1970s. Thses bodies need to be directly linked to implementation and financing mechanisms. Otherwise, they will have no influence whatsoever and are doomed to collapse.

6.12 It is important that the linkages be formed and strengthened not just with the sectors typically linked with nutrition such as the health and agriculture sectors, but also other sectors such as the water and sanitation and education. Recognition of the importance of water and sanitation to malnutrition is coming to fore in the government, but not as much as with donor and NGO projects. Other sectors that affect nutrition include the infrastructure sectors, as well as micro lending institutions. All these sectors play a role in affecting nutritional insecurity, but there is little to no communication and collaboration between the different actors on areas related to nutrition. The national coordination council for nutrition proposed above would greatly help to strengthen linkages with these others sectors as well. Also, there is scope for public-private partnerships with NGOs implementing, for example, community health strategies. This is successfully done in quite a few developing countries.

6.13 Lastly, the power of public-private partnerships needs to be developed and explored in the face of the current nutritional insecurity crisis. Many nutrition interventions can occur

with the help of the private sector and with those working in industry, in particular interventions to fortify foods with micronutrients such as iodine and vitamin A. The private sector could be fruitfully involved, for example, in fortification of flour or of salt with iodine, as well as the fortification of sugar with vitamin A.

6.1.2 Nutritional Surveillance

6.14 In Ethiopia, it is not currently possible to obtain localized information on nutritional indicators at the kebele or even the woreda levels, except on a sporadic basis. Virtually the only woreda-level data that are available come from localized nutrition surveys conducted in woredas in emergency situations, as part of the system overseen by the Emergency Nutrition Coordination Unit (ENCU), described below. Surveys with broad geographical coverage such as the Welfare Monitoring Surveys (WMS) and the Demographic Health surveys (DHS) are conducted, but only once every three to five years, and these are only representative at the zonal level (for the WMS) or the regional level (for the DHS). This means that these surveys cannot be used to provide accurate values for nutritional indicators for individual woredas. Furthermore, they do not cover all areas of the country; for example, the DHS does not cover nomadic areas.

6.15 Ethiopia currently does have the Early Warning System (EWS) of the DPPA, but this is focused more on collecting indicators on food insecurity than on nutritional insecurity. A constant theme of this report has been that these two are not the same things, and addressing food insecurity is not the same as addressing nutritional insecurity. The EWS system collects information on market conditions (e.g. price of teff or wheat), disasters (e.g. floods, wild fires), weather (e.g. rainfall), agriculture (e.g. activity level compared to seasonal averages), and pastoral areas (e.g. livestock and pasture condition). However, it does not track measures of nutritional indicators such as stunting and wasting or goiter rates. Furthermore, the EWS data collection efforts are relatively weak in pastoral areas, non-famine prone areas, areas of non-sedentary populations, and in areas where people have been historically marginalized. The EWS also excludes urban areas.

6.16 The ENCU directs NGOs to conduct rapid assessment and nutrition surveys in woredas where an emergency situation appears to be developing, as determined by the EWS. It collects and records the data from these surveys, but these are the only nutrition data that it collects. These data are limited to the woredas where a potential emergency situation is occurring from a food security viewpoint, and does not focus on other woredas where there could be chronic food security, or where there could be nutritional insecurity with poor nutritional indicators even without food insecurity. The ENCU also cannot be used for the purposes of monitoring and evaluation, since it does not collect data from an unbiased sample of woredas. In addition, it cannot be used for the purposes of program targeting or of the selection of woredas for individual programs because of its limited coverage of woredas.

6.17 Because of this, reviews of Ethiopia’s nutrition strategy, programs, and situation consistently end in recommendations to establish a proper and comprehensive nutrition surveillance system. This is a key recommendation of the National Nutrition Strategy. Such a system would be able to track localized nutritional indicators at a large number of focal points, so that the nutritional status of households in different localities could be tracked over time at the woreda and even the kebele levels. Monitoring of child growth would be a component of the surveillance system, but the nutritional indicators tracked

would extend for beyond this measure to include, among others, micronutrient intake and local sanitation conditions. A nutrition surveillance system can identify constraints in particular areas, help determine if project objectives are being met, provide information to improve targeting, assess quantity, quality, and timeliness of project inputs, and inform decision making at each level of government. For Ethiopia to move closer to a nutritionally secure society, a nationwide surveillance system must be put in place.

6.18 There are many methods available for a nutrition surveillance system. In the National Nutrition Strategy and a document by Oliphant (2005), suggestions were put forth for best practices for Ethiopia. These include: (i) the need for political and social support, efficient management, clearly defined indicators, and communication of results in a timely fashion to decision makers at each level of decision making and (ii) information should be made available at the woreda and zonal levels. One method to achieve these results would be the adoption of new technology. Through the use of pilot programs incorporating cellphones and woredanet, HEWs can report data and provide rapid referral services. With such programs, Ethiopia will be able to leapfrog into the modern era.

6.19 The following are objectives that should be met by a successful nutrition surveillance system:

Prevention of malnutrition epidemics during times of crisis as well as regular seasonal fluctuations.

Easy, measurable, relevant, and minimal information are at the core of surveillance. To collect, process, and communicate the information should take minimal time with maximum output. This output being getting the information to the stakeholders who need it, in minimal amount of time so action will not be delayed.

Not be completely new system, rather use data and sources already available at the local level building up as necessary.

Have set trigger points where actions are automatically set in motion if a given threshold is surpassed.

The process needs to be owned by local level stakeholders, specifically at the kebele and woreda levels. This includes leaders as well as local health volunteers.

6.20 To achieve the best possible practices in addressing nutritional insecurity, the nutritional surveillance system needs to develop Ethiopia-specific indicators to best predict problems before they happen. Current practices use global and severe malnutrition rates as the key thresholds to trigger action. Yet once these have risen, a crisis generally has already ensued. More specific indicators for various regions or livelihood zones, other than just malnutrition rates, would provide valuable insight. It is fundamental that all population groups are included in the monitoring indicators. It is recommended that sentinel sites be established to help monitor the more difficult populations. Sentinel data is not universally representative, but if done correctly can illustrate the situation in a given area. As the system develops, sentinel sites could be increased in number or even removed as widespread monitoring becomes feasible.

6.1.3 Targeting of Food Aid

6.21 This section attempts to draw some conclusions regarding the impact and targeting of food aid, given the available information. But a number of caveats are in order. First, a recurrent theme of this report is that malnutrition in Ethiopia is caused by a

range of factors, with food insecurity being just one of them; emergency food aid is vital but it is can only address the component of malnutrition that results from food insecurity. Furthermore, the analysis here is only partial; a more in-depth analysis is warranted to draw firmer conclusions on this important topic.

6.22 Emergency Food Aid works well overall. It has made a large difference over the years, and has certainly saved many lives in a country with widespread food insecurity. But there are several flaws in the food aid targeting process. Emergency food aid needs are determined by the Early Warning System (EWS) meher assessment, but specific allocations of food aid resources are determined and made only after more specific area-by-area and case-by-case assessments are performed to determine acute needs. This process has a number of drawbacks, including the relatively poor coverage by the EWS of pastoral areas, non-famine prone areas, areas of non-sedentary populations, areas where people have been historically marginalized and urban areas. Analogous to other countries, there have been allegations of some preferential treatment of some areas or woredas over others when determining who should get emergency food aid, and political factors have sometimes allegedly affected food aid targeting decisions.

6.23 Another drawback is that woredas that have been identified as “Food Insecure” in the past – even through a process that may have had its flaws – tend to continue to be counted as a “Food Insecure” woredas, compounding errors if any of the past. The long-standing practice in Ethiopia for programs providing food, such as in particular Emergency Food Aid, is to provide aid mostly only to the so-called “Food Insecure” woredas. The inflexibility of food aid targeting was noted in chapter 3; the so-called “Food Insecure” woredas appear to consistently receive food aid. Conversely, the so-called “Food Secure” woredas seem to receive much less frequently, or sometimes never at all.

6.24 A more flexible approach to food aid targeting, to address particular patterns of shocks that take place in any particular year, would be preferable to the present approach. Furthermore, the present approach appears to insufficiently take into account the large proportions of food insecure people that are in the so-called “Food Secure” woredas. This can be seen from Table 6.31 as well as Figure 6.29 and Figure6.30, which presents figures calculated using data from the 2004 household Welfare Monitoring Survey (WMS). Specifically, as discussed in chapter 3, the data are are based on responses to questions asking each household: (i) whether or not the household had experienced food shortage in the previous 12 months; and (ii) if the answer given was yes, how many months of food shortage had been experienced. Despite the subjectivity associated to some extent with such self-reported data, these data – in the absence of better alternatives – can be taken as rough indicators of households’ food security status.

6.25 For the analysis in this section, woredas were categorized into either “Food Insecure”, “Partially Food Secure” or “Fully Food Secure”, based on the frequency with which they received food aid over the years 2000 to 2004, before the introduction of the Productive Safety Nets Program. Woredas that were deemed to need food aid in all five years of the period 2000-2004 were labeled as “Food Insecure”. Woredas that were not deemed to need food aid in any of the five years were labeled “Fully Food Secure”, while the other woredas were called “Partially Food Secure”. Note that not all woredas that have been deemed to need food aid in any one year have actually obtained food aid.

Table 6.31: Extent of Self-Reported Food Insecurity in 2004, for Woredas Categorized by Degree of Food Insecurity

No. of Woredas

Number of Households in Sample

Percentage of Households Reporting Food Shortage Within Previous 12 Months2

Average Number of Months of Food Shortage Within Previous 12 Months2

“Fully Food Secure” Woredas1 182 2818 24.7% 0.85“Partially Food Secure” Woredas1 161 4209 32.0% 1.24“Food Insecure” Woredas1 213 4150 35.8% 1.30

Notes:1. Woredas here are defined according to 2004 boundaries. 2. Based on self-reported data from the 2004 WMS. The figures for the average number of months of food shortage incorporate the households that reported no food shortage; these households were taken to have zero months of food shortage within the previous 12 months. Source: Calculations using data from the WMS 2004 and food aid data from DPPA.

Figure 6.29: Percentage of Households Reporting Food Shortage Within Previous 12 Months

0%

5%

10%

15%20%

25%

30%

35%

40%

“Fully FoodSecure” Woredas

“Partially FoodSecure” Woredas

“Food Insecure”Woredas

Notes: See notes for Table 6.1.Source: Calculations using data from the WMS 2004 and food aid data from DPPA.

Figure 6.30: Average Number of Months of Food Shortage As Reported by Households within Previous 12 Months

Notes: See notes for Table 6.1.Source: Calculations using data from the WMS 2004 and food aid data from DPPA.

6.26 The data highlighted imply that there is less difference in the extent of food insecurity between the so-called “Food Secure” and “Food Insecure” woredas than may be expected. This can be attributed in part to the positive impact of emergency food aid which was distributed exclusively in the “Food Insecure” woredas as defined for the present analysis. However, the data suggest that there are large number of food insecure people in the so-called “Food Secure” woredas that are not being reached. Figure 6.29 shows that about 25% of households in the “Fully Food Secure” woredas – those that were deemed not to need any food aid over the period 2000 to 2004 – reported food shortages within the previous 12 months in the 2004 WMS survey. This is lower than the corresponding percentage for the “Food Insecure” woredas – those that were deemed to need food aid in all five years 2000 to 2004 – which is about 36%. However, the difference between the two is rather less than may be expected. A similar picture is depicted in Figure6.30 which shows the average number of months of self-reported food shortage within the previous 12 months, for the different categories of woredas.

6.27 A surprising finding emerges from an analysis of the 2004 WMS data for the different categories of woredas: There appears to have been little difference in stunting and wasting rates between the “Food Insecure”, “Partially Food Insecure” and “Fully Food Secure” woredas (Table 6.32 and Figure 6.31). The classification of woredas is the same as that used throughout this section, and is based on the frequency with which the various woredas received food aid over the five-year period 2000 to 2004 (see above). The results show tthat the “Food Insecure” woredas indeed had higher stunting rates in 2004 than the other woredas, but the difference is not very large. In addition, the “Food Insecure” woredas did not appear to have higher wasting rates in 2004 than the other woredas. Indeed, the “Food Insecure” woredas had significantly lower wasting rates than the “Fully Food Secure” woredas.

0

0.2

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0.6

0.8

1

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“Fully FoodSecure” Woredas

“Partially FoodSecure” Woredas

“Food Insecure”Woredas

6.28 This finding should be interpreted alongside: (i) the findings regarding self-reported household food insecurity in the different categories of woredas (Table 6.31 and Figure 6.29 as well as Figure 6.30), and: (ii) the analysis in Chapter 3 on the links between child malnutrition and the extent of self-reported household food insecurity (see Table 3.2 and 3.3, and Figure 3.5). Recall that the latter analysis found that there was a partial correlation between child wasting rates and the extent of household food insecurity in 2004, but a very large component of wasting could not be explained by food shortage alone. No clear relationship was found between child stunting rates and the extent of household food insecurity.

6.29 Taken together, these three sets of findings imply that the picture portrayed in Table 6.32 and Figure 6.31 can be explained partly by the fact there is a large degree of food insecurity even in the so-called “Food Secure” woredas, to an extent that is not hugely lower than in the so-called “Food Insecure” woredas. This can be attributed, in turn, partly to the equalizing effect of emergency food aid which was distributed in the “Food Insecure” woredas only, despite the large proportions of food insecure households in the “Food Secure” woredas.

6.30 Another explanation for the picture portrayed in Table 6.32 and Figure 6.31, taking into account all the findings so far, is that a very large component of both wasting and stunting is attributable to factors other than household food shortages. These include factors related to poor health status, inadequate safe water and sanitation, and inappropriate child care and child feeding practices. These factors may, in fact, be more prevalent in the “Food Secure” woredas than in the “Food Insecure” ones, reversing the impact on wasting rates of the lower extent of food insecurity on average in the “Food Secure” woredas as demonstrated by Figure 6.29 and Figure 6.30.

Table 6.32: Malnutrition Rates in 2004, for Woredas Categorized by Degree of Food Insecurity

Stunting rate in 2004

Wasting rate in 2004

No. of Woredas Global Severe Global Severe

“Fully Food Secure” Woredas 213 47.2% 24.5% 10.0% 2.0%“Partially Food Secure” Woredas 161 46.8% 24.3% 7.5% 1.4%“Food Insecure” Woredas 182 48.6% 24.0% 9.0% 1.8%

Note: Woredas here are defined according to 2004 boundaries.Source: Calculations using data from the WMS 2004 and food aid data from DPPA.

Figure 6.31: Malnutrition Rates in 2004, for Woredas Categorized by Degree of Food Insecurity

0%

10%

20%

30%

40%

50%

60%

GlobalStunting

SevereStunting

GlobalWasting

SevereWasting

“Fully Food Secure”Woredas

“Partially Food Secure”Woredas

“Food Insecure” Woredas

Source: Calculations using data from the WMS 2004 and food aid data from DPPA.

6.1.4 Overall Targeting of Programs Affecting Nutrition

6.31 It has long been the practice to target interventions to certain groups such as pregnant and lactating women (PLWs), children under-5, and the elderly, as these groups are assumed to be the most nutritionally vulnerable. However, this assumption is not always correct and programs would do well to research the cultural practices of an area before specifying the target group. Not all PLWs may be at risk, and there may be other programs which are focusing on under five children with few programs at the same time benefiting adolescents. For nutrition security to be substantially improved in Ethiopia, the targeting of programs to the correct households and also to members within those households needs to be further developed. It is important to distinguish here between the food secure and nutritionally secure when targeting. Food Security is generally addressed in the context of households, communities, regions, as well as at the national level. Nutrition Security requires one to focus on priority target groups: individuals in household or specific households in a community.

6.32 Because of the lack of a proper nutritional surveillance system, there is very limited woreda-level data on nutritional indicators. This makes it very difficult or even impossible for programs addressing nutrition to target the most nutritionally insecure woredas. The lack of a proper nutritional surveillance system is described above.

6.33 Another obstacle to efficient targeting is the widespread myth that nutrition security is the same as food security. With this principle entrenched in minds, and with the dearth of available locally representative data on nutritional insecurity, targeting of programs designed to combat malnutrition is often done using measures of food insecurity or other measures of vulnerability such as the “Chronic Vulnerability Index”69. Yet these are not necessarily highly correlated with nutritional insecurity, Indeed, 69 The Chronic Vulnerability Index CVI) started in 1999. The CVI results from a multi-agency project tasked with the development of a Woreda level baseline of areas needing assistance. Due to a lack of data, however,

the correlation between food and nutritional insecurity is only partial, and there are many factors other than food provision that have a strong and large impact on malnutritional indicators, especially stunting, as has been shown in Chapter 3.

6.34 To make matters worse, targeting food insecurity itself is difficult, even if one explicitly aims to ignore the other factors that contribute to malnutrition. The approach taken by many programs aiming to combat malnutrition is to focus largely on the woredas that have been regularly receiving emergency food aid, which are in turn classified as “Food Insecure” woredas. In other words, problems in the food aid targeting process – see the previous section for a full discussion of this – translate to problems in the targeting of other programs as well. The so-called “Food Secure” woredas, which in fact have large proportions of food insecure households (see above), receive little if any emergency food aid. They also receive little assistance from many of the other programs that aim to combat malnutrition.

6.35 This can be seen from Table 6.3, which was constructed from listings of woredas that were covered in 2006 under each of several major70 programs that affect nutrition. Woredas have been categorized here in the same manner as in Chapter 3 (Section 3.3) and in Section 6.1-3 of this chapter – according to the frequency with which the woredas have been receiving food aid over the five-year period 2000-2004. Woredas that received food in all five years were classified as “Food Insecure”; those that received no food aid were classified as “Fully Food Secure”. The rest of the woredas were categorized as “Partially Food Secure”. Aside from Pathfinder and WASH, whose objectives do not explicitly state addressing nutritional insecurity, the percentage of “Food Insecure” woredas included in these programs is high – often very high – compared to the percentage of “Partially Food Secure” woredas, and especially compared to the percentage of “Fully Food Secure” woredas.

6.36 In analyzing these data, it is important to distinguish between programs that aim to combat malnutrition solely or largely by providing food, and those that do not. In Table 6.3, as well as other tables afterwards that provide statistics by program, an asterisk is used to denote the programs in the first category, i.e. which provide food. Aside from Pathfinder and WASH, improving nutritional indicators through pathways other than food provision are key goals of all the other programs.

Table 6.33: Percentage of All “Fully Food Secure”, “Partially Food Secure” and “Food Insecure” Woredas Included in Each Major Program Affecting Nutrition

Full EOS

TSFP*

PSNP*

MERET*

School Feeding* ESHE CGP

Path-finder

WASH Water and Sanitation Program

“Fully Food Secure” Woredas 88.6% 78.4% 94.6% 28.6% 37.8% 18.9% 13.5% 31.4% 48.6%

some regions were not represented in developing the CVI, including Afar and Somali. Nine variables were ultimately chosen and used to develop a list of the most vulnerable Woredas. The list was given to the Regional offices, who had a say in the final decision as to which Woredas should be on the list. This list was used in the implementation of MERET and the school feeding program.70 ‘Major’ programs were defined by number of beneficiaries, budget, and objectives. These 9 programs were chosen, as they all affect NS and all have large coverage.

“Partialy Food Secure” Woredas 68.7% 48.8% 46.9% 6.2% 21.8% 9.0% 3.3% 34.6% 50.2%“Food Insecure” Woredas 8.1% 4.1% 0% 2.0% 2.7% 5.4% 0% 35.1% 49.3%

Note: Programs marked with an asterisk aim to impact malnutrition only or largely through food provision.

6.37 Further problems arise from the fact that programs are often targeted to the larger regions and then areas with denser populations to reduce unit costs of coverage. Some of the smaller and more sparsely populated regions, such as Benshangul-Gumuz and Somali regions, have fewer programs, even though some of them have high malnutrition indicators especially wasting rates. Due to the nature of the current surveillance system, there is less information available on these areas, for example the nomadic peoples of Somali region. This relative lack of information is one reason for the reduced focus on these smaller regions; the lower population density and greater difficulties in delivering interventions is another reason. Yet, as illustrated by Figure 3.14 and Figure 3.15 of Chapter 3, some of the smaller regions have high malnutrition indicators; for example, Afar and Somali have the highest wasting rates among all the regions.

Table 6.34: Display of Which Programs are Active in Each Region.

EOS TSFP* PSNP* MERET*School Feeding* ESHE CGP Pathfinder

WASH Water and Sanitation Program

Tigray X X X X X X X XAfar X X X X XAmhara X X X X X X X X XOromiya X X X X X X X X XSomali X X X X X XBenshangul-Gumuz X XSNNPR X X X X X X X X XGambella X X XHarari X X X XDiredawa X X X X X

Note: Programs marked with an asterisk aim to impact malnutrition only or largely through food provision..

6.38 Within the targeted regions, programs tend to focus on a subset of woredas, labeled as “Food-Insecure” due to food aid targeting procedures of the past. These woredas tend to be the beneficiaries of several major programs, generally not coordinated with each other and sometimes overburdening Health Extension Workers as noted above (Section 6.1-1). At the same time, the less favored woredas are targeted by disproportionately fewer programs; many of them have no programs at all (Table6.35 through Table 6.37). These tables show the malnutrition rates in 2004 – from the 2004 WMS – for subsets of households grouped according to the number of major programs in 2006 in their woreda of residence.

6.39 A “major program” here is defined as any program listed in Table 6.34, except for WASH (Water, Sanitation and Hygiene program) and emergency food aid. Table 6.35

classifies woredas by number of major program providing food, excluding emergency food aid (TSFP, PSNP, MERET and School feeding/CHILD) and WASH. Table 6.37 classifies woredas by number of major program with a strong community volunteer focus (CGP, ESHE, and Pathfinder).

Table 6.35: Moderate and Severe Stunting and Wasting Rates in 2004 of Woredas, grouped by Number of Major Programs Active in those Woredas

Stunting Rate in 2004

Wasting Rate in 2004

No. of Woredas Global Severe Global Severe

Four or More Major Programs 91 52.5% 27.3% 9.5% 2.1%Three Major Programs 91 45.5% 23.7% 6.5% 1.1%Two Major Programs 90 42.7% 19.8% 7.2% 2.0%One Major Program 149 50.2% 26.2% 7.8% 1.7%No Major Program 135 42.9% 19.5% 9.8% 1.6%

Notes: Woredas here are defined according to 2004 boundaries. Stunting and wasting rates were calculated using data from the 2004 WMS. These figures are excluding WASH and emergency food aid.

Figure 6.32: Stunting Rates in 2004, by Number of Major Programs Affecting Nutrition

0%

10%

20%

30%

40%

50%

60%

Global Stunting Severe Stunting

Four or More MajorProgramsThree Major Programs

Two Major Programs

One Major Program

No Major Program

Source: Calculations using data from the 2004 WMS.

Figure 6.33: Wasting Rates in 2004, by Number of Major Programs Affecting Nutrition

0%

2%

4%

6%

8%

10%

12%

Global Wasting Severe Wasting

Four or More MajorProgramsThree Major Programs

Two Major Programs

One Major Program

No Major Program

Source: Calculations using data from the 2004 WMS.

6.40 Table 6.35 and Table 6.36 show us that the woredas with a high concentration of programs in 2006 had higher stunting rates in 2004 than the woredas with low concentration of programs, but the difference is not very large. The wasting rates in 2004 of the woredas with a high concentration of programs is not higher than the woredas with a low concentration of programs. Table 6.36 shows us that when one looks only at the major programs providing food, there is little relationship between program concentration and malnutrition rates, especially not for stunting. Table 6.37 shows however, that the major programs with a strong community volunteer focus do seem to be generally more targeted to the woredas with higher stunting rates.

Table 6.36: Moderate and Severe Stunting and Wasting Rates in 2004 of Woredas, grouped by Number of Major Food-Providing Programs Active in those Woredas

Stunting rate in 2004 Wasting rate in 2004

No. of Woredas Global Severe Global Severe

Three Or More Major Programs 115 49.6% 23.6% 9.9% 2.2%Two Major Programs 142 46.6% 24.9% 6.6% 1.4%One Major Program 72 45.9% 23.8% 7.2% 1.9%No Major Program 227 46.9% 23.1% 8.8% 1.6%

Note: Woredas here are defined according to 2004 boundaries. Stunting and wasting rates were calculated using data from the 2004 WMS.

6.41 This pattern is justifiable to the extent that there are complementarities in these overlapping programs. Strong complementarities would justify the coexistence of two more programs affecting nutrition in the same woreda, although the need to strengthen linkages between these programs then becomes even more paramount. Section 6.1-1 discussed this topic and the urgent need to strengthen linkages.

6.42 Conversely, to the extent that there is duplication of programs with limited complementarities in the same woredas with overstretching of existing local capacity, this pattern suggests that there would be gains from programs “branching out” and focusing more on the less-favored woredas. Regardless, all the evidence points to the need

for the various programs to jointly select target woredas, and then to work jointly in the woredas where there is overlap of programs.

Table 6.37: Moderate and Severe Stunting and Wasting Rates in 2004 of Woredas, grouped by Number of Major Programs with strong community focus

Stunting rate in 2004

Wasting rate in 2004

No. of Woredas Global Severe Global Severe

Two Or More Major Programs 44 49.6% 27.2% 8.2% 1.4%One Major Program 186 51.7% 27.6% 7.9% 1.7%No Major Program 326 42.9% 19.2% 8.9% 1.8%Note: Woredas here are defined according to 2004 boundaries. Stunting and wasting rates were calculated using data from the 2004 WMS.

6.43 This scenario is depicted pictorially in Maps 3.2 to 3.4, as well as Maps 6.1 to 6.3, all in Appendix 4. Maps 6.1 and 6.2 show that there is a high degree of overlap between the woredas where the major food-providing programs occur and the woredas which regularly receive food aid. These maps shows that the major food-providing programs are concentrated especially in a vertical belt starting roughly a bit south of the middle of the country, running upwards and then finishing in the north of the country where the programs are especially heavily concentrated.

6.44 Maps 6.1 to 6.3 also show that there is not, however, much correlation between the location of the nutrition-related programs with a strong CV focus on the other hand, and the location of the food-providing programs on the other hand. Neither is there much of a correlation between the location of these CV-focused programs and the location of the woredas receiving emergency food aid. This is in line with what is depicted in Table 6.33.

6.45 Maps 3.2, 3.4, and 3.6 in the appendix depict the wasting, stunting, and underweight prevalence in 2004, based on WMS data. These maps must read with caution, because – unlike Maps 6.1 to 6.3 – there are many woredas for which there is no data.

6.46 Taken together with the Maps 6.1 to 6.3, these maps indicate that there are large parts of the country – the west of the country for example, generally considered food-secure – that have high malnutrition rates but a low concentration of programs affecting nutrition. The overall picture is one where targeting of programs could be clearly improved. One positive finding is, however, that the programs with a strong CV focus appear better targeted than the food-providing programs from a nutritional standpoint, especially if stunting is the indicator of focus. This is consistent with the figures in Table6.37.

6.47 Table 6.38 examines the degree of targeting of the major programs affecting nutrition, from a nutritional standpoint. A comparison of nutritional indicators based on the WMS 2004 for two groups of woredas are provided for each program: those included the program and those not included in 2006.

6.48 In general, these programs do not appear to be very well targeted towards the most nutritionally vulnerable woredas. Generally, there is not much difference between the values of standard stunting and wasting indicators for woredas included in each program, versus those that are excluded, although there are some exceptions..

6.49 This overall picture of poor targeting in choice of beneficiary woredas is not surprising, and reflects the lack of a suitable means to use to do the targeting. As noted above, there is currently no proper nutritional surveillance system that provide the woreda-level data needed to do proper targeting. Those designing programs have no choice but focus on the so-called “Food-Insecure” woredas or to develop a proxy indicator of nutritional insecurity, that often is not necessarily highly correlated with the true degree of malnutrition.

6.50 The situation is compounded by the widespread nature of malnutrition in Ethiopia, making it difficult to select a subset of the most nutritionally vulnerable woredas. This widespread nature is depicted in Maps 3.2 and 3.4; while there is some variation in stunting and wasting rates across the country, these rates are generally high almost everywhere. Indeed, the maps point to the need for scaling up the programs affecting nutrition in the country.

6.51 In the meantime, even with the ostensibly poor woreda targeting of many programs in terms of stunting and wasting, it should be stressed that these programs are nevertheless operating in woredas with high rates of malnutrition, as can be seen from Table 6.38. They would thus be having a high impact in their focus woredas in any case, if they are working as intended.

6.52 A further observation, and a caveat to the above analysis, is that nutritional insecurity is made up of many components, of which malnutrition indicators such as stunting and wasting rates are just part. Proper targeting would take into account more then just the standard indicators of stunting and wasting. Malnutrition indicators are important factors to consider in targeting and program design, but there are many other aspects, e.g. the area’s vulnerability to shocks, local capacity, population density, geography, health care capacity, current programming, livelihoods, availabiliy of public health information, water and sanitation, women’s status community support for new mothers and long term needs for emergency food aid. The targeting for the programs mentioned in this document is slightly different for different programs. All used a combination of indicators to choose their woredas, and then, in some cases, households within those woredas in some cases. It is important to recognize that politics, donor predilections, and organizational aims of implementing partners also play a role in targeting, and this is unfortunately unavoidable.

6.53 Lastly, a key topic for targeting in Ethiopia is its bias for rural populations. This is reasonable, as 84% of the population lives in rural areas and as was shown in previous chapters, rates of malnutrition, childhood disease, and mortality are higher in the bucolic areas. However, it important that the urban poor not be left out as Ethiopia moves forward toward a Nutritionally Secure society. As was shown by Figure 1.9 in Chapter 1, wasting rates have continued to drop in rural areas since 1998, but between 2000 and 2004 there was no decrease in urban areas and a slight increase. The rates of wasting are substantially lower in urban areas versus rural; however they are still high as are the stunting rates in urban areas. Moreover, as discussed later in this chapter, the nutrition transition,

generally begins in urban areas and spreads to rural areas. Without proper monitoring and evaluation of urban areas and nutrition education, a new problem could arise unnoticed.

6.54 A final comment is that while the ostensibly poor woreda targeting within individual programs is difficult to correct in the short term without a proper nutritional surveillance system, a harmonized method for selecting woredas should nevertheless be urgently implemented, and more attention should be given to the woredas that are currently not much favored often on the grounds of being “Food-Secure”. As seen from Figures 6.1 to 6.5, many of the so-called “Food-Secure” woredas – the ones not regularly receiving food aid – in fact have poor nutritional indicators. There should be more focus on these woredas, and a more evenly spread pattern of intervening rather than concentrating on a subset of highly favored mostly “Food-Insecure” woredas.

Table 6.38:Stunting and Wasting rates from 2004 of Woredas that were targeted in 2006 by specific programs.

EOS TSFP* PSNP* MERET*School Feeding* ESHE CGP Pathfinder WASH

Global Stunting Rates (<-2) for Woredas In and Out of Major ProgramsRate of Those in Program 47.2% 46.6% 50.6% 42.8% 47.4% 48.7% 50.4% 47.3% 52.5%Rate of Those Out of Program 45.4% 48.3% 44.5% 47.4% 46.2% 46.6% 46.2% 46.6% 45.4%

Severe Stunting Rates (<-3) for Woredas In and Out of Major ProgramsRate of Those in Program 23.7% 22.5% 27.1% 18.3% 24.5% 23.6% 23.8% 24.0% 27.3%Rate of Those Out of Program 22.3% 27.4% 21.1% 24.1% 22.0% 23.5% 23.4% 22.9% 22.4%

Global Wasting Rates (<-2) for Woredas In and Out of Major ProgramsRate of Those in Program 8.2% 8.6% 8.0% 7.3% 8.9% 10.1% 9.0% 8.0% 9.5%Rate of Those Out of Program 8.8% 7.2% 8.5% 8.4% 7.3% 7.9% 8.1% 8.7% 8.0%

Severe Wasting Rates (<-3) for Woredas In and Out of Major ProgramsRate of Those in Program 1.7% 1.8% 1.7% 1.5% 1.8% 2.3% 1.8% 1.8% 2.1%Rate of Those Out of Program 1.5% 1.3% 1.7% 1.7% 1.5% 1.6% 1.6% 1.6% 1.6%

Note: Programs marked with an asterisk aim to impact malnutrition only or largely through food provision. Stunting and wasting rates were calculated using data from the 2004 WMS. Addis Ababa was excluded from the calculations.

6.2 HEALTH EXTENSION WORKERS

6.55 The Health Extension Program (HEP) is a landmark program for Ethiopia, addressing three of four components of Nutrition Security directly, and the fourth indirectly. As was discussed in Chapter 1, Nutrition Security is made up of secure access to food, sanitary environment, adequate health services, and knowledgeable care. The aim of the HEP is to improve practices related to proper hygiene; improve reproductive health & nutritional status; control common infections; and bring equity in health services. The core of the program is the Health Extension Workers (HEWs) who educate their communities on environmental health; provide basic health care and community mobilization

for health care programs; and provide education on various topics to improve caring practices in the community.

6.56 The food component of Nutrition Security is addressed indirectly through education, especially regarding nutrition and food hygiene. Often, it is the misconceptions of parents and community members that can lead to malnutrition, morbidity, and mortality. A study by Lloyd and others (2007) researched the child care practices responsible for malnutrition. Many of these behaviors have been touched on in previous chapters; they include poor composition, late introduction and inadequate amounts of complimentary foods. Use of traditional healers before approaching the HEP system as well as belief in the ‘evil eye’ can prove harmful and even fatal to children and PLW. The HEP system serves to directly change these dangerous behaviors.

6.57 The HEP is currently working in the form of a four-tier system, the lowest level being a primary health care unit composed of a health center with five satellite health posts. Health posts are meant to serve the community through HEWs. HEWs are imperative components to the HEP. HEWs serve to fill the gap of human resources in health. They are given extensive training, over 450 hours, in 16 health focus areas, as well as personal development. Table 6.39 lists the 16 packages HEW are to focus on once working in their communities.

6.58 As can be seen in the table above, the HEP has already reached substantial success with 9,612 HEWs trained and working and 5,000 health posts in 2006, all in two years. The figure for HEWs has since risen even more, and now stands at 17,643 in June 2007. This growth and expansion is almost unprecedented for a health care system, and has reached millions of Ethiopians. The 2009 goal of 30,000 HEWs seems considerable, but the program is on the right track to attain this commendable target. Without any other intervention, or change in programming, the HEP alone will have a great effect on NS in Ethiopia. The continued support, monitoring and evaluation of the Health Extension Program is key to forward momentum on the Millennium Development Goals and Ethiopia’s NS.

Table 6.39: HEP Program DetailsHealth Extension Workers of the Health Extension Programme

Key goals of the HEPs: preventative, promotive, and basic curative care. 

HEWs are a key component in the HEP; they serve to solve the lack of human resources for health in Ethiopia. 

    

Progress 2004 (inception) 2006 (review) 2009 (goal)  Health Posts 0 5,000 15,000  HEWs 0 9,612 30,000  HCs 412 N/A 3,153       Four key areas are focused on for HEWs:

 

Hygiene and Environmental

SanitationFamily Health

Services

Disease Prevention and

Control

Health Education and

CommunicationPercentage of training time devoted*: 22.10% 24.40% 14.70% 2.20%

16 Packages used as the focus

of HEW work

Building and Maintaining a Healthy Home

Adolescent Reproductive Health First Aid Health Education

Control of Insects, Rodents, and other biting species Family Planning

HIV/Aids and TB Prevention and Control  

Food Hygiene and Safety Measures

Maternal and Child Health Malaria Prevention  

Personal Hygiene Nutrition  

Construction, usage, and maintenance of a Sanitary Latrine

Vaccination Services

*The remainder of the training time is devoted to Common courses (23.7%), Other (8.6%),

and Community Documentation (4.3%)

Solid and Liquid waste managementWater Supply Safety Measures      

*The remainder of the training time is devoted to Common courses (23.7%), Other (8.6%), and Community Documentation (4.3%).

6.59 As can be imagined, with such a large program and rapid implementation, growing pains will be felt. With just 2 years of experience, there is much to learn and a lot of hard work ahead as the scale up continues. As part of the HEP design, HEWs are meant to be supplemented by community volunteers (CV). Many of the areas where the HEWs have begun work have yet had the opportunity to find and train the sufficient number of CVs to properly support the HEW. This is a major constraint in the system, and it is expected that finding and training CVs takes considerable time. Many of the issues HEWs face are in regard to not enough support on the ground.

6.60 One concern that has yet to be addressed is whether implementing these 16 packages is being realized; each package requires extensive work and outreach. Further, HEWs since their inception have been pulled into help with other programs

and projects such as EPI, and as mentioned are not yet fully supported by their CV system in most cases. The burden of HEWs appears to have gradually increased, without extra compensation. With all the constraints they face, it would be very useful to understand how HEWs allocate their time across various activities. Time use and time availability studies are integral in moving forward for the HEW program.

6.61 A group comprising members of the Ethiopian Public Health Association in collaboration with experts from Tigray RHB, Public health Association of Tigray (PHAT) and FMOH set out to review the HEP in Tigray. They reviewed documents as well as surveyed and tested HEWs and conducted focus groups. Their findings have great lessons for all regions, and should be looked at closely. The demographic findings of the HEWs sends a mixed message. 58% were born and/or lived outside of their post kebele and woreda. 87.8% said they were assigned to their kebele ‘unwillingly.’ 23% of HEWs were missing or absent from their HP when the survey team arrived. The aforementioned statistics may account for the high absence rate. Such absenteeism is not uncommon in programs where young women are placed in rural areas. However, only 13.5% reported being unhappy with their post, a positive discovery. The HEWs are young, with an average age of 21.4 years +/- 3.6. It can be assumed they have family matters that need to be attended to in their villages/towns of origin

6.62 The HEW were also tested on their knowledge in areas relating to the 16 packages: family planning, antenatal care, HIV/AIDS prevention, labor assistance, diarrhea, neonatal care, nutrition, ARI/TB, malaria prevention, immunizations, health related tasks (e.g. how to give an injection), and environmental health. Scores were based on the number of questions answered correctly (or if an activity was demonstrated correctly). Scores were highest for family planning, HIV/AIDS prevention, and diarrhea diagnosis and treatment. HEWs showed competence in these areas, and it was felt that they could carry out tasks related to these areas properly. However, the lowest scores were seen in nutrition knowledge and ARI/TB. Scores were also low for neonatal care and delivery assistance.

6.63 All of the tasks given to HEW serve to better the NS of their respective communities, but it is difficult to assume they will achieve much success if their knowledge of nutrition is so poor. A mere 18.9% of the surveyed HEWs were able to calculate a weight for height score; only 21.6% could accurately classify stunting; and just 35% knew how to properly measure a MUAC. With endemic goiter rates high in Tigray, only 18.9% knew salt iodization needs to be universal and is needed by all for health. Focus group discussions also illuminated the fact that there are poor relationships between the HEWs and health workers in their area. Some HEWs even reported animosity between them.

6.64 Since then, the training of new HEWs with respect to nutrition has been strengthened, so it can be hoped that similar surveys in the future would produce more positive findings regarding HEWs’ knowledge regarding nutrition. Nevertheless, it is clear that adequate education of HEWs regarding nutrition is vital. There is a need to reassess HEWs’ knowledge in this area again, and to continually make efforts to ensure a high standard of education of HEWs regarding nutrition through regular assessments of their training curricula.

6.65 In Section 6.1-1, the concept of linkages with HEWs and other programs in their communities was touched on. It seems natural for those running these programs to appoint HEWs as coordinators for their kebeles and many do this; however potential problems can arise in interpersonal relationships as shown in the Tigray HEW study. Most HEWs are new and young and as was discovered in Tigray, not respected by local health workers. HEWs may be difficult for others to accept as leaders in the community as well, especially older women who have been trained and worked as community volunteers for extended periods of time. The cadre of community volunteers that is to be trained to support the HEWs should stem from the currently available CVs – those involved in current CV-focused programs – to help link past, present, and future programming in areas. This may solve some of the relationship issues among CVs and HEW, as they are brought together as a team and trained together. It would be important in the trainings to bring across the message that the HEW realizes she may learn from the experienced CVs, and the CVs may learn new material from the HEW.

6.66 Currently, the FMOH is interested in pursuing a transition of EOS program activities to the HEWs. By all accounts, the HEW system is not ready to take on such a large scale activity. It is vital that more research be done on HEWs, and how they handle their current workload as well as the demands of being involved at the same time as kebele coordinators for one or more programs other than the HEP. Implementing appropriate programs of community volunteers to support HEWs, and allowing time to learn and to scale up at an appropriate pace, is vital. To completely take over the EOS activities is a large undertaking, and appears beyond the scope of HEWs as they currently function and are trained, at least not without the support of CVs that are adequately trained and given adequate incentives. For the short term, it is recommended that the HEP be strengthened and further developed, specifically in the areas of community relations, working with the CV team, and implementation of all 16 packages with proper knowledge. Additional studies need to be carried out especially in regards to time allocation of HEWs, community relationships, and the ability to take over EOS activities.

6.3 THE ENHANCED OUTREACH STRATEGY (EOS)

6.67 In 2004, WFP, UNICEF and FMOH set out to design the Enhanced Outreach Strategy – one of the largest child survival initiatives ever to be put in place in Ethiopia. Following years of drought, 325 woredas were identified as most vulnerable and became the target of the EOS campaign. Starting in 2004, with phased-in implementation, these woredas would begin receiving biannual campaigns that involve vitamin A supplementation, deworming, measles vaccines, malnutrition screening, ITNs (in SNNPR), referral to the TSFP and TFP, and mass social mobilization and education. The program is targeted at children under five and PLW. The methodology of the EOS nutrition screening has changed since its inception. In the beginning, MUAC, weight, and length/height were all measured. In the last campaign this was cut down to only MUAC measurements. There are pros and cons to this change, but overall it seems to have benefited the program. In addition, a more limited version of the EOS – the Extended EOS (EEOS) – is now implemented in most of the woredas in the country that do not benefit from the regular EOS. EEOS provides all the same services to children under five and PLW, with the exception of nutritional screening and then referral to the TSFP and TFP. A map of EOS and TSFP coverage is located in Appendix 4 (Map 6.4).

6.68 Since its inception, EOS has garnished both rave reviews and strong criticisms. But it can safely be assumed that EOS has made a significant difference in the woredas receiving services as there is strong evidence that mass vitamin A and measles campaigns save lives. A report in 2006 by UNICEF and DPPA showed results for each of the regions. At the time of the report there had been 5 rounds of EOS. The table below shares some of the results from those 5 rounds.

6.69 Along with the above tables, a midline survey in ESHE woredas found that woredas where EOS campaigns had occurred had statistically higher vitamin A coverage numbers (Table 6.38). The table below shows the drastic increase in coverage over the 2 year period. While one cannot scientifically assign impacts to EOS with this study, it can be assumed this increase was due to the EOS as no other mass campaigns were taking place at that time.

Table 6.40: ESHE Findings on Vitamin A coverage. Region Baseline (2004) Mid-line (2006) P ValueAmhara 15% 88% <0.001SNNPR 14% 79% <0.001Oromiya 44% 54% <0.01

Source: ESHE (2006).

6.70 Unfortunately, lack of data and make it difficult at present to evaluate the impact of most of the interventions in the EOS at this point. But the EOS with or without TSFP and TFP would be a cost effective intervention even if the vitamin A supplementation and measles vaccinations were the only EOS/TSFP/TFP interventions with any impact. In Amhara and Oromiya, it cost $91,513,333 to implement EOS in 200671. The TSFP distributed food worth about $11,200,000 in 2006 to these regions72. Using the assumptions in Chapter 5, the EOS/TSFP/TFP programs produce about $410,000,000 in increased lifetime earnings in Amhara and Oromiya, when considering the reduced mortality from vitamin A and measles, while the total cost of these programs is around $100,000,000. Thus considering only these two interventions, the EOS/TSFP/TFP programs produce four times the value of their costs in economic benefits. Note that the calculations assume that the interventions other than vitamin A supplementation and measles vaccinations have zero benefit, but their costs are nevertheless counted in the computations.

6.71 An independent assessment of the EOS was carried out in November and December of 2006.73 This evaluation provided concrete evidence on what were assumed to be EOS strengths and weaknesses. Table 6.39 summarizes some of these findings.

6.72 Note that attempts are being made to address some of the flaws listed in the above table. For example, there are plans to administer tetanus toxoid injections to PLWs as part of the EOS in the near future, and efforts are under way to take steps needed to reduce the time taken after the screenings to deliver the TSFP rations.

6.73 Key recommendations from the aforementioned evaluation mirror suggestions from this report. It is imperative that more information be gathered consistently and of 71 It costs on average 1,855,000 birr to implement the EOS in one Woreda in Amhara and Oromia (Fiedler, Cost analysis of the EOS/EEOS Program, presented at the Hilton, Addis Ababa, March 2007). In 2006, the program was implemented in 73 Woredas in Amhara and 149 in Oromia.72 TSFP data obtained from Alemu Mekonnen, WFP.73 Hall Andrew, Khara Tanya. “Mission Report:EOS/TSF for child survival interventions” November 23 to December 12, 2006. UNICEF.

quality on the EOS program. The program was born out of necessity in an acute time of crisis. EOS is not so much a development program, as a transitional program trying to connect the gap between chronic emergencies and development. Due to the nature of emergency programs, it is common for emergency programs neither to employ baseline studies properly nor to implement monitoring systems. However, it is essential that implementation in all programs be monitored. A proper monitoring and evaluation system for EOS would only serve to better the program; a comprehensive nutritional surveillance program is crucial in this regard. As was discussed in Section 6.1-2, such a system could help develop clues as to where issues are occurring, why programs are succeeding or failing, and which aspects need modification.

Table 6.41: Selected findings from 2006 Independent assessmentPositive Negative

EOS is the largest program of its kind targeting more then 7 million children and 1.6 million PLW

A key issue is lack of data regarding EOS implementation and impact.

Children are now de-wormed on a regular basis

Due to practical and administrative reasons it may take up to 3 months after the screening for the provision of the TSFP ration to take place

TSFP is now in place and makes food available to malnourished children and women every three months (vs. only during emergencies)

Coverage rates are flawed as the denominator is number of children ages 6-59 months, whereas entry criteria is children less then 110 centimeters.

Malnourished children are identified regularly and severely malnourished are given referrals for treatment

A key opportunity to target PLW with tetanus toxoid, Iron/Folate supplements, etc is missed

Vitamin A coverage rates substantially increased

EOS data has limitations so it can not be used for nutrition surveillance

Source: Hall, A. & Khara, T. (2006).

6.74 There are other questions that lie ahead for the EOS program. As was mentioned in Section 6-2 on HEW, the FMOH is interested in the HEWs taking over EOS. However, this may not be the best option for the EOS at this time, as discussed above. Other questions include whether the TSFP should be joined with the PSNP and if targeting should be done jointly. Many of these questions can not be answered clearly at this time due to the lack of information.

6.75 It would best serve both the HEP and EOS programs if they remained independent for a time, at minimum 5 to 10 years, to establish their own roots in the community before combining. When both programs are seen as entitlements and as equally important, merging of the programs may be more appropriate. It is a risk if they are united too soon, one of the programs may be favored over the other, resulting one losing status and even decreasing effectiveness.

6.4 MICRONUTRIENTS

6.76 Micronutrient interventions are generally accepted as having extremely high benefit-cost ratios and as being vital for countries such as Ethiopia. Chapter 5 provides figures on the cost-effectiveness and benefit-cost ratio for some of these interventions, in

the context of Ethiopia. The 2005 national survey on VAD and IDD conducted by the Ethiopian Health Nutrition Research Institute (EHNRI) showed that the prevalence of Bitot’s spots74 in under-5 year old children was 1.7% (over 3-fold of the WHO cut-off point for a crisis) and that of night blindness of mothers was 1.8% which was nearly two-fold of the WHO cut-off point.

6.77 The total goiter rates according the EHNRI survey results were 39.9% and 35.8% in children 6 -12 years of age and mothers respectively. The same study found that only 4.2% of the surveyed HH had access to iodized salt.75 It was found that over 60 million Ethiopians are at risk of iodine deficiency; over 20 million have varying sizes of goiter; and there are over 77,400 cretins in Ethiopia and more than 50,000 per year peri-natal deaths that are attributable to iodine deficiency. DHS 2005 found 52% of women were anemic and greater then 70% of children under 17 months were anemic.

6.78 These numbers along with the impacts shown in Chapter 3 and the cost analysis in Chapter 5 attest to the fact that micronutrient initiatives are a foremost input to NS in Ethiopia.

6.79 Further research needs to be done in Ethiopia regarding micronutrients. This operational research could include novel ways to increase vitamin and mineral intake, such as though the use of Sprinkles and distribution of iron pots. The former has shown some interesting possibilities in other countries, but might face insurmountable distribution costs in Ethiopia. The latter has been field tested in Tanzania with promising results, although questions about possibile toxicity remain.

74 Sign of Vitamin A deficiency.75 As mentioned earlier in this draft, the DHS found this percentage to be about 20% rather than 4.2%. In any case, these are both very low percentages..

APPENDICES

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APPENDIX 2: SUPPLEMENTAL TABLES

Table A3.1: Determinants of Health of Pre-School Girls and Boys (Wasting)Regressions (Obs. 4206)

Weight For Height Z-Score(Girls)

Weight For Height Z-Score (Boys)

R-squared= .089703 R-squared= .046457Variable Coefficient T-ratio Coefficient T-ratioConstant -0.1520 (-3.138)*** -0.0340 (-2.651)***Child Age (months)

6-11 0.0555 (2.269)** 0.0753 (2.094)**12-17 0.0986 (4.989)*** 0.0732 (2.175)**18-23 0.0670 (2.290)** 0.0332 (0.419)24-29 0.0253 (1.143) 0.0354 (1.103)30-35 0.0021 (0.064) -0.0137 -(0.412)36-41 0.0018 -(0.051) 0.0170 (0.506)42-47 0.0032 (0.150) 0.0148 (0.360)48-53 0.0049 (0.403) 0.0165 (0.554)54-59 0.0005 -(0.176) 0.0205 (0.427)

Age of Head -0.0003 (-0.891) -0.0010 (-2.274)**Female Head 0.0130 (0.686) 0.0009 (1.531)Household size 0.0007 (1.657)* 0.0008 (2.151)**Parental Education

Primary -0.0114 (-0.094) 0.0039 (-0.166)Secondary 0.0428 (1.386) 0.0188 (1.088)

Higher 0.0759 (1.273) 0.0432 (0.783)Region

Tigray -0.0041 (-0.271) 0.0913 (-0.286)Afar -0.0141 (-4.478)*** -0.0146 (-4.164)***

Amhara -0.0350 (-1.766)* -0.0889 (-0.842)Ormiya -0.0183 (-1.718)* -0.0457 (-1.481)Somali -0.0933 (-3.298)*** -0.2150 (-2.247)**

Bensh-Z -0.0360 (-1.348) -0.0819 (-1.339)SNNPR -0.0438 (-2.13)** -0.0319 (-1.235)

Gambella -0.0398 (-3.316)*** -0.0348 (-1.828)*Dire dawa -0.0034 (-0.17) -0.1048 (-0.344)

Addis -0.0452 (-0.978) -0.0240 (-0.092)Iodine 0 -0.0262 (-1.045) -0.0401 (-1.066)Iodine 7 -0.0006 (-1.121) -0.0523 (-1.424)Iodine 15 -0.0252 (-1.284) -0.0290 (-1.181)Afterbirth care rec’d 0.0161 (1.692)* -0.0300 (-0.276)Two month check up post birth -0.0231 (-.735) -0.0169 (-.901)Toilet Type

Flush Toilet 0.0228 (2.062)** 0.0250 (1.825)*Pit Latrine 0.0023 (1.648)* 0.0465 (1.469)

No Flush 0.0185 (1.284) 0.0645 (1.418)Wealth 0.0198 (1.553) 0.0130 (1.988)*** Significant at 10% level; ** Significant at 5% level; *** Significant at 1% levelDefaults – Missed Education (for all education variables), Toilet – bush, Iodine 30, No 2 month check up post birth , region Harari

Table A3.2: Determinants of Health of Pre-School Girls and Boys (Stunting)Regressions (Obs. 4206)

Height for Age Z-Score(Girls)

Height for Age Z-Score (Boys)

R-squared= .057181, R-squared= .041882Variable Coefficient T-ratio Coefficient T-ratioConstant 0.1588 (-3.178)*** -0.1707 (-2.685)***Child Age (months)

6-11 0.1481 (4.908)*** 0.1375 (3.797)***12-17 0.3035 (4.857)*** 0.2732 (3.573)***18-23 0.4901 (1.405) 0.5112 (1.639)24-29 0.3196 (5.759)*** 0.3329 (3.647)***30-35 0.4187 (3.734)*** 0.4309 (2.689)***36-41 0.3056 (5.708)*** 0.2840 (3.982)***42-47 0.3863 (4.351)*** 0.4688 (2.221)**48-53 0.3131 (7.364)*** 0.2856 (5.834)***54-59 0.4514 (5.361)*** 0.4255 (4.057)***

Age of Head 0.0010 (-0.907) -0.0017 (-2.279)**Female Head 0.0456 (0.649) 0.0233 (1.497)Household size 0.0029 (1.729)* 0.0012 (2.213)**Parental Education

Primary -0.0516 (-0.167) -0.0433 (-0.218)Secondary -0.0320 (1.001) -0.0274 (0.788)

Higher 0.5895 (1.07) 0.7102 (0.612)Region

Tigray -0.0598 (-0.157) -0.1427 (-0.206)Afar -0.0350 (-4.365)*** -0.1300 (-4.085)***

Amhara -0.2181 (-1.603) -0.2477 (-0.718)Ormiya -0.0905 (-1.578) -0.1445 (-1.378)Somali -0.0947 (-3.184)*** -0.1072 (-2.172)**

Bensh-Z -0.0893 (-1.229) -0.1344 (-1.238)SNNPR -0.1930 (-1.913)* -0.2258 (-1.062)

Gambella -0.0208 (-3.262)*** -0.0232 (-1.763)*Dire dawa -0.1470 (-0.138) -0.2057 (-0.321)

Addis -0.0345 (-1.083) -0.0623 (-0.196)Iodine 0 -0.0347 (-1.052) 0.0549 (-1.088)Iodine 7 -0.0185 (-1.12) -0.0500 (-1.446)Iodine 15 -0.0537 (-1.28) -0.0794 (-1.196)Afterbirth care rec’d 0.0463 (1.768)* -0.0493 (-0.287)Two month check up post birth -0.0519 (-0.897) -0.0707 (-0.733)Toilet Type

Flush Toilet 0.0210 (2.06)** 0.3149 (1.833)*Pit Latrine 0.0527 (1.626) 0.1342 (1.458)

No Flush 0.0476 (1.295) 0.1308 (1.433)Wealth 0.0228 (1.445) 0.0270 (1.874)** Significant at 10% level; ** Significant at 5% level; *** Significant at 1% levelDefaults – Missed Education (for all education variables), Toilet – bush, Iodine 30, No 2 month check up post birth , region - harari

Table A4.1: Determinants of Breastfeeding76

Regressions (Obs. 4206)Girls Boys

Variable Coefficient T-ratio Coefficient T-ratioConstant 87.9414 (17.356)*** 91.6249 (17.102)***Age of head -0.3827 (-5.64)*** -0.3319 (-4.612)***Female Head -0.2981 (-0.141) -5.6411 (-2.573)**Household Size 1.3861 (3.746)*** 1.5171 (3.977)***

Parental EducationSecondary 0.9838 (0.234) 1.3734 (0.252)

Higher 7.2233 (0.233) -50.9921 (-1.686)*Region

Tigray -3.7473 (-0.97) -5.6357 (-1.386)Afar -1.9098 (-0.445) -2.9987 (-0.684)

Amhara 5.8153 (1.552) 8.2127 (2.075)**Ormiya 0.1645 (0.046) -2.5392 (-0.666)Somali -10.8269 (-2.551)** -11.0819 (-2.518)**

Bensh-Z 4.2840 (1.022) -1.8468 (-0.431)SNNPR 4.2961 (1.191) -0.3736 (-0.096)

Dire Dawa -16.2937 (-3.489)*** -13.0191 (-2.623)***Addis -2.1183 (-0.272) -10.7391 (-1.279)Harar -19.5815 (-3.8)*** -15.8010 (-3.007)***

Two month check up post birth 0.0584 (0.016) -6.3916 (-1.586)

After Birth Check Up 0.7212 (0.152) 0.3728 (0.071)

Distance to Health Centre -0.41081 (-2.508)** .18116 (1.068)Wealth -0.5918 (-1.026) -0.9144 (-1.763)*

* Significant at 10% level; ** Significant at 5% level; *** Significant at 1% levelDefaults – Missed Education (for all education variables), Toilet – bush, Iodine 30, No 2 month check up post birth . Regional Default – Gambella. Likelihood ratio test justify separation of regression by gender. Source Data DHS 2005

APPENDIX 3: ASSUMPTIONS FOR COSTING IN CHAPTER 5

76 Dependant variable is the number of month’s breastfeeding.

Section B: Current Interventions Costing and Effect on Mortality

BeneficiariesPSNP 5,664,471 beneficiaries77

located in 208 woredasSchool Feeding 639,191 beneficiaries78

located in 128 woredasEFA 3,188,511 beneficiaries, calculated as 15 kg

of grain per beneficiary per month, six months per year in the program79

located in 457 woredas MERET 363,278 beneficiaries, calculated as 15 kg

of grain per beneficiary per month, six months per year in the program80

located in 72 woredasTSFP 800,000 beneficiaries

located in 264 woredasCTC Programmes all of the 6-59 month old children that

would have died in the areas covered by the CTC for all of the years the CTC had been

77 dataset for 200578 dataset for 200679 based on the amount of food distributed in 200680 based on cost of food distributed in 2005

Section A: General Assumptions 

Population 78,000,000Average woreda size 150,000

Household size 5.2Under-five mortality rate 132Infant mortality rate 77Maternal mortality rate 6.7Number of births per year 3,600,000Under-five percent of pop. 18.25%Under-two percent of pop. 8.88%Reproductive-age women percent of pop.

21.8%

Percentage of rep.-age women that are pregnant

10%

GDP per capita 170Discount rate 5%Growth in real per capita GDP

0%

Percent of Ethiopia where malaria is endemic

72%

functioning in the woredaE/EOS: Vitamin A 6,650,000 beneficiaries81

E/EOS: Deworming 6,650,000 beneficiariesE/EOS measles 2,160,000 beneficiaries82

Bednets 20,000,000 distributedtwo nets per household

EPI 1,205,389 beneficiaries83

HEW the entire populationCHP

Breastfeeding 2,255,613 beneficiaries calculated as the number of pregnant women in areas

covered by the program for the years during which the program was active

Handwashing same as aboveLatrines 28,939,960 beneficiaries calculated as 80%

of the total population in the woredas TTBA 18,440 beneficiaries calculated as total

number of pregnant women in areas covered by the program for the years during which the program was active

CBRHA 6,240,000 beneficiaries calculated as 120 households for each of the 10,000 CBRHA

CostsFood Costs for EFA and MERET (includes product, transport, program costs, and a 10% government overhead)

Grain $400Supplementary food $600Edible oil $1000

PSNP $495TSFP $680School Feeding total cost per beneficiary: $18.82CHP: rough estimate of cost breakdown

Breastfeeding 30% of total CHP costsHand washing 20% of total CHP costsSanitation and hygiene 20% of total CHP costs

ImpactsThe cost per death averted and the BCR for child and maternal mortality include a range of +/-10%

81 E/EOS dataset for 2006 in Amhara and Oromia for one round83 the number of fully immunized children and women given tetanus toxoid injections in 200182 E/EOS dataset for 2006 in Amhara and Ormoia for two rounds

EFA one-third of 6-59 month old beneficiaries would have died

57% of 6-59 months olds that would have died have reduced mortality84

95% of those 57% would surviveTSFP the mortality rate among beneficiaries was

4.6 as high as the general population85

reduced deaths of moderately malnourished by 70%

Typical NGO CTC coverage: average from surveys 86

the number of deaths was converted into those deaths due to mild, moderate, and

severe malnutrition using the prevalence of global malnutrition and severe

malnutrition87

95% cure rate for moderately and severely malnourished

Institutionalized CTC coverage: 30%cure rate 60% of moderately and severely

malnourishedE/EOS: Vitamin A reduces U5MR by 20%88

E/EOS: Measles 4% of child deaths are due to measles89

vaccine efficacy - 90%90

Bednets reduces U5MR by 20%91

CHPBreastfeeding92 timely initiation of BF reduces NMR by

16%93; it increased in prevalence by 25.3%EBF reduces U5MR by 13%; it increased

in prevalence by 8%

84 Based on estimates, 57% of childhood mortality is related to malnutrition. Ethiopia PROFILES.89 The State of the World’s Children 2006. (2005).88 Beaton, G. H., Martorell, R., Aronson, K. J., Edmonston, B., Ross, A. C., Harvey, B., & McCabe, G., (1993).87 Pelletier, D. L et al (1994).86 Tanner, C. G., (2006).85 Pelletier, D. L et al (1994) found the mean relative risk for moderate malnutrition was 4.6. Since the target population of the TSFP is moderately malnourished children, we estimated that this was the increased probability of dying among the beneficiaries90 Aaby, P., Samb, B., Simondon, F., Seck, A. M., Bennett, J., Markowitz, L., & Whittle, H., (1996).91 Lengeler, C., (2004).92 We used the mid-term assessment to determine the increase in promoted activities. Community Assessment in selected ESHE focus woredas in Amhara, Oromia, & SNNPR regions. (2006).93 Edmond, K. M., Zandoh, C., Quigley, M., A., Amenga-Etego, S., Owusu-Agyei, S., & Kirkwood, B., R., (2006).

correct complementary feeding reduces U5MR by 6%94; it increased in prevalence

by 6%Hand washing reduces deaths due to diarrhea by 40%95; it

increased in prevalence by 7%96,97

U5 deaths due to diarrhea was 14.1%98

TTBA reduce NMR by 25%99

coverage: 75%100

94 Jones, G., Steketee, R., W, Black, R. E., Bhutta, Z., A. & Morris, S. S., (2003).95 Luby, S. P., Agboatwalla, M., Feikin, D. R., Painter, J., Billhimer, W., Altaf, A., & Hoekstra, R. M., (2005).96 The increase in prevalence of hand washing could not be determined from the mid-term assessment. Instead, we turned to another USAID-funded programme that also used CHPs to promote hygiene and sanitation. There, hand washing by the primary caregiver increased by 12% over two years. Here we are conservative and assume an increase of about half that. 97 Kolesar, R., Kleinau, E. F., Torres, M. P., Gil, C., de la Cruz, V., & Post, M., (2003).98 Black, R. E., Morris, S. S., & Bryce, J., (2003).99 Darmstadt, D. L., Bhutta, Z. A., Cousens, S., Adam, T., Walker, N., & de Burnis, L., (2003).100 Essential services for maternal and child survival in Ethiopia: Mobilizing the traditional and public health sectors and informing programming for the pastoralist populations. (2006).

Section C: Possible Interventions Costing and Effect on Mortality

BeneficiariesSalt iodization and Iron in iodized salt 99.9% of the population101

Vitamin A in Sugar 41% of the population102

CostsIodizing salt $0.05 per kg

annual demand for salt - 250,000MT103

Iron in iodized salt $0.45 per capita104

Vitamin A in sugar $16.00 per kgannual demand for sugar - 200,000 MT105

Iron and folate capsules $0.0024106

Iron and folate syrup $1.10 per 50mL107

Iodated oil $0.24108

E/EOS109: Vitamin A $0.02110

E/EOS: Deworming $0.0173111

ImpactsIodated oil to preg. women reduces U5MR by 6%112

Iodizing salt reduces U5MR by same amount as iodated oil

Iron and folate to 6-24 months olds increases the IQ of 30%, of anemic children by 7.5 points113

Iron and folate to preg. women reduces MMR by 22%114

Deworming reduces IMR by 20%115

Zinc reduces U5M due to diarrhea by 50%116,117

17% of U5M is caused by diarrhea118

101 CSA & ORC Macro (2006).102Mason, J. B., (2001). The Micronutrient Report. Current progress and trends in the control of vitamin A, iodine, and iron deficiencies. Ottawa, Micrnutrient Initiative.103 Yager, T. R., (2002).104 We use the average of the range proposed in Activity Highlight: Double fortification of salt. The Micronutrient Initiative.105 Umeta, M., (2005).106 Abebe Hailemariam, UNICEF, personal communication, August 2007.107 Risonar, M. G. D., Tengco, L. W., Rayco-Solon, P., & Solon, F.S. (2007). We assumed each child received one quarter of one mL per dose and that each child was dosed 72 times, which is weekly for 18 months.108 Abebe Hailemariam, UNICEF, personal communication, August 2007.109 E/EOS costs per supplement are for without distribution costs.110 Abebe Hailemariam, UNICEF, personal communication, August 2007. This cost includes the procurement and distribution of scissors.111 Abebe Hailemariam, UNICEF, personal communication, August 2007.112 Mahomed, K., & Gulmezoglu, A. M., (2002).113 Ross, J., & Horton, S., (1998).114 Stoltzfus, R., Mullany, L. & Black, R.E. (2003).115 Christian, P., Khatry, S. K., & West Jr., K. P., (2004).116 Baqui, A. H., Black, R. E., El Arifeen, S., Yunus, M., Chakraborty, J., Ahmed, S., & Vaughan, J. P., (2002).117 We assumed each child would have three diarrheal episodes per year requiring treatment with zinc.118 Black, R. E., Morris, S. S., & Bryce, J., (2003).

Section D: Impact on Productivity

GeneralAverage adult height 160 cmDecrease in earnings for a 1% decrease in height

2.4%119

Prevalence of LBW 13.50%120

Decrease in earnings due to LBW 7.5%121

Increase in height due to increase in birth weight

1.2 cm for 0.45 kg122

Prevalence of anemia 54%Prevalence of IDD 65%Anemia decreases earnings by 5%123

ImpactsCTC programs124 under-twos admitted to CTCs were on

average -2.5 z-scores wt-for-ht125

after treatment, their height would return to normal

EFA a shock decreases child height by 1.75cmcan mitigate the effect of a shock on the

poorest half of the children below two years of age126

Bednets decrease LBW by 28%127

Iodine increases birth weight by about 50 grams128

Deworming increases birth weight by about 60 grams129

Iron and folate decreases the prevalence of LBW by 13%130

119 Thomas, D., & Strauss, J., (1997).120 Ethiopia PROFILES, (2005).121 Behrman, J. R., Alderman, H., & Hoddinott, J., (2004).122 Le, H., Stien, A., Barhhart, H., Ramakrishnan, U., & Martorell, R., (2003).123 Ross, J., & Horton, S., (1998).124 Because it seems that only children less than two years of age are able to benefit in terms of decreased stunting, this impact only applies to this age group.125 If this difference were maintained until adulthood, as some studies suggest happens when malnutrition is severe and persistent, this would decrease adult height by about 20 cm, assuming a standard deviation in adult height of about 7.5 cm.126 Yamano, T., Alderman, H., & Christiaensen, L., (2005).127 Ter Kuile, F. O., Terlouw, D. J., Phillips-Howard, P. A., Hawley, W. A., Friedman, J. F., Kariuki, S. K., Shi, Y. P., Kolczak, M. S., Lal, A. A., Vulule, J. M., Nahlen, B. L., (2003).128 Mason, J. B., Deitchler, M., Gilman, K., Shuaib, M., Hotchkiss, K., Mason, K., Mock, N., & Sethuraman, K., (2002).129 Christian, P., et al (2004).130 Cogswell, M. E., , I., Ickes, L., Yip, R., & Brittenham, G. M., (2003).

Section E: Impact on Ability

GeneralIncrease earnings due to change in IQ 10% for a one standard deviation

increase131

Standard deviation of IQ 15ImpactsIron and folate to 6-24 months olds132 increases IQ of 30%133 of anemic children

by 7.5 points134

Iodated oil to preg. women increases IQ of children with IDD by 13.5 points135

Deworming decreases prevalence of anemia by 50%136

131 Alderman, H., Behrman, J. R., & Sabot, R., (1996).132 For both iron and folate to children and iodated oil to pregnant women, it was assumed that the same affect would occur with fortification as with supplementation. 133 Menendez, C., Kahigwa, E., Hirt, R., Vounatsou, P., Aponte, J. J., Font, F., Acosta, C. J., Schellenberg, D. M., Galindom C. M., Kimario, J., Urassa, H., Brabin, B., Smith, T. A., Kitua, A Y., Tanner, M., & Alonso, P. L., (1997).134 Ross, J., & Horton, S., (1998).135 Grantham-McGregor, S. M., Fernald, L. C., & Sethuraman, K., (1999).136 Stolzfus, R., Chway, H.M., Montresor, A., Tielsch, J.M., Jape, J.K., Albonico, M. & Savioli, L. (2004).

APPENDIX 4: MAPS