Growing Nutrition for Mothers and Children (GROW) Program in Ethiopia
FUNDED BY: GLOBAL AFFAIRS CANADA
PROGRAM IMPLEMENTED BY: CARE IN PARTNERSHIP WITH CUSO INTERNATIONAL AND MCGILL UNIVERSITY (2016-2020)
Baseline household survey report
Submitted to:
CAEE Ethiopia
Submitted by:
Le Monde Health and Development Consultancy PLC Matyas Building, 5th floor, Room No. 406 & 407 P.O.BOX 3200 Code 1250 Addis Ababa, Ethiopia Tel: +251 913 05 42 65 or +251 920 10 10 10 Email: [email protected] or [email protected]
December 2016 Addis Ababa Acknowledgements Le Monde Health and Development Consultancy (LHD) PLC acknowledges the efforts of all individuals and their institutions that assisted with this baseline study. Our sincere gratitude is to the study participants for their cooperation and time. Our special thank goes to the staff of CARE Ethiopia, CARE Canada and McGill University for their guidance and valuable input throughout the study. We would also like to thank Save the Children International, Concern Ethiopia and ENCU for supporting us by providing tools for the anthropometric survey.
i Table of contents Acknowledgements ...... i Table of contents ...... ii List of tables...... iii List of figures ...... v List of acronyms ...... vi Executive summary ...... vii 1. Background ...... 1 1.1. Introduction ...... 1 1.2. GROW program ...... 1 2. Objectives of the survey ...... 2 3. Methods ...... 2 3.1. Study area and period ...... 2 3.2. Study design ...... 2 3.3. Study population ...... 2 3.4. Sample size ...... 2 3.5. Sampling technique ...... 3 3.6. Data collection tools ...... 4 4. Data collection, management and analysis...... 4 5. Quality control ...... 4 6. Ethical considerations ...... 5 7. Findings ...... 5 7.1. Response rates and characteristics of respondents ...... 5 7.2. Household characteristics and possessions ...... 6 7.3. Food production and consumption ...... 8 7.3.1. Source of food ...... 8 7.3.2. Home garden and livestock ...... 9 7.3.3. Food preservation and storage ...... 12 7.3.4. Income and savings ...... 13 7.3.5. Women and Men Dietary Diversity...... 15 7.4. Household food security situation...... 17 7.5. Infant and Young Child Feeding Practices (IYCF) ...... 17 7.6. Child’s Health ...... 20 7.7. Nutritional status of children and women ...... 22 7.7.1. Acute malnutrition (Weight-for-height) ...... 22 7.7.2. Stunting (Height-for-age) ...... 24 7.7.3. Underweight (Weight-for-age) ...... 25 7.7.4. Nutritional status of women (MUAC) ...... 25 7.8. Water, Sanitation and Hygiene ...... 25 7.9. Gender ...... 28 7.9.1. Public engagement ...... 28 7.9.2. Attitudes and perceptions ...... 29 7.9.3. Household decision-making ...... 30 8. Discussion ...... 32 9. Recommendations ...... 33 Annexes ...... 35 Annex 1: Foods and liquids given to 0-5 month infants ...... 35 Annex 2: Food types consumed among 6-8 months old infants ...... 35 Annex 3: Prevalence of underweight ...... 36 Annex 4: Baseline values for key indicators ...... 37
ii List of tables Table 1: List of Woredas and Kebeles included in the survey...... 2 Table 2: Sample number of children, women and men for the baseline study in Afar, East Hararghe and West Hararghe, October 2016 ...... 5 Table 3: Socio-demographic characteristics of respondents in Afar, East Hararghe and West Hararghe, October 2016 ...... 6 Table 4: Place of cooking and percentage of households having electricity, solar power or generator in Afar, East Hararghe and West Hararghe, October 2016 ...... 7 Table 5: Household possessions in Afar, East Hararghe and West Hararghe, October 2016 ...... 8 Table 6: Source of food for household consumption in Afar, East Hararghe and West Hararghe, October 2016 . 8 Table 7: Source of land personally managed by women and inputs for home gardening in Afar, East Hararghe and West Hararghe, October 2016 ...... 9 Table 8: Types of foods produced and consumed from home gardening in the past year in Afar, East Hararghe and West Hararghe, October 2016 ...... 10 Table 9: Ultimate decision maker about the type of foods to be produced and consumed from home gardening in Afar, East Hararghe and West Hararghe, October 2016 ...... 11 Table 10: Average number of livestock owned by household by type of animal in Afar, East Hararghe and West Hararghe, October 2016 ...... 11 Table 11: Methods of food preservation used and types of foods preserved by households in the last 12 months in Afar, East Hararghe and West Hararghe, October 2016 ...... 12 Table 12: Types of crops stored, methods of storage and purpose of storing foods by households in Afar, East Hararghe and West Hararghe, October 2016 ...... 13 Table 13: Women’s income from home garden and other sources in Afar, East Hararghe and West Hararghe, October 2016 ...... 14 Table 14: Saving practice of women in Afar, East Hararghe and West Hararghe, October 2016 ...... 15 Table 15: Women’s and men’s Diet Diversity Score (DDS) in Afar, East Hararghe and West Hararghe, October 2016 ...... 16 Table 16: Household hunger Score in Afar, East Hararghe and West Hararghe, October 2016 ...... 17 Table 17: Breastfeeding related practices among women in Afar, East Hararghe and West Hararghe, October 2016 ...... 18 Table 18: Complementary feeding related practices among women in Afar, East Hararghe and West Hararghe, October 2016 ...... 19 Table 19: Diarrhea prevalence and feeding practice during illness in Afar, East Hararghe and West Hararghe, October 2016 ...... 20 Table 20: Care seeking during diarrhea in Afar, East Hararghe and West Hararghe, October 2016 ...... 21 Table 21: Growth monitoring and treatment for malnutrition in Afar, East Hararghe and West Hararghe, October 2016 ...... 21 Table 22: Preference on service providers to seek care from if child becomes malnourished in the future in Afar, East Hararghe and West Hararghe, October 2016 ...... 22 Table 23: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016 ...... 23 Table 24: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016 ...... 23 Table 25: Prevalence of stunting based on height-for-age z-scores and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016 ...... 24 Table 26: Prevalence of stunting based on height-for-age z-scores and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016 ...... 24
iii Table 27: Prevalence of acute malnutrition among women of reproductive age (MUAC <230mm) in Afar and East and West Hararghe, October 2016 ...... 25 Table 28: Access to safe water supply in Afar and East and West Hararghe, October 2016 ...... 26 Table 29: Household water treatment practices in Afar and East and West Hararghe, October 2016 ...... 26 Table 30: Availability of hand washing station at households in Afar and East and West Hararghe, October 2016 ...... 27 Table 31: Access to latrine facilities and excreta disposal practices in Afar and East and West Hararghe, October 2016 ...... 28 Table 32: Women and men participation in local committees in Afar and East and West Hararghe, October 2016 ...... 28 Table 33: Attitudes related to gender among women and men in Afar and East and West Hararghe, October 2016 ...... 29 Table 34: Perceptions related to gender among women in Afar and East and West Hararghe, October 2016.. 30 Table 35: Decision-maker on household issues in male-headed households in Afar and East and West Hararghe, October 2016 ...... 31 Table 36: Foods and liquids given to 0-5 month infants in Afar and East and West Hararghe, October 2016 ... 35 Table 37: Food types consumed among 6-8 months old infants in Afar and East and West Hararghe, October 2016 ...... 35 Table 38: Prevalence of underweight based on weight-for-age z-scores and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016...... 36 Table 39: Prevalence of underweight based on weight-for-age z-scores and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016...... 37 Table 40: Baseline values for key indicators, October 2016 ...... 37
iv List of figures Figure 1: Age of women respondents in Afar, East Hararghe and West Hararghe, October 2016 ...... 5 Figure 2: Type of household head of surveyed households in Afar, East Hararghe and West Hararghe, October 2016 ...... 7 Figure 3: Percentage of households participating in the PSNP Program in Afar, East Hararghe and West Hararghe, October 2016 ...... 7 Figure 4: Source of food for household consumption by type of household head in Afar, East Hararghe and West Hararghe, October 2016 ...... 9 Figure 5: Final decision maker about which animals owned by the household should be consumed for meat and when should it be consumed in Afar, East Hararghe and West Hararghe, October 2016 ...... 12 Figure 6: Percent of women ever received credit in the past two years in Afar, East Hararghe and West Hararghe, October 2016 ...... 15 Figure 7: Percent of women and men consuming ≥4 food groups in the past 24 hours in Afar, East Hararghe and West Hararghe, October 2016 ...... 16 Figure 8: Percent of hand washing station with water and soap/substitute in Afar and East and West Hararghe, October 2016 ...... 27 Figure 9: Opinion about the level of women and men participation in water committees in Afar and East and West Hararghe, October 2016 ...... 29 Figure 10: Decision-maker on household issues in male-headed households in Afar and East and West Hararghe, October 2016 ...... 32
v List of acronyms
ANC Antenatal Care
CBNC Community Based Newborn Care
CMAM Community Management of Acute Malnutrition
DDS Dietary Diversity Score
EBF Exclusive Breast Feeding
EDHS Ethiopia Demographic and Health Survey
ENCU Emergency Nutrition Coordination Unit
GAM Global Acute Malnutrition
HDA Health Development Army
HEWs Health Extension Workers
HH Household/s
IYCF Infant and Young Child Feeding
LHD Le Monde Health and Development Consultancy
MAD Minimum Acceptable Diet
MDD Minimum Dietary Diversity
MMF Minimum Meal Frequency
MUAC Middle Upper Arm Circumference
ODF Open Defecation Free
OTP Outpatient Therapeutic Program
PSNP Productive Safety Net Program
SAM Severe Acute Malnutrition
SPSS Statistical Package for Social Sciences
VSLA Village Saving and Loan Association
vi Executive summary Background CARE is currently implementing the Growing Nutrition for Mothers and Children (GROW) program, with funding provided by Global Affairs Canada, in the East Hararghe and West Hararghe Zones of Oromia Region (six Woredas in each Zone) and in Afar Region (two Woredas). In total, GROW is being implemented in 164 Kebeles found in 14 Woredas. The goal of the program is to improve the nutritional status of women of reproductive age and boys and girls under 5 years in Ethiopia. This baseline study was conducted to obtain baseline values for the key GROW program areas. Methods This baseline study was conducted in 39 Kebeles selected from the 14 project target Woredas found in East Hararghe, West Hararghe and Afar. A community-based cross-sectional observational study design was employed. The data was collected through household surveys using a standardized questionnaire and ODK Collect App uploaded on tablets. The questionnaire had one section for women and another section for their husbands/partners. A total of 1310 women and children were selected for the sample, of which 1261 were successfully interviewed and included in the study, yielding a response rate of 96.3%. In addition, 908 men were interviewed with a response rate of 69.3%. Anthropometric measurement (length/height and weight) of 950 children aged between 6-59 months was taken to calculate their nutritional status. Presence of bilateral oedema among children aged 6- 59 months was also assessed. Middle upper arm circumference (MUAC) measurement was taken from 1236 women of reproductive age group (age 15-49 years). The data was collected from October 9-30, 2016. Findings1 Less than a-third (30.4%) of women consumed 4 or more food groups in the 24 hours period preceding the survey. The average women’s dietary diversity score (DDS) was 3.1 and the meal frequency was 2.7 per day. Slightly higher than half (55.5%) of children 0-5 months age were exclusively breastfed. Dietary diversity of complementary foods, which is measured by minimum meal (diet) diversity (MMD), was met by around a quarter (26.1%) of children aged 6-23 months. The minimum acceptable diet (MAD), which accounts both for practices of optimal diversity and frequency stood at 20.2%, showing that nearly four out of five children did not consume complementary food according to the recommended diversity and frequency. Global acute malnutrition (GAM) rate, children age 6-59 months who fall below the <-2 z-score, was 13.5%, with the highest rate recorded in Afar (23%). Severe acute malnutrition (SAM) prevalence was 5.3%. The overall prevalence of stunting, which measures the level of chronic malnutrition by labeling height/length-for-age index below -2 z-score using the WHO 2006 reference chart, was 39.1%. Overall, 15.2% of children under the age of 5 years experienced diarrhea in the 2-week period prior to the survey. The prevalence of acute malnutrition among all women aged 15-49 years (MUAC less than 230mm) was 24.8%, with the highest prevalence recorded among currently pregnant women (34.5%). The prevalence was 24.7% among currently pregnant and/or lactating women. Only 30% of the households use water from improved sources, with the lowest recorded in Afar (15.4%). Few households (13.8%) use improved toilet facilities that are not shared with other households. Open defecation is reported to be practiced in half (51.5%) of households, with the highest in Afar (92%).
1 See annex 4 for baseline values of key indicators vii 1. Background 1.1. Introduction Proper nutrition is crucial for adult health and well-being, and critical to the development of children, particularly in the first 1000 days of life. Globally, it is estimated that under nutrition is responsible, directly or indirectly, for at least 35% of deaths in children less than five years of age. Under nutrition is also a major cause of disability preventing children who survive from reaching their full development potential. According to WHO 2010 health statistics, an estimated 32%, or 186 million, children below five years of age in developing countries are stunted and about 10%, or 55 million, are wasted. In Ethiopia, there has been a substantial decline in the proportion of malnourished children in the last 15 years. The prevalence of stunting has reduced from 58% in 2000 to 40% in 2014. The proportion of underweight children was 41% in 2000 and declined to 25% in 2014. However, malnutrition ranks among the top problems affecting Ethiopian people in general, and children under-5 and mothers in particular. Findings from the 2014 Ethiopia Demographic and Health Mini-Survey (EDHS) showed that 9% of under-5 children suffered from acute malnutrition (wasting), although it showed a slight reduction from 12% in 2000. Underlying causes of malnutrition in Ethiopia include: a) a lack of access to sufficient and nutritious food (many families are unable to acquire sufficient food and intra-household consumption is unbalanced); b) a lack of appropriate care and limited knowledge of nutrition (certain practices have a negative impact on nutrition); and c) a lack of basic health, water and sanitation services (leading to diseases which increase malnutrition rates). Ethiopia has made encouraging progress in recent years in detecting and managing acute malnutrition. However, there is growing evidence that a more integrated approach is required to tackle the underlying causes of malnutrition. 1.2. GROW program CARE is currently implementing the Growing Nutrition for Mothers and Children program with funding provided by Global Affairs Canada in Oromia Region: East Hararghe Zone (six Woredas, 78 Kebeles) and West Hararghe Zone (six Woredas, 78 Kebeles) and Afar Region: Guanine (two Woredas, eight Kebeles) and Argoba special Woreda (4 Kebeles). In total, GROW is being implemented in 164 Kebeles in Oromia and Afar regions. GROW is a partnership between CARE International, CUSO International, McGill University, the Government of Ethiopia (Ministries of Health, Agriculture, Women’s Affairs, and Mines, Water and Irrigation) and Global Affairs Canada. The project implementation between is April 2016 - March 2020. GROW is a scale up of CARE’s successful project Improving Health and Nutrition of Vulnerable Women and Children in Ethiopia and Zimbabwe (2012 – 2014) funded by Global Affairs Canada through the Muskoka Initiative Partnership Program. The goal of GROW is to improve the nutritional status of women of reproductive age and boys and girls under 5 years in Ethiopia. The program’s ultimate outcome is to improve the nutritional status of women of reproductive age (15-49) and boys and girls under five in Ethiopia. The program has the following three intermediate outcomes: ▪ Improve nutrition practices and services for women of reproductive age and boys and girls under 5 years; ▪ Improve nutrition sensitive practices for women of reproductive age and boys and girls under 5; and, ▪ Strengthen governance of gender-sensitive nutrition programs and approaches at the Federal, Regional, Zonal and Woreda levels.
1 2. Objectives of the survey The main objective of this baseline study was to obtain baseline values for the key GROW program areas. The specific objectives were to: ▪ Examine attitudes, behaviors and practices related to nutrition, hygiene and sanitation, gender and women’s empowerment ▪ Establish baseline values for the outcome level indicators for the program 3. Methods 3.1. Study area and period This baseline study was conducted in 39 Kebeles selected from the 164 project intervention Kebeles in Oromia and Afar regions. The survey covered 6 Woredas in East Hararghe, 6 Woredas in West Hararghe and 2 Woredas in Afar (total 14 Woredas). The data was collected from October 9-30, 2016. Table 1 shows the names of study Kebeles by Woredas. Table 1: List of Woredas and Kebeles included in the survey Region/Zone Woreda No. of Kebeles Kebele name Afar Argoba 4 Abali, Sufager, Tach Metekeleya and Lay Meteklya Afar Gewane 4 Ourafita, Yiggle, Gelaladora and Gebeyabora East Hararghe Girawa 3 Lafto Somonu, Meda Jalela and Tokkuma Jalela East Hararghe Kombolcha 3 Burka Negaya, Egu and Samergene East Hararghe Meta 2 Doke No 1 and Chefe Anani East Hararghe Deder 4 Geba Gudina, Kura Dader, Yatu and Kabso Tokkuma East Hararghe Gursum 2 Oda Oromia and Oda Sentela East Hararghe Babile 2 Berkele and Najat Gemachisa West Hararghe Boko 2 Cabii and Mayuu West Hararghe Odabultum 3 Koluu, GubaGutu and Gabiba West Hararghe Mieso 1 D/Kora West Hararghe Mesela 4 Kufa kaas gamachis, Abaadir, Abbaa cabsii and Gabbis West Hararghe Chiro 2 K/Gudiinaa and W/Gille West Hararghe Gemechis 3 Sire –Gudo, S/Q/H/xaxee and G/Dinget Total 39
3.2. Study design A community-based cross-sectional observational study design was employed. The study include a household survey (questionnaire including observation) and anthropometric measurement of women and children. 3.3. Study population Children aged 0-59 months, their mothers or primary care givers and fathers (or other male household members) were the study population. 3.4. Sample size The sample size was calculated using prevalence of key infant and young child feeding (IYCF) practices of exclusive breastfeeding and a target percentage point change expected to take place at the end of the proposed intervention. CARE’s proposed intervention aims to improve exclusive breastfeeding by 15 percentage points and stunting among participating children by 5 percentage points at end of the program. For the IYCF indicators, exclusive breastfeeding was used as the key indicator for sample size determination. For sample size estimation, prevailing baseline rate was set at P0 = 52% and expected rate of change at P1 = 67% (EDHS 2011). Using a significance level of 5%, power = 80%, difference between baseline and end line rates at 15 percentage points, with a design effect of 1.5, it was estimated that a sample of 200 children have to be included in each of the age
2 groups, i.e. 0-5, 6-11, 12-17, 18-23, and 24-59 months. After adjusting the sample size for Afar and a 10% increase for non-response and errors/missed forms, it was decided to include a sample of 262 children in each group with a total sample of 1310 children. Aside from interviewing the primary caregiver, the study also includes a men’s section which required interviewing the partner or husband of the primary caregiver, which essentially doubled the sample size to 2620 respondents. 3.5. Sampling technique Selection of Kebeles The sampling frame for this survey was constructed using Kebele level population data obtained from government census, district and local office sources within the 12 intervention Woredas. Accordingly, 39 Kebeles were selected from 164 intervention Kebeles using probability proportional to size (PPS) technique with a total population of 276,804 as provided in the sampling frame. The calculated sample size (1310) was allocated across the 39 selected Kebeles using PPS technique based on the population size of Kebeles. Selection of households and study participants Segmentation and mapping was used to randomly select households/sampling units within the Kebele. Upon arrival at a selected Kebele, the team contacted health extension workers and the Kebele Administrator and collected information on the number of villages together with the average number of under five children per village. Based on the information, the Kebele was segmented to sub-geographical units (villages) depending on the size of villages and the population size of under five children. In cases where the required number of sample was higher than the average number of under five children per village, adjacent villages were merged and taken as one segment. After segmentation, the team randomly selected one segment using lottery method and prepared a sampling frame by listing all households having under five children. As the sample size for each group of children was pre- determined, separate lists were prepared for households with children of age 0-5, 6-11, 12-17, 18-23, and 24- 59 months. Only children whose mother/caregiver were eligible for the survey (i.e. women of reproductive age) were included in the list. When a household had more than one eligible child, one child was randomly selected (using lottery method) and included in the list. After households were listed, the required number of households for each age group were randomly selected using a random number generator app installed on the tablets. Women, children and men were selected and included in the study as per the following criteria (one per household for each type of study participant). Women: The mother or caregiver of a child between 0-59 months of age selected for the study. Only women of 15-49 years of age who permanently reside in the selected households and lived in the Kebele for at least 6 months were included. Children: Children of age between 0-59 months who permanently live with family of the selected household and without any known or suspected chronic or congenital diseases or physical deformity associated with growth problems were included in the study. Men: Apart from interviewing the mother or primary caregiver of the child, man, preferably the father of the selected child was interviewed. Illegible men for the interview were selected based on the following criteria: Inclusion criteria for men Men of at least 15 years of age who are preferably the father of the selected child or otherwise another man within the household (preferably with a child aged 0-59 months) were interviewed in each selected household. Only men who had lived in the Kebele for at least 6 months and were permanently residing in the selected households were included.
3 3.6. Data collection tools Household survey: The data was collected through household surveys using a standardized questionnaire. The questionnaire had one section for women and another section for their husbands/partners. Socio-demographic information of women and men, information on basic household characteristics, status of household food security, and water, sanitation and hygiene information was collected. Data on feeding practices for the young children, child’s health, women’s and men’s dietary diversity and meal frequency, gender equity, and women’s participation in household decision making was also captured in the household survey. In addition, GPS coordinates of the selected households were recorded. Anthropometric measurement: Anthropometric measurements (length/height and weight) of children 6-59 months of age were taken to calculate their nutritional status. The weight of children was measured using digital scales and length/height measured using a standardized height board. Presence of bilateral oedema among children aged 6-59 months was also assessed. Middle upper arm circumference (MUAC) measurements were taken to assess the nutritional status of women age 15-49 years. 4. Data collection, management and analysis A total of fifteen (15) teams, each team having one team leader and two enumerators were deployed for the field level data collection. The field teams were led by three survey managers (one for East Hararghe, one for West Hararghe and one for Afar) who were responsible for coordinating the day-to-day field activities. The data was collected using ODK Collect application for Android tablets. To create backups and prevent data loss, the study team transferred data from tablets to hard drives on a regular basis using ODK Briefcase App. Data collected using ODK Collect application was transferred to a hard drive and pulled to Ms-Excel (CSF format) using ODK Briefcase App. Then, the data was exported to SPSS version 20 for Windows and cleaned for missing values, inconsistencies and out of range figures. Since the CSF format have only question numbers, variable names and response values were recorded on SPSS in line with the questionnaire. Responses for questions with multiple responses were also recorded. Data tabulation plan was prepared and shared with CARE Ethiopia, McGill University and CARE Canada before analysis. SPSS version 20 for Windows was used for data analysis and descriptive statistics including frequencies, proportions and means were computed. Findings from the study are presented in tables and graphs. 5. Quality control The quality of this baseline survey was maintained by introducing strategic monitoring measures at all stages including planning, data collection, data management, interpretation and write-up. The survey was led by a well- qualified and experienced Principal Investigator. Three survey managers were employed and closely followed the day-to-day data collection. Enumerators who are well versed in local languages were recruited at study sites and trained for 5 days. A survey manual was prepared for use by data collectors as a quick reference tool in the field. The ODK Collect data collection was programed in a way to prevent entry of inaccurate (outliers or other errors), and incomplete data (missing values). Pilot-testing of the questionnaire and ODK Collect data collection template was conducted before the actual data collection. On a daily basis, team leaders reviewed data to ensure the questionnaire has been administered correctly. For this purpose, the ODK App was programed in such a way that forms cannot be fully submitted until the team leader has reviewed/approved it. Standard digital scales and height boards were used for measuring weight and height/length respectively. MUAC measurements were taken using standard MUAC tapes. As part of enumerators training, standardization test of anthropometric measurements was conducted to assess enumerators’ skill in accurately measuring weight and height of children.
4 6. Ethical considerations Ethical clearance was obtained from the McGill University IRB review board. Government sector offices at Zonal and Woreda level were officially communicated prior to data collection. Up on arrival at field, enumerators informed Kebele leaders about the purpose, content and sampling methods of the study. Study participants were informed about the purpose of the baseline study and how the results will be used. They are clearly informed about their right to refuse to take part, terminate the interview at any point or not answering any question. Using a standard consent form provided by CARE, consent (99.8% verbal) was received from each study participant before each interview. For anthropometric measurement, consent was received from the mother/caregiver before measuring weight and height/length of a child. Interviews and were conducted at household level in settings that ensure privacy. Copies of the consent form were left with Kebele leaders in case participants want to review at a later time. No names or other identifying information was recorded in the questionnaires and electronic database. Acute malnutrition cases (both SAM and MAM) identified in the survey were referred to the nearest health facilities providing OTP and SC services. 7. Findings 7.1. Response rates and characteristics of respondents Table 2 shows response rates for the baseline study. A total of 1310 women and children were selected for the sample, of which 1261 were successfully interviewed and included in the study, yielding a response rate of 96.3%. In households included in the study, a total of 908 men were interviewed with a response rate of 69.3%. Table 2: Sample number of children, women and men for the baseline study in Afar, East Hararghe and West Hararghe, October 2016 Calculated sample Actual achieved sample East West Afar East Hararghe West Hararghe Total Afar Total H. H. n % n % n % n % Total Children 292 530 490 1310 286 97.9% 502 94.7% 473 96.5% 1261 96.3% 0-5 months 58 106 98 262 61 105.2% 122 115.1% 92 93.9% 275 105.0% 6-11 months 58 106 98 262 53 91.4% 76 71.7% 90 91.8% 219 83.6% 12-17 months 58 106 98 262 60 103.4% 118 111.3% 105 107.1% 283 108.0% 18-23 months 58 106 98 262 43 74.1% 88 83.0% 82 83.7% 213 81.3% 24-59 months 58 106 98 262 69 119.0% 98 92.5% 104 106.1% 271 103.4% Women 292 530 490 1310 286 97.9% 502 94.7% 473 96.5% 1261 96.3% Men 292 530 490 1310 168 57.5% 361 68.1% 379 77.3% 908 69.3%
About two-third (65.3%) of women respondents were under the age of 30 years. As presented in figure 1 below, 37.7% of respondents were in the age group of 25-29 years, followed by those aged 20-24 years (22.3%). The majority (63.8%) of women respondents were spouses and 23% were parent of the household head. One in every ten women (10.5%) were heads of the surveyed households.
40.0% 37.7%
30.0% 22.3% 19.5% 20.0% 10.9% 10.0% 5.3% 4.0% 0.4% 0.0% 15-19 20-24 25-29 30-34 35-39 40-44 45-49
Figure 1: Age of women respondents in Afar, East Hararghe and West Hararghe, October 2016
5 The majority of respondents were married to a single spouse (91.8% of women and 94.5% of men). About eight women respondents in ten (79%) and three quarters of men (74.8%) had never attended school. The majority (81.9% of women and 76.7% of men) could not read. Nearly two-thirds (64%) of women were unemployed as compared with 38.2% of men. Twenty percent of women were engaged in housekeeping, 11.7% in crop production and 10.7% in livestock rearing. Among men respondents, 33.3%, 29.0% and 20.0% were engaged in casual labor, crop production and livestock rearing respectively. Table 3: Socio-demographic characteristics of respondents in Afar, East Hararghe and West Hararghe, October 2016 Women [n=1261] Men [n=908] Characteristics Count % Count % Marital status Married (monogamous) 1157 91.8% 858 94.5% Married (polygamous) 47 3.7% 47 5.2% Divorced or separated 24 1.9% 1 0.1% Widowed 29 2.3% 0 0.0% Cohabitating with partner (monogamous) 4 0.3% 0 0.0% Cohabitating with partner (polygamous) 0 0.0% 1 0.1% Single (Never married) 0 0.0% 1 0.1% Education status Never attended school 996 79.0% 679 74.8% Some primary (grade 1-4) 144 11.4% 91 10.0% Completed primary (grade 5-8) 87 6.9% 80 8.8% Some secondary (grade 9-11) 15 1.2% 25 2.8% Completed secondary (completed grade 12) 5 0.4% 8 0.9% Some higher education 2 0.2% 5 0.6% Completed higher education 4 0.3% 5 0.6% Adult education 4 0.3% 7 0.8% Vocational school 0 0.0% 2 0.2% Don’t know 4 0.3% 6 0.7% Reading ability Cannot read at all 1033 81.9% 696 76.7% Able to read only parts of sentence 133 10.5% 99 10.9% Able to read whole sentence 94 7.5% 111 12.2% Blind/visually impaired 1 0.1% 2 0.2% Employment status Unemployed 807 64.0% 347 38.2% House keeping 256 20.3% NA NA Casual labor 81 6.4% 302 33.3% Crop production 148 11.7% 263 29.0% Livestock rearing 135 10.7% 182 20.0% Formally employed 19 1.5% 39 4.3% Petty trade 101 8.0% 105 11.6% Other 58 4.6% 74 8.1%
7.2. Household characteristics and possessions On average, the study found six people live per household (6.6 in Afar, 5.9 in East Hararghe and 5.7 in West Hararghe). The average number of children under the age of 5 years living per household was two (2 in Afar, 1.9 in East Hararghe and 2 in West Hararghe). The majority (88.8%) of surveyed households were male-headed. The percentage of female-headed households ranged from 7.8% in West Hararghe to 13.7% in East Hararghe [Figure 2].
6 Male-headed Female-headed
Total 88.8% 11.2%
West Hararghe 92.2% 7.8%
East Hararghe 86.3% 13.7%
Afar 87.8% 12.2%
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Figure 2: Type of household head of surveyed households in Afar, East Hararghe and West Hararghe, October 2016
The religion for nearly all (94.7%) households was Muslim followed by Orthodox Christian (5.1%). A few (0.2%) of households were Protestants. A third (36.5%) of households had separate kitchens. Slightly lower than half (45.3%) of households had electricity, solar power or generator. The percentage of households having electricity, solar power or generator was lowest in Afar (14%), while the highest was recorded in East Hararghe (57%). Table 4: Place of cooking and percentage of households having electricity, solar power or generator in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n-286] [n=502] [n=473] [n=1261] Count % Count % Count % Count % Place of cooking In a room used for living or sleeping 103 36.0% 98 19.5% 189 40.0% 390 30.9% In a separate room in the same building 9 3.1% 36 7.2% 101 21.4% 146 11.6% used as a kitchen In a separate building used as kitchen 28 9.8% 179 35.7% 107 22.6% 314 24.9% Outdoors 145 50.7% 187 37.3% 56 11.8% 388 30.8% Other 1 .3% 2 .4% 20 4.2% 23 1.8% Households having electricity, solar power or generator Male-headed 34 13.8% 228 63.0% 226 52.6% 488 47.0% Female-headed 6 15.4% 58 41.4% 19 44.2% 83 37.4% Total 40 14.0% 286 57.0% 245 51.8% 571 45.3%
Participation in the Productive Safety Net Program Figure 3 presents the percentage of households participating in the Productive Safety Net Program (PSNP) across the three study areas and by type of household head. As shown in the figure, about three households in every ten (32.4%) were participating in the PSNP during the time of the survey. Participation in the PSNP was found to be relatively higher among female-headed households as compared with male-headed households (39% for female- headed and 31.6% for male-headed).
50.0% 38.5% 40.8% 39.0% 40.0% 31.6% 32.4% 30.0% 21.1% 20.0% 10.0% 0.0% Afar East Hararghe West Hararghe Male-headed HH Female-headed HH Total
Figure 3: Percentage of households participating in the PSNP Program in Afar, East Hararghe and West Hararghe, October 2016
7 Household possessions A quarter (24.7%) of households had radios while only 2.1% of them had television. From the total surveyed households, 26.9% had a mobile or other telephone and 19.7% had a bed/s. As shown in the table below, very few households possess means of transportation and production machineries. Table 5: Household possessions in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n-286] [n=502] [n=473] [n=1261] Count % Count % Count % Count % Household effects Radio 70 24.5% 101 20.1% 140 29.6% 311 24.7% Television 3 1.0% 9 1.8% 15 3.2% 27 2.1% Mobile/other Telephone 84 29.4% 148 29.5% 107 22.6% 339 26.9% Refrigerator 1 0.3% 0 0.0% 7 1.5% 8 0.6% Bed 92 32.2% 70 13.9% 86 18.2% 248 19.7% Watch/Clock 35 12.2% 64 12.7% 80 16.9% 179 14.2% Means of transportation Bicycle 4 1.4% 1 0.2% 7 1.5% 12 1.0% Cart pulled by animal 3 1.0% 3 0.6% 14 3.0% 20 1.6% Motorcycle 5 1.7% 0 0.0% 4 0.8% 9 0.7% Car/Truck 1 0.3% 0 0.0% 3 0.6% 4 0.3% Others Tractor 0 0.0% 0 0.0% 1 0.2% 1 0.1% Small generator (for irrigation) 2 0.7% 8 1.6% 3 0.6% 13 1.0% Sewing Machine 0 0.0% 2 0.4% 3 0.6% 5 0.4% None 120 42.0% 283 56.4% 238 50.3% 641 50.8%
7.3. Food production and consumption 7.3.1. Source of food Food bought from market/shop and self-produced by households were the main source of food for household consumption reported by 71.8% and 66.8% of respondents respectively. Other sources of food for household consumption included: government aid (64.3%), food for work programs (36.5%), and aid from NGOs (32.1%). In Afar, the majority of households consume food bought from market / shop (79.0%) and food received from government aid (73.8%). The main source of food in Oromia was from self-production (77.1% in East Hararghe and 77.4% in West Hararghe), followed by food bought from market / shop (74.9% in East Hararghe and 64.3% in West Hararghe). Table 6: Source of food for household consumption in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total Source of food for household consumption [n-286] [n=502] [n=473] [n=1261] Count % Count % Count % Count % Bought from market/shop 226 79.0% 376 74.9% 304 64.3% 906 71.8% Self-produced by household 89 31.1% 387 77.1% 366 77.4% 842 66.8% Food provided by the government? 211 73.8% 92 18.3% 165 34.9% 468 37.1% Food received in exchange for work 108 37.8% 203 40.4% 149 31.5% 460 36.5% Food provided by NGOs? 135 47.2% 87 17.3% 183 38.7% 405 32.1%
Figure 4 presents the source of food for household consumption by the type of household head. As shown in the figure, more female-headed households depend on foods bought from market/shop for household consumption as compared with male-headed households (80.9% Vs. 70.7%).
8 Male-headed HH [n=1120] 100.0% 80.9% 70.7% Female-headed HH [n=141] 80.0% 67.1% 64.5% 60.0% 36.0% 40.4% 37.6% 36.7% 40.4% 40.0% 31.4% 20.0% 0.0% Self-produced by Bought from Food received in Food provided by Food provided by household market/shop exchange for work NGOs the government
Figure 4: Source of food for household consumption by type of household head in Afar, East Hararghe and West Hararghe, October 2016
7.3.2. Home garden and livestock Home garden Half (49.8%) women had access to land personally managed by them in the past year (49.4% for male-headed households and 53.2% for female-headed). The proportion of women who had access to land was highest in West Hararghe (60.3%) followed by East Hararghe (56.6%), while the lowest was reported in Afar (20.6%). Table 7 presents information on source of land, seeds and resources for growing crops and difficulties in accessing enough water to adequately water the land among those women who had access to land in the past year. Slightly lower than half (45.2%) of women owns the land themselves and 35.8% got the land from the head of the household. Fifty four percent of women grow their own seeds. Access to seeds was found to be limited in Afar, where 39% of women reported that they did not have any seeds this year and only 11.9% of them grow their own seeds. A- quarter (27.1%) of women in Afar received seeds from the Agriculture Bureau free of charge. In East and West Hararghe, 66.2% and 50.5% women use their own seeds respectively. Husbands are the main source of resources such as money, tools and animals to grow crops on the plot of land for 90.1% and 79.6% of women in East Hararghe and West Hararghe respectively. While, in Afar, 45.8% of women use their own resources and 35.6% depend on support from government programs. Respondents were asked how frequently in the past year they encountered difficulties accessing enough water to adequately water their land. The findings showed that a third (35.2%) of women rely on rain and did not water their land at all. A few (17.8%) of women said water is always available while 32.6% of them encounter difficulties accessing enough water 1-2 times per month. Table 7: Source of land personally managed by women and inputs for home gardening in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=59] [n=284] [n=285] [n=628] Count % Count % Count % Count % Type of source (from where or whom women get the land) Rented in (cash) 0 0 16 5.6% 30 10.5% 46 7.3% Allocated by head of household 3 5.1% 134 47.2% 88 30.9% 225 35.8% Sharecropped in 2 3.4% 19 6.7% 9 3.2% 30 4.8% Borrowed (no payment) 0 0 0 0 6 2.1% 6 1.0% Self-owned by respondent 53 89.8% 103 36.3% 128 44.9% 284 45.2% Other 1 1.7% 10 3.5% 24 8.4% 35 5.6% Don’t know 0 0 2 0.7% 0 0 2 0.3% Source of seeds to grow crops NGO (free handout) 0 0.0% 32 11.3% 56 19.6% 88 14.0%
9 Afar East Hararghe West Hararghe Total [n=59] [n=284] [n=285] [n=628] Count % Count % Count % Count % NGO (cost share) 5 8.5% 7 2.5% 28 9.8% 40 6.4% Agricultural bureau (free handout) 16 27.1% 26 9.2% 32 11.2% 74 11.8% Agricultural bureau (subsidy) 4 6.8% 33 11.6% 55 19.3% 92 14.6% Private seed growers 6 10.2% 29 10.2% 45 15.8% 80 12.7% Own seeds (self-grown by respondent) 7 11.9% 188 66.2% 144 50.5% 339 54.0% Other 2 3.4% 23 8.1% 61 21.4% 86 13.7% Didn't have any seeds this year 23 39.0% 5 1.8% 5 1.8% 33 5.3% Source of resources to grow crops Husband 15 25.4% 256 90.1% 227 79.6% 498 79.3% Male relative 12 20.3% 10 3.5% 10 3.5% 32 5.1% Female relative 8 13.6% 7 2.5% 6 2.1% 21 3.3% Land owner 0 0.0% 3 1.1% 1 0.4% 4 0.6% Neighbor 6 10.2% 29 10.2% 60 21.1% 95 15.1% Private company 0 0.0% 7 2.5% 11 3.9% 18 2.9% Government program 21 35.6% 1 0.4% 10 3.5% 32 5.1% Non-governmental organization 1 1.7% 3 1.1% 11 3.9% 15 2.4% Religious organization 0 0.0% 3 1.1% 1 0.4% 4 0.6% Other 3 5.1% 7 2.5% 41 14.4% 51 8.1% Self (respondent) 27 45.8% 18 6.3% 35 12.3% 80 12.7% Frequently of difficulties in accessing enough water to adequately water land in the past year Never (water is always available) 9 15.3% 56 19.7% 47 16.5% 112 17.8% Sometimes (1-2 times per month) 8 13.6% 78 27.5% 119 41.8% 205 32.6% Frequently (once per week 1 1.7% 9 3.2% 19 6.7% 29 4.6% Most of the time (more than once per week) 18 30.5% 27 9.5% 16 5.6% 61 9.7% Don't water the land (rely on rain) 23 39.0% 114 40.1% 84 29.5% 221 35.2%
Grains are the main types of crops grown on plots of land personally managed by women in the past year reported by 77.2% of respondents followed by roots and tubers (29.6%). Twenty percent of women produced Vitamin A- rich plant foods and dark green leafy vegetables on their plots of land in the past year. As shown in table 8 below, the majority of households use foods produced from home gardening for household consumption. Table 8: Types of foods produced and consumed from home gardening in the past year in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=59] [n=284] [n=285] [n=628] Count % Count % Count % Count % Types of foods produced on the land in the past year Grains 46 78.0% 221 77.8% 218 76.5% 485 77.2% Roots or tubers 1 1.7% 106 37.3% 79 27.7% 186 29.6% Pulses/legumes/nuts 5 8.5% 62 21.8% 102 35.8% 169 26.9% Vitamin A-rich plant foods 2 3.4% 67 23.6% 62 21.8% 131 20.9% Dark green leafy vegetables 3 5.1% 66 23.2% 68 23.9% 137 21.8% Other fruits or vegetables 1 1.7% 43 15.1% 52 18.2% 96 15.3% Coffee and/or tea 1 1.7% 42 14.8% 80 28.1% 123 19.6% From foods produced on the land, types of foods consumed by the household Grains 38 82.6% 205 92.8% 179 82.1% 422 87.0% Roots or tubers 1 100% 96 90.6% 54 68.4% 151 81.2% Pulses/legumes/nuts 5 100% 50 80.6% 76 74.5% 131 77.5% Vitamin A-rich plant foods 2 100% 53 79.1% 34 54.8% 89 67.9% Dark green leafy vegetables 1 33.3% 56 84.8% 51 75.0% 108 78.8% Other fruits or vegetables 1 100% 35 81.4% 43 82.7% 79 82.3% Coffee and/or tea 1 100% 37 88.1% 56 70.0% 94 76.4%
10 Husbands/spouses are the final decision makers about the types of foods to be produced on plots of land personally managed by women in 77.1% of households. Similarly, 61.9% of women reported that their husband/spouse is the ultimate decision maker on which of the foods produced from home gardening should be consumed by the family. As shown in table 9, husbands/spouses are the one passing the final decision on which type of foods to be produced on the plot of land across all the three study areas (East Hararghe 74.6%, West Hararghe 79.6% and Afar 76.3%). However, regarding decision making about which foods produced from home gardening should be consumed, women in Afar are more likely to make the final decision (50.8%) as compared with 30.6% in East Hararghe and 20.4% in West Hararghe. Table 9: Ultimate decision maker about the type of foods to be produced and consumed from home gardening in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=59] [n=284] [n=285] [n=628] Count % Count % Count % Count % Ultimate decision maker about the type of foods to be produced Respondent (women) 12 20.3% 27 9.5% 47 16.5% 86 13.7% Husband (spouse) 45 76.3% 212 74.6% 227 79.6% 484 77.1% Other 2 3.4% 45 15.9% 11 4.0% 58 9.3% Ultimate decision maker on which of the foods produced from home gardening should be consumed by the family Respondent (women) 30 50.8% 87 30.6% 58 20.4% 175 27.9% Husband (spouse) 27 45.8% 146 51.4% 216 75.8% 389 61.9% Other 2 3.4% 51 18.0% 11 3.9% 64 10.2%
Livestock Seventy three percent of households own livestock (Afar 85%, East Hararghe 70.9% and West Hararghe 68.1%). The percentage of households owning livestock was 72.6% for male-headed and 76.6% for female-headed households. Goat and sheep are the major types of livestock owned by households in which a household owns an average of 4.7 goat and 2.5 sheep. On average, a household owns 2.3 cattle. The majority of households do not consume their livestock for meat. Only 31.1% of respondents from households owning livestock said their family consumed any of their livestock for meat in the past year. Consumption of livestock for meat was highest in Afar (49.8%), followed by West Hararghe (29.2%), while the lowest was reported in East Hararghe (19.9%). Table 10: Average number of livestock owned by a household by type of animal in Afar, East Hararghe and West Hararghe, October 2016 Type of livestock Afar East Hararghe West Hararghe Total Cattle 4.58 1.52 1.73 2.29 Goat 14.81 1.42 2.04 4.69 Sheep 8.17 0.90 0.70 2.47 Chickens 0.87 1.36 2.05 1.51 Horse 0.01 0.02 0.04 0.03 Donkey 0.61 0.72 0.86 0.75 Mule 0.02 0 0.03 0.02 Camel 1.31 0.09 0.07 0.36
Respondents from households who consumed their livestock for meat in the past year were asked about who makes the final decision in selecting the type of animals and when it should be consumed for meat. The findings showed that husbands/spouses are the final decision makers, mentioned by 74.1% of respondents, while only 18.9% of women said they made the decision.
11 Total 18.9% 74.1% 6.9% West Hararghe 31.9% 60.6% 7.4% East Hararghe 9.9% 74.6% 15.5% Afar 14.0% 84.3% 1.6%
Respondent (women) Husband (spouse) Other Figure 5: Final decision maker about which animals owned by the household should be consumed for meat and when should it be consumed in Afar, East Hararghe and West Hararghe, October 2016
7.3.3. Food preservation and storage Food preservation Eleven percent of households preserved fruits and/or vegetables in the 12 months period preceding the survey. About one household in every five (19.2%) in West Hararghe and 9.4% in East Hararghe preserved fruits and/or vegetables in the past 12 months while only 1.7% households in Afar do so. Respondents from those households that preserved fruits and/or vegetables were asked about the method of preservation used and types of fruits and vegetables preserved. The findings showed that 73.4% of households used sun drying followed by salting (35%) and smoking (30.1%). The major types of fruits and vegetables preserved include; red pepper (34.3%), garlic (28%), tomato (24.5%), onion (23.8%) and pumpkin (23.1%). Table 11: Methods of food preservation used and types of foods preserved by households in the last 12 months in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=5] [n=47] [n=91] [n=143] Count % Count % Count % Count % Methods of food preservation used Sun drying 2 40.0% 26 55.3% 77 84.6% 105 73.4% Other drying 0 0 1 2.1% 8 8.8% 9 6.3% Canning 0 0 0 0 6 6.6% 6 4.2% Salting 0 0 4 8.5% 46 50.5% 50 35.0% Pickling or fermentation 0 0 0 0 9 9.9% 9 6.3% Smoking 0 0 2 4.3% 41 45.1% 43 30.1% Berbere (spice) for preserving meat 0 0 2 4.3% 8 8.8% 10 7.0% Other 3 60.0% 16 34.0% 19 20.9% 38 26.6% Types of fruits and vegetables preserved Pumpkin 0 0 13 27.7% 20 22.0% 33 23.1% Citron 0 0 0 0 8 8.8% 8 5.6% Banana 0 0 1 2.1% 6 6.6% 7 4.9% Kale 0 0 11 23.4% 7 7.7% 18 12.6% Cabbage 0 0 10 21.3% 11 12.1% 21 14.7% Lettuce 0 0 2 4.3% 5 5.5% 7 4.9% Carrot 0 0 6 12.8% 4 4.4% 10 7.0% Tomato 2 40.0% 16 34.0% 17 18.7% 35 24.5% Citrus 0 0 1 2.1% 4 4.4% 5 3.5% Red pepper 1 20.0% 12 25.5% 36 39.6% 49 34.3% Garlic 0 0 9 19.1% 31 34.1% 40 28.0% Onion 1 20.0% 9 19.1% 24 26.4% 34 23.8% Mango 0 0 3 6.4% 2 2.2% 5 3.5% Papaya 0 0 0 0 2 2.2% 2 1.4% Lemon 0 0 2 4.3% 1 1.1% 3 2.1% Orange 0 0 4 8.5% 0 0 4 2.8% Other 3 60.0% 18 38.3% 23 25.3% 44 30.8%
12 Food storage About three households in every ten (27.8%) stored food crops produced by them during the last post-harvest period (Afar 10.8%, East Hararghe 21.5% and 44.8% West Hararghe). Maize was the major type of the stored crop mentioned by 81.8% of respondents, followed by sorghum (65%). The majority of households (93.4%) store crops for household food consumption and 44.7% for use as seeds. Pits are the most common storage methods used by 43% of households, followed by GrainPro bags (36.5%). In-house storage and thatch stores or gunnysacks were used for storing crops by 35.9% and 14.8% of households respectively. Table 12: Types of crops stored, methods of storage and purpose of storing foods by households in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=31] [n=108] [n=212] [n=351] Count % Count % Count % Count % Types of crops stored in the last 12 months Chick pea 2 6.5% 3 2.8% 27 12.7% 32 9.1% Pea 0 0.0% 4 3.7% 24 11.3% 28 8.0% Teff 8 25.8% 5 4.6% 13 6.1% 26 7.4% Sorghum 5 16.1% 77 71.3% 146 68.9% 228 65.0% Flaxseed 0 0.0% 4 3.7% 6 2.8% 10 2.8% Maize 27 87.1% 97 89.8% 163 76.9% 287 81.8% Millet 0 0.0% 0 0.0% 8 3.8% 8 2.3% Wheat 2 6.5% 25 23.1% 27 12.7% 54 15.4% Barely 1 3.2% 14 13.0% 20 9.4% 35 10.0% Bean 2 6.5% 14 13.0% 22 10.4% 38 10.8% Haricot bean 3 9.7% 8 7.4% 15 7.1% 26 7.4% Oats 0 0.0% 5 4.6% 3 1.4% 8 2.3% Lentil 0 0.0% 3 2.8% 8 3.8% 11 3.1% Grass pea 0 0.0% 3 2.8% 0 0.0% 3 0.9% Red pea 0 0.0% 0 0.0% 6 2.8% 6 1.7% Other 3 9.7% 10 9.3% 24 11.3% 37 10.5% Method of storage used Granary 0 0.0% 7 6.5% 27 12.7% 34 9.7% Cribs or metal silos 1 3.2% 0 0.0% 14 6.6% 15 4.3% Sealed/tight containers/plastic drums 0 0.0% 5 4.6% 13 6.1% 18 5.1% Cereal banks 1 3.2% 0 0.0% 13 6.1% 14 4.0% Community storing facilities 0 0.0% 2 1.9% 14 6.6% 16 4.6% Thatch stores or gunny sacks 2 6.5% 2 1.9% 48 22.6% 52 14.8% In-house storage 19 61.3% 57 52.8% 50 23.6% 126 35.9% Storage in pits 0 0.0% 28 25.9% 123 58.0% 151 43.0% Purdue Improved Crop Storage (PICS) 1 3.2% 0 0.0% 6 2.8% 7 2.0% GrainPro bag 13 41.9% 46 42.6% 69 32.5% 128 36.5% Other 2 6.5% 3 2.8% 21 9.9% 26 7.4% Purpose of storing the crop Food for household consumption 31 100% 103 95.4% 194 91.5% 328 93.4% To sell for higher price 1 3.2% 5 4.6% 30 14.2% 36 10.3% Seed for planting 8 25.8% 58 53.7% 91 42.9% 157 44.7% Other 2 6.5% 2 1.9% 26 12.3% 30 8.5%
7.3.4. Income and savings Income Among those women who produced crops on plots of land used for home gardening and managed by them in the past year, 19.9% sold crops they produced (Afar 8.5%, East Hararghe 19.4% and West Hararghe 22.8%). The amount of yearly income earned from the sale of crops was less than 2000 Birr for 65.6% of women and between
13 2000 and 5000 Birr for 12.8% of female respondents. Few (4%) women earned more than 5000 Birr from crops sold. Female respondents were asked what other income sources they have apart from the sale of crops produced on plots of land they personally managed. Accordingly, 23.2% said farming from other land (crop production on land other than that personally managed by women) and 16.3% named the sale of livestock. Half (50.7%) of the female respondents do not have any other income source. The amount of income earned in the past year from other sources was less than 2000 Birr for 61.1% of women and between 2000 and 5000 Birr for 13.7% of female respondents. Table 13: Women’s income from home garden and other sources in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Yearly income from sell of crops [n=5] [n=55] [n=65] [n=125] <2000 ETB 5 100% 35 63.6% 42 64.6% 82 65.6% 2000-5000 0 .0% 8 14.5% 8 12.3% 16 12.8% >5,000 ETB 0 .0% 4 7.3% 1 1.5% 5 4.0% Don’t know 0 .0% 8 14.5% 14 21.5% 22 17.6% Other income sources for women [n=286] [n=502] [n=473] [n=1261] Farming from other land 37 12.9% 83 16.5% 172 36.4% 292 23.2% Remittance 43 15.0% 24 4.8% 28 5.9% 95 7.5% Regular or casual employment 10 3.5% 6 1.2% 14 3.0% 30 2.4% Petty trade 20 7.0% 26 5.2% 65 13.7% 111 8.8% Sale of livestock 91 31.8% 22 4.4% 92 19.5% 205 16.3% Own business 49 17.1% 26 5.2% 45 9.5% 120 9.5% Other 17 5.9% 43 8.6% 87 18.4% 147 11.7% None 119 41.6% 328 65.3% 192 40.6% 639 50.7% Yearly income from other sources [n=167] [n=174] [n=281] [n=622] <2000 ETB 117 70.1% 102 58.6% 161 57.3% 380 61.1% 2000-5000 25 15.0% 22 12.6% 38 13.5% 85 13.7% >5,000 ETB 6 3.6% 12 6.9% 8 2.8% 26 4.2% Don’t know 19 11.4% 38 21.8% 74 26.3% 131 21.1%
Saving Less than a-third (27.9%) of women reported that they personally save money. Fewer women in Afar save money (11.5%) as compared with those in East Hararghe (32.7%) and West Hararghe (32.8%). Those women who personally save money were asked whether they are saving on voluntary or compulsory basis and the vast majority (93.2%) of women said it is voluntarily while 6.5% of them replied the saving is compulsory. Among women who save money, 63.9% save at home, 16.2% at Idir/Iqub2 and 14.8% at a bank. Two-thirds (66.5%) of those women who personally save money practice the saving to use the money for crop/food production and 45.5% save for personal use. Thirty percent of those women who save money managed to save between 1000 to 3000 Birr in the 12 months period preceding the survey and thirty eight percent saved less than 1000 Birr. Only 14.9% of women had ever received training on saving, with the highest percentage reported in West Hararghe (23.7%), followed by East Hararghe (11.4%). Only 6.6% of those women interviewed in Afar had ever received training on saving.
2 Idir/Iqub is a traditional community saving group 14 Table 14: Saving practice of women in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=33] [n=164] [n=155] [n=352] Count % Count % Count % Count % Type of saving Compulsory 0 .0% 6 3.7% 17 11.0% 23 6.5% Voluntary 33 100% 158 96.3% 137 88.4% 328 93.2% Don’t know 0 .0% 0 .0% 1 .6% 1 .3% Place of saving VSLA 0 0.0% 5 3.0% 19 12.3% 24 6.8% Bank 1 3.0% 17 10.4% 34 21.9% 52 14.8% MFIs 0 0.0% 0 0.0% 7 4.5% 7 2.0% RUSSACOs 0 0.0% 4 2.4% 35 22.6% 39 11.1% Idir/Iqub 5 15.2% 19 11.6% 33 21.3% 57 16.2% Informal community group 0 0.0% 4 2.4% 16 10.3% 20 5.7% At home 31 93.9% 123 75.0% 71 45.8% 225 63.9% Other 0 0.0% 6 3.7% 20 12.9% 26 7.4% Purpose of saving Crop/food production 12 36.4% 121 73.8% 101 65.2% 234 66.5% Personal use 25 75.8% 63 38.4% 72 46.5% 160 45.5% Livestock production 6 18.2% 27 16.5% 49 31.6% 82 23.3% Other production 3 9.1% 17 10.4% 59 38.1% 79 22.4% Other 5 15.2% 6 3.7% 27 17.4% 38 10.8% Amount saved in the last 12 months <1000 ETB 11 33.3% 38 23.2% 85 54.8% 134 38.1% 1000 – 3000 ETB 13 39.4% 47 28.7% 46 29.7% 106 30.1% >3000 ETB 3 9.1% 21 12.8% 10 6.5% 34 9.7% Don’t know 6 18.2% 58 35.4% 14 9.0% 78 22.2%
Credit Only 13.2% of women had ever received credit in the past two years, most of them in West Hararghe (19%). The percentage of women who had ever received credit was 9.4% in Afar and 9.8% in East Hararghe. A higher proportion of women from female-headed households had ever received credit (16.3%) as compared with those from male-headed households (12.8%).
30.0%
19.0% 20.0% 16.3% 12.8% 13.2% 9.4% 9.8% 10.0%
0.0% Afar East Hararghe West Hararghe Female-headed HH Male-headed HH Total
Figure 6: Percent of women ever received credit in the past two years in Afar, East Hararghe and West Hararghe, October 2016
7.3.5. Women and Men Dietary Diversity The dietary diversity score (DDS) reflects the probability of micronutrient adequacy of the diet consumed by an individual. The scores are calculated by summing the number of food groups consumed by individual respondents
15 (women and men) over a 24-hour recall period. The scores are created based upon consumption of the following 9 food groups; (1) grains, white roots and tubers, (2) dark green leafy vegetables, (3) other vitamin a-rich fruits and vegetables (4) other vegetables, (5) other fruits (6) meat, poultry and fish, (7) eggs, (8) legumes, nuts and seeds, and (9) dairy. Values are assigned for each food group based on the individual response (value of ‘1’ if the individual consumed at least one food type in the food group, or else ‘0’). Then, the DDS is calculated by adding the number of food groups consumed by an individual giving scores ranging from 0-9. Figure 7 presents the percent of women and men consuming 4 or more food groups over the 24 hour period prior to the survey. As shown in the figure, more than only three women and men in every ten consumed four or more food groups. The percent of individuals consuming four or more food groups was highest in West Hararghe, while the lowest was recorded in Afar. 50.0% Women Men 42.5% 37.8% 40.0% 31.3% 30.4% 30.9% 28.8% 29.5% 30.0% 23.5% 20.8% 20.0% 16.4%
10.0% Percent 0.0% Afar East Hararghe West Hararghe Total Non-fasting individuals Figure 7: Percent of women and men consuming ≥4 food groups in the past 24 hours in Afar, East Hararghe and West Hararghe, October 2016
The average DDS was 3.1 for women and 3.0 for men. Diets during fasting days are more diversified than that consumed in normal days. The average DDS during fasting days was 6.1 for women and 6.9 for men as compared with 2.9 for both women and men during normal days. Across areas, women and men in Afar consume less diversified diet than those in Hararghe. Table 15: Women’s and men’s Diet Diversity Score (DDS) in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Women Men Women Men Women Men Women Men Average DDS by type of day in terms of food consumption Normal day 2.6 2.7 2.8 2.6 3.2 3.3 2.9 2.9 Fasting -- -- 6.6 7.0 3.7 6.0 6.1 6.9 Feasting -- -- 8.0 -- 3.3 2.3 3.6 2.3 Sick 1.5 -- 2.0 -- 3.3 5.0 2.8 5.0 Total 2.6 2.7 3.2 2.9 3.2 3.3 3.1 3.0 Average DDS by type of household head Male-headed 2.6 2.8 3.2 2.9 3.1 3.2 3.0 3.0 Female-headed 2.9 1.3 3.0 2.8 4.8 4.6 3.4 3.3
The average meal frequency per day was 2.7 for women and 2.6 for men. The daily average meal frequency was found to be relatively higher in Afar (2.9 for both women and men), followed by West Hararghe (2.8 for women and 2.7 for men). In East Hararghe, the average meal frequency was 2.4 for women and 2.5 for men.
16 7.4. Household food security situation Household hunger scale The household hunger scale (HHS) estimates household hunger by measuring household food deprivation using three items in the scale. The scale assesses the severity of household food shortage using the following three items; no food to eat of any kind in the household, any household member goes to sleep at night hungry, and any household member go a whole day without eating anything at all. Using a 4 weeks (30 days) recall period the frequency of occurrence for the three items (never, rarely or sometimes, and often) was assessed for each household. A continuous scale score has been tabulated for each household in the sample by summing a household’s responses to the three items where never=0, rarely or sometimes=1, and often=2 (with a minimum possible score of 0 and a maximum possible score of 6). Then, households were categorized based on the score as; “little to no household hunger” (scores of 0-1), “moderate household hunger” (scores of 2-3), and “severe household hunger” (scores of 4-6). One in every three households (33.5%) was categorized as experiencing “moderate hunger” and 2.9% “severe household hunger”. The proportion of households categorized in the “moderate household hunger” score was the highest in West Hararghe (47.8%) while those in the “severe HH hunger” score was the highest in East Hararghe (6.2%). Comparing by type of household head, more proportion of male-headed households were categorized in both moderate and severe household hunger score (34.2% for moderate and 3.1% for sever). From the surveyed female-headed households, 27.7% and 1.4% of them were categorized in the moderate and severe HHS respectively. Table 16: Household hunger Score in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Household hunger Score (total household) [n=286] [n=502] [n=473] [n=1261] “Little to no HH hunger” (scores 0–1) 238 83.2% 322 64.1% 242 51.2% 802 63.6% “Moderate HH hunger” (scores 2–3) 47 16.4% 149 29.7% 226 47.8% 422 33.5% “Severe HH hunger” (scores 4–6) 1 0.3% 31 6.2% 5 1.1% 37 2.9% HHS for Male-headed households [n=251] [n=433] [n=436 [n=1120] “Little to no HH hunger” (scores 0–1) 207 82.5% 279 64.4% 216 49.5% 702 62.7% “Moderate HH hunger” (scores 2–3) 43 17.1% 125 28.9% 215 49.3% 383 34.2% “Severe HH hunger” (scores 4–6) 1 0.4% 29 6.7% 5 1.1% 35 3.1% HHS for Female-headed households [n=35] [n=69] [n=37] [n=141] “Little to no HH hunger” (scores 0–1) 31 88.6% 43 62.3% 26 70.3% 100 70.9% “Moderate HH hunger” (scores 2–3) 4 11.4% 24 34.8% 11 29.7% 39 27.7% “Severe HH hunger” (scores 4–6) 0 0.0% 2 2.9% 0 0.0% 2 1.4%
7.5. Infant and Young Child Feeding Practices (IYCF) Breastfeeding Practices Breastfeeding related data was collected for a total of 990 infants and young children (0-23 months old) and varying age groups taken to calculate the different key indicators as per global recommendations. Out of the total under-two population included in this study, 94.8% were reported to be ever breastfed implying the nearly universal extent of breastfeeding. Yet, universality is not the case when it comes to other indicators of optimum breastfeeding. As displayed in table 17, more than 85% of the mothers of under-two children reported of having initiated breastfeeding within the first one hour of birth without much apparent variation among the three study areas. Similarly, the tradition of discarding colostrum was not a common practice as more than 90% of the mothers gave colostrum to newborns. However, provision of pre-lacteal feeds within the first three days was found to be a common practice with one out of three newborns (born in the past two years) reported of consuming such feeds. Giving pre-lacteal foods appeared to be higher in Afar, where two out of five mothers (40.3%) had practiced it.
17 Table 17: Breastfeeding related practices among women in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Core Indicators Timely initiation of breastfeeding (0-23 months) [n=217] [n=404] [n=369] [n=990] 0-11 months 106 93.0% 166 83.8% 164 90.1% 436 88.3% 12-23 months 87 84.5% 170 82.5% 168 89.8% 425 85.7% Total 193 88.9% 336 83.2% 332 90.0% 861 87.0% Exclusive breastfeeding (0-5 months) [n=57] [n=109] [n=70] [n=236] 0-1 month 13 92.9% 24 68.6% 6 54.5% 43 71.7% 2-3 months 11 47.8% 28 71.8% 17 48.6% 56 57.7% 4-5 months 7 35.0% 12 34.3% 13 54.2% 32 40.5% Total 31 54.4% 64 58.7% 36 51.4% 131 55.5% Continued breastfeeding at 1 year (12-15 months) [n=40] [n=71] [n=72] [n=183] Total 23 57.5% 62 87.3% 66 91.7% 151 82.5% Bottle feeding (0-23 months) [n=216] [n=403] [n=364] [n=983] 0-5 months 2 3.3% 4 3.3% 16 17.4% 22 8.0% 6-11 months 0 0.0% 11 14.5% 27 31.4% 38 17.7% 12-23 months 7 6.9% 23 11.2% 62 33.3% 92 18.7% Total 9 4.2% 38 9.4% 105 28.8% 152 15.5% Additional Indicators Colostrum (0-23 months) 192 95.0% 355 94.4% 320 89.9% 867 92.8% Children ever breastfeed (0-23 months) 202 94.0% 379 93.8% 356 96.5% 937 94.8% Pre-lacteal within 3 days (0-23 months) 81 40.3% 107 28.8% 132 37.3% 320 34.5%
Level of exclusive breastfeeding rate is one key indicator that has shown apparent variation among the study areas and age groups. While nearly three-quarters (71.7%) of all under-1 month infants were exclusively breastfed during the first month, the figure progressively declined to 40.5% among 4-5 month old infants. Although exclusive breastfeeding rate in the first month looked highest in Afar (92.9%), as with the East and West Hararghe responses, the rate declined to 35% around 4-5 months of the infants’ age. It is worth noting that almost a third (30%) in East Hararghe and nearly half (45%) of the neonates (infants under one month of age) in West Hararghe were not exclusively breastfed. Further analysis has illustrated (See Annex 1- foods given to 0-5 month infants) that plain water is the major food type disrupting EBF practice in all study areas followed by cereal based supplementary foods (premature startup) and animals’ milk. Regarding other breastfeeding related indicators, continued breastfeeding rate has shown substantial variation between Afar and Oromia. Though the smaller sample size of young children in the age group 12-15 months (out of which continued breastfeeding rate is calculated) does not allow assessment for significant variation, more than two out of five (42%) of young children in Afar ceased breastfeeding earlier whereas the same indicator stayed above 85% in East and West Hararghe. Bottle feeding practice as a whole did not present as a widespread practice in the study areas, with a cumulative rate of 16%. However, in case of West Hararghe, the apparent higher bottle feeding practice compared with similar rates in the other two study areas (28.8% as compared with 9.4% in East Hararghe and 4.2% in Afar) draws attention. Moreover, bottle-feeding practice in West Hararghe shows progressive increase alongside increasing age from 17.4% among children of age 0-5 months to 33.3% for those aged 12-23 months. Across the different intervention areas, variations in some breastfeeding practices; namely, pre-lacteal feeding, continued breastfeeding and bottle-feeding are demonstrated. Complementary feeding practices The majority (71.3% of women and 73.4% of men) knew complementary food for a child should be introduced at the age of 6 months. As presented in table 18, nearly three-quarters (72.8%) of mothers having 6-8 month old infants reported introducing complementary foods around the recommended time of 6 months, with the rate ranging
18 between 66.7% in East Hararghe to 94.4% in Afar. However, more than a third of all children (36%) were not timely initiated on complementary food. Dietary diversity of complementary foods, which is measured by minimum meal (Diet) diversity (MMD), was met in approximately a-quarter (26.1%) of children aged 6-23 months. The lowest rate was reported in Afar (11.9%) and the highest in West Hararghe (40.5%). A slight rise in dietary diversity was observed among the different age groups across all three study sites with infants between 6-11 months appearing to have the lowest minimum dietary diversity score particularly in Afar and East Hararghe. On the other hand, the recommended meal frequency, as calculated by the minimum meal frequency rate, was relatively higher with nearly 60% of 6-23 months children being fed with the recommended frequency in the last 24 hours. The rate was found to be the highest in West Hararghe (76.5%) and lowest in East Hararghe (44.8%). Further analysis of food types consumed among 6-8 months old infants (See annex 2 - food types consumed among 6-8 months old infants) has shown that cereal based complementary foods were widely consumed in all study areas (73%) whereas consumption of vegetables and animal source foods was quite insignificant in Afar and East Hararghe. Table 18: Complementary feeding related practices among women in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Timely complementary feeding (6-9 months) [n=25] [n=51] [n=48] [n=124] Total 18 72.0% 33 64.7% 28 58.3% 79 63.7% Introduction of solid, semi-solid or soft foods (6-8 months) [n=18] [n=39] [n=35] [n=92] Total 17 94.4% 26 66.7% 24 68.6% 67 72.8% Minimum dietary diversity (6-23 months) [n=126] [n=242] [n=210] [n=578] 6-11 months 4 9.3% 5 8.5% 24 34.8% 33 19.3% 12-17 months 4 8.0% 26 24.1% 38 41.3% 68 27.2% 18-23 months 7 21.2% 20 26.7% 23 46.9% 50 31.8% Total 15 11.9% 51 21.1% 85 40.5% 151 26.1% Minimum meal frequency (6-23 months) [n=103] [n=212] [n=166] [n=481] 6-11 months 24 63.2% 27 54.0% 43 75.4% 94 64.8% 12-17 months 16 42.1% 36 37.9% 53 75.7% 105 51.7% 18-23 months 16 59.3% 32 47.8% 31 79.5% 79 59.4% Total 56 54.4% 95 44.8% 127 76.5% 278 57.8% Minimum acceptable diet (6-23 months) [n=103] [n=212] [n=166] [n=481] 6-11 months 3 7.9% 4 8.0% 20 35.1% 27 18.6% 12-17 months 2 5.3% 15 15.8% 23 32.9% 40 19.7% 18-23 months 4 14.8% 11 16.4% 15 38.5% 30 22.6% Total 9 8.7% 30 14.2% 58 34.9% 97 20.2% Consumption of iron-rich/iron-fortified foods (6-23 months) [n=103] [n=212] [n=166] [n=481] 6-11 months 7 18.4% 7 14.0% 22 38.6% 36 24.8% 12-17 months 7 18.4% 26 27.4% 31 44.3% 64 31.5% 18-23 months 6 22.2% 19 28.4% 23 59.0% 48 36.1% Total 20 19.4% 52 24.5% 76 45.8% 148 30.8%
The minimum acceptable diet, which accounts both for practices of optimal diversity and frequency stood at 20.2%, showing that nearly four out of five children did not consume complementary food according to the recommended diversity and frequency. This indicator stood as low as 8.7% and 14.2% in Afar and East Hararghe respectively, and at 34.9% in West Hararghe. Consumption of iron rich foods such as dark green vegetables and organ meat was also the highest in West Hararghe (45.8%) while it is the lowest in Afar (19.4%), with an overall average of 30.8%. Overall, the practice of timely initiation and introduction of complementary feeding in the study areas can be considered good, but the proportion of children getting the recommended minimum dietary diversity and minimum
19 acceptable diet was found to be very low. Only a-quarter of young children were fulfilling the optimal feeding recommendations for minimum dietary diversity and one in every five of them got the minimum acceptable diet. Moreover, less than a third of young children were fulfilling the optimal feeding recommendations for consumption of iron rich (iron-fortified foods). It also appears that, complementary feeding related indicators are relatively better in West Hararghe compared to levels in Afar and East Hararghe.
7.6. Child’s Health Diarrhea Overall, 15.2% of children under the age of 5 years experienced diarrhea in the 2-week period prior to the survey. The highest diarrhea prevalence was recorded in West Hararghe (19.9%) and among children of age 12- 17 months (20.8%). Findings from this study revealed the prevailing poor practice regarding feeding of a child during diarrheal illness. More than half of mothers/caretakers said they gave less amount of breast milk, fluids and foods as compared to the amount the child usually consumes the last time s/he had diarrhea. Table 19: Diarrhea prevalence and feeding practice during illness in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % 2 weeks diarrhea prevalence [n=286] [n=502] [n=473] [n=1261] 0-5 months 4 6.6% 12 9.8% 11 12.0% 27 9.8% 6-11 months 7 13.2% 14 18.4% 15 16.7% 36 16.4% 12-17 months 8 13.3% 26 22.0% 25 23.8% 59 20.8% 18-23 months 3 7.0% 6 6.8% 21 25.6% 30 14.1% 24-59 months 6 8.7% 12 12.2% 22 21.2% 40 14.8% Total 28 9.8% 70 13.9% 94 19.9% 192 15.2% Breast feeding during diarrhea [n=17] [n=56] [n=70] [n=143] Less than usual 7 41.2% 29 51.8% 44 62.9% 80 55.9% About the same 7 41.2% 10 17.9% 22 31.4% 39 27.3% More than usual 2 11.8% 10 17.9% 1 1.4% 13 9.1% Nothing to drink/eat 0 0 2 3.6% 2 2.9% 4 2.8% Not breastfeeding 0 0 2 3.6% 0 0 2 1.4% Don't know 1 5.9% 3 5.4% 1 1.4% 5 3.5% Fluids given during diarrhea [n=23] [n=57] [n=88] [n=168] Less than usual 7 30.4% 29 50.9% 59 67.0% 95 56.5% About the same 12 52.2% 10 17.5% 21 23.9% 43 25.6% More than usual 2 8.7% 13 22.8% 4 4.5% 19 11.3% Nothing to drink/eat 2 8.7% 3 5.3% 3 3.4% 8 4.8% Don't know 0 0 2 3.5% 1 1.1% 3 1.8% Foods given during diarrhea [n=23] [n=57] [n=88] [n=168] Less than usual 7 30.4% 30 52.6% 53 60.2% 90 53.6% About the same 10 43.5% 10 17.5% 26 29.5% 46 27.4% More than usual 3 13.0% 9 15.8% 4 4.5% 16 9.5% Nothing to drink/eat 2 8.7% 7 12.3% 5 5.7% 14 8.3% Don't know 1 4.3% 1 1.8% 0 0 2 1.2%
Sixty three percent of mothers/caregivers sought treatment for the diarrhea (67.9% in Afar, 67.1% in East Hararghe and 58.5% West Hararghe). Regarding service providers where care was first sought for treatment of diarrhea, the majority (60.3%) sought care from health professionals. Slightly higher than half (53.1%) of children had received ORS and 39.6% of them were given Zinc during the diarrhea episode.
20 Table 20: Care seeking during diarrhea in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Service provider where care was first [n=19] [n=47] [n=55] [n=121] sought for treatment of diarrhea Health professional 15 78.9% 23 48.9% 35 63.6% 73 60.3% Traditional healer 1 5.3% 3 6.4% 2 3.6% 6 5.0% Health extension worker 0 0 16 34.0% 12 21.8% 28 23.1% Village health workers 0 0 1 2.1% 5 9.1% 6 5.0% Mother 0 0 1 2.1% 0 0 1 .8% Husband/partner 0 0 3 6.4% 1 1.8% 4 3.3% Other 3 15.8% 0 0 0 0 3 2.5% Children who received the following [n=28] [n=70] [n=94] [n=192] during diarrhea A fluid made from an ORS packet 11 39.3% 34 48.6% 57 60.6% 102 53.1% Zinc 9 32.1% 20 28.6% 47 50.0% 76 39.6% A homemade sugar and salt solution 14 50.0% 22 31.4% 36 38.3% 72 37.5% Other homemade fluid 11 39.3% 26 37.1% 49 52.1% 86 44.8%
Growth monitoring and treatment for malnutrition Only 16.7% of children had ever had their growth monitored, of which 47.9% got the service in the past one month prior to the survey. Around fifteen percent of children had ever received treatment for malnutrition. Among them, half (50.8%) got treatment for malnutrition from government health posts and 22.2% from government health centers. The majority (72.7%) of mothers/caretakers traveled on foot to seek treatment for malnutrition in their child, with an average walking time of 1.2 hours. Table 21: Growth monitoring and treatment for malnutrition in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Children taken for weighing (growth [n=286] [n=502] [n=473] [n=1261] monitoring) Total 36 12.6% 82 16.3% 93 19.7% 211 16.7% Place taken for weighing (growth 100.0 36 82 100.0% 93 100.0% 211 100.0% monitoring) % The past month 6 16.7% 39 47.6% 56 60.2% 101 47.9% 1-3 months ago 8 22.2% 20 24.4% 23 24.7% 51 24.2% > 3 months ago 10 27.8% 15 18.3% 8 8.6% 33 15.6% Don’t know 12 33.3% 8 9.8% 6 6.5% 26 12.3% Children received treatment for [n=286] [n=502] [n=473] [n=1261] malnutrition Total 34 11.9% 54 10.8% 97 20.5% 185 14.7% Source of treatment for malnutrition [n=34] [n=54] [n=97] [n=185] Religious healer 0 .0% 2 3.7% 5 5.2% 7 3.8% Traditional healer 2 5.9% 1 1.9% 3 3.1% 6 3.2% At government hospital 0 .0% 5 9.3% 14 14.4% 19 10.3% At government health center 16 47.1% 7 13.0% 18 18.6% 41 22.2% At government health post 15 44.1% 35 64.8% 44 45.4% 94 50.8% Other government sectors 1 2.9% 1 1.9% 1 1.0% 3 1.6% At private hospital/clinic 0 .0% 1 1.9% 3 3.1% 4 2.2% Other private medical sector 0 .0% 2 3.7% 2 2.1% 4 2.2% At home 0 .0% 0 .0% 4 4.1% 4 2.2% Nowhere (no treatment) 0 .0% 0 .0% 0 .0% 0 .0% Other 0 .0% 0 .0% 1 1.0% 1 .5% Don't know 0 .0% 0 .0% 2 2.1% 2 1.1% Transport to travel to health facility to seek [n=32] [n=51] [n=82] [n=165] treatment for malnutrition On foot (walking) 21 65.6% 45 88.2% 54 65.9% 120 72.7%
21
Preference on service providers to seek care for malnourished child Mothers/caregivers and fathers of a child under 5 years of age were asked about the service providers they prefer to seek treatment from if their child becomes malnourished. The findings showed that government health posts are the most preferred service providers mentioned by 55.1% of mothers/caregivers (women) and 52.5% of fathers (men). One respondent in every five (22.8% for mothers/caregivers and 23.7% for fathers) chooses government health centers to seek treatment for malnourished children. These service providers are the two most preferred places to seek treatment from across all the three study areas, although government health centers are the first choice and health posts ranks second in Afar. Table 22: Preference on service providers to seek care from if child becomes malnourished in the future in Afar, East Hararghe and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total
Count % Count % Count % Count % Service providers preferred by WOMEN [n=286] [n=502] [n=473] [n=1261] Religious healer 0 0 5 1.0% 17 3.6% 22 1.7% Traditional healer 4 1.4% 4 .8% 11 2.3% 19 1.5% At government hospital 2 .7% 38 7.6% 43 9.1% 83 6.6% At government health center 115 40.2% 64 12.7% 108 22.8% 287 22.8% At government health post 145 50.7% 344 68.5% 206 43.6% 695 55.1% Other government sectors 5 1.7% 5 1.0% 8 1.7% 18 1.4% At private hospital/clinic 1 .3% 2 .4% 14 3.0% 17 1.3% Other private medical sector 0 0 2 .4% 3 .6% 5 .4% At home 0 0 10 2.0% 13 2.7% 23 1.8% Nowhere (no treatment) 1 .3% 3 .6% 5 1.1% 9 .7% Other 1 .3% 3 .6% 13 2.7% 17 1.3% Don't know 12 4.2% 22 4.4% 32 6.8% 66 5.2% Service providers preferred by MEN [n=164] [n=356] [n=372] [n=892] Religious healer 1 .6% 7 2.0% 15 4.0% 23 2.6% Traditional healer 2 1.2% 1 .3% 10 2.7% 13 1.5% At government hospital 1 .6% 31 8.7% 33 8.9% 65 7.3% At government health center 79 48.2% 44 12.4% 88 23.7% 211 23.7% At government health post 60 36.6% 244 68.5% 164 44.1% 468 52.5% Other government sectors 5 3.0% 5 1.4% 3 .8% 13 1.5% At private hospital/clinic 0 .0% 2 .6% 11 3.0% 13 1.5% Other private medical sector 1 .6% 2 .6% 3 .8% 6 .7% At home 0 0 6 1.7% 11 3.0% 17 1.9% Nowhere (no treatment) 0 0 2 .6% 4 1.1% 6 .7% Other 1 .6% 2 .6% 15 4.0% 18 2.0% Don't know 14 8.5% 10 2.8% 15 4.0% 39 4.4%
7.7. Nutritional status of children and women 7.7.1. Acute malnutrition (Weight-for-height) Anthropometric measurements of weight and height were conducted among 950 children aged 6-59 months to assess the level of acute and chronic malnutrition by calculating three indices - height/length for age, weight-for- height and weight-for-age. As shown table 23, Global Acute Malnutrition (GAM) rate, children age 6-59 months who fall below the <-2 z- score, was found to be 13.5%, with the highest rate recorded in Afar (23%) and the lowest in West Hararghe (10.2%). Moderate and severe acute malnutrition are also shown to be the highest in Afar, where the rates are 15.2% and 7.9% respectively. Distribution of all types of acute malnutrition is consistently shown to be higher among boys than girls across all study areas. Variation among boys and girls, however, appeared to be substantially higher in East Hararghe (e.g. 14.4% among males vs. 6% among females for GAM) for the different
22 levels of acute malnutrition. Across age groups, global acute malnutrition rate appeared to be higher among children 6-11 months age in all the study areas. Table 23: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016 All Boys Girls n = Afar=178; East Hararghe=277; n = Afar=98; East Hararghe=160; n = Afar=80; East Hararghe=117; West Hararghe=303;Total =758 West Hararghe=177; Total=435 West Hararghe=126; Total=323 Prevalence of global malnutrition (<-2 z-score and/or oedema) (41) 23.0 % (25) 25.5 % (16) 20.0 % Afar (17.5 - 29.7 95% C.I.) (17.9 - 35.0 95% C.I.) (12.7 - 30.0 95% C.I.) (30) 10.8 % (23) 14.4 % (7) 6.0 % East Hararghe (7.7 - 15.0 95% C.I.) (9.8 - 20.6 95% C.I.) (2.9 - 11.8 95% C.I.) (31) 10.2 % (23) 13.0 % (8) 6.3 % West Hararghe (7.3 - 14.2 95% C.I.) (8.8 - 18.7 95% C.I.) (3.3 - 12.0 95% C.I.) (102) 13.5 % (71) 16.3 % (31) 9.6 % Total (4.3 - 35.2 95% C.I.) (6.7 - 34.5 95% C.I.) (1.5 - 41.9 95% C.I.) Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema) (27) 15.2 % (17) 17.3 % (10) 12.5 % Afar (10.6 - 21.2 95% C.I.) (11.1 - 26.0 95% C.I.) (6.9 - 21.5 95% C.I.) (17) 6.1 % (13) 8.1 % (4) 3.4 % East Hararghe (3.9 - 9.6 95% C.I.) (4.8 - 13.4 95% C.I.) (1.3 - 8.5 95% C.I.) (18) 5.9 % (12) 6.8 % (6) 4.8 % West Hararghe (3.8 - 9.2 95% C.I.) (3.9 - 11.5 95% C.I.) (2.2 - 10.0 95% C.I.) (62) 8.2 % (42) 9.7 % (20) 6.2 % Total (2.1 - 26.8 95% C.I.) (2.8 - 28.3 95% C.I.) (1.1 - 27.7 95% C.I.) Prevalence of severe malnutrition (<-3 z-score and/or oedema) (14) 7.9 % (8) 8.2 % (6) 7.5 % Afar (4.7 - 12.8 95% C.I.) (4.2 - 15.3 95% C.I.) (3.5 - 15.4 95% C.I.) (13) 4.7 % (10) 6.3 % (3) 2.6 % East Hararghe (2.8 - 7.9 95% C.I.) (3.4 - 11.1 95% C.I.) (0.9 - 7.3 95% C.I.) (13) 4.3 % (11) 6.2 % (2) 1.6 % West Hararghe (2.5 - 7.2 95% C.I.) (3.5 - 10.8 95% C.I.) (0.4 - 5.6 95% C.I.) (40) 5.3 % (29) 6.7 % (11) 3.4 % Total (2.5 - 11.0 95% C.I.) (4.8 - 9.2 95% C.I.) (0.5 - 21.4 95% C.I.)
Table 24: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016 Total Severe wasting (<-3 z-score) Moderate wasting (>= -3 and <-2 z-score )
no. No. % No. % Afar 6-11 months 30 5 16.7 4 13.3 12-17 months 44 3 6.8 7 15.9 18-23 months 40 3 7.5 4 10.0 24-59 months 64 3 4.7 12 18.8 East Hararghe 6-11 months 24 2 8.3 3 12.5 12-17 months 89 3 3.4 3 3.4 18-23 months 72 1 1.4 2 2.8 24-59 months 92 7 7.6 9 9.8 West Hararghe 6-11 months 61 4 6.6 6 9.8 12-17 months 86 4 4.7 6 7.0 18-23 months 59 3 5.1 3 5.1 24-59 months 97 2 2.1 3 3.1 Total 6-11 months 115 11 9.6 13 11.3 12-17 months 219 10 4.6 16 7.3
23 Total Severe wasting (<-3 z-score) Moderate wasting (>= -3 and <-2 z-score )
no. No. % No. % 18-23 months 171 7 4.1 9 5.3 24-59 months 253 12 4.7 24 9.5
7.7.2. Stunting (Height-for-age) Table 25 shows the prevalence of chronic malnutrition in the studied areas. The overall prevalence of stunting, which measures the level of chronic malnutrition by labeling height/length-for-age index below -2 z-score using the WHO 2006 reference chart as stunted, was 39.1%. Values ranged between 32.2% in West Hararghe to 49.3% in East Hararghe. Boys were more affected than girls across all study areas and different levels of stunting. Higher proportion of under-five children was also found to be severely stunted in East Hararghe compared with the other two study areas. Stunting prevalence was higher among 18-23 months old children in Afar, whereas stunting affected those within 12-17 months age group in East Hararghe and those older than 24 months in West Hararghe. Table 25: Prevalence of stunting based on height-for-age z-scores and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016
All Boys Girls n = Afar =78; East Hararghe n = Afar =175; East Hararghe =286; n = Afar =97; East Hararghe =163; =123; West Hararghe =131; Total West Hararghe =326; Total =787 West Hararghe =195; Total =455 =332 Prevalence of stunting (<-2 z-score) (62) 35.4 % (41) 42.3 % (21) 26.9 % Afar (28.7 - 42.8 95% C.I.) (32.9 - 52.2 95% C.I.) (18.3 - 37.7 95% C.I.) (141) 49.3 % (88) 54.0 % (53) 43.1 % East Hararghe (43.6 - 55.1 95% C.I.) (46.3 - 61.5 95% C.I.) (34.7 - 51.9 95% C.I.) (105) 32.2 % (66) 33.8 % (39) 29.8 % West Hararghe (27.4 - 37.5 95% C.I.) (27.6 - 40.7 95% C.I.) (22.6 - 38.1 95% C.I.) (308) 39.1 % (195) 42.9 % (113) 34.0 % Total (18.4 - 64.8 95% C.I.) (18.5 - 71.2 95% C.I.) (16.4 - 57.5 95% C.I.) Prevalence of moderate stunting (<-2 z-score and >=-3 z-score) (32) 18.3 % (23) 23.7 % (9) 11.5 % Afar (13.3 - 24.7 95% C.I.) (16.4 - 33.1 95% C.I.) (6.2 - 20.5 95% C.I.) (51) 17.8 % (33) 20.2 % (18) 14.6 % East Hararghe (13.8 - 22.7 95% C.I.) (14.8 - 27.1 95% C.I.) (9.5 - 21.9 95% C.I.) (46) 14.1 % (27) 13.8 % (19) 14.5 % West Hararghe (10.7 - 18.3 95% C.I.) (9.7 - 19.4 95% C.I.) (9.5 - 21.5 95% C.I.) (129) 16.4 % (83) 18.2 % (46) 13.9 % Total (11.2 - 23.4 95% C.I.) (8.9 - 33.7 95% C.I.) (10.7 - 17.8 95% C.I.) Prevalence of severe stunting (<-3 z-score) (30) 17.1 % (18) 18.6 % (12) 15.4 % Afar (12.3 - 23.4 95% C.I.) (12.1 - 27.4 95% C.I.) (9.0 - 25.0 95% C.I.) (90) 31.5 % (55) 33.7 % (35) 28.5 % East Hararghe (26.4 - 37.1 95% C.I.) (26.9 - 41.3 95% C.I.) (21.2 - 37.0 95% C.I.) (59) 18.1 % (39) 20.0 % (20) 15.3 % West Hararghe (14.3 - 22.6 95% C.I.) (15.0 - 26.2 95% C.I.) (10.1 - 22.4 95% C.I.) (179) 22.7 % (112) 24.6 % (67) 20.2 % Total (8.3 - 48.8 95% C.I.) (9.4 - 50.7 95% C.I.) (6.8 - 46.7 95% C.I.)
Table 26: Prevalence of stunting based on height-for-age z-scores and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016 Total Severe stunting (<-3 z-score) Moderate stunting (>= -3 and <-2 z-score )
no. No. % No. % Afar 6-11 months 29 0 0.0 2 6.9
24 Total Severe stunting Moderate stunting (>= -3 and <-2 z-score ) (<-3 z-score) no. No. % No. % 12-17 months 45 5 11.1 10 22.2 18-23 months 39 14 35.9 9 23.1 24-59 months 62 11 17.7 11 17.7 East Hararghe 6-11 months 26 0 0.0 2 7.7 12-17 months 89 35 39.3 17 19.1 18-23 months 76 31 40.8 12 15.8 24-59 months 95 24 25.3 20 21.1 West Hararghe 6-11 months 63 1 1.6 2 3.2 12-17 months 92 13 14.1 13 14.1 18-23 months 71 19 26.8 7 9.9 24-59 months 100 26 26.0 24 24.0 Total 6-11 months 118 1 0.8 6 5.1 12-17 months 226 53 23.5 40 17.7 18-23 months 186 64 34.4 28 15.1 24-59 months 257 61 23.7 55 21.4
7.7.3. Underweight (Weight-for-age) Underweight prevalence, which is measured by a composite index of weight for height and does not differentiate between acute and chronic malnutrition, was found to affect one out of five children among the whole study population. Its prevalence was significantly higher in Afar and like the other indicators; it tends to be more common among boys (see annex 3). 7.7.4. Nutritional status of women (MUAC) MUAC measurements were taken from 1236 women of reproductive age (15-49 years). The prevalence of acute malnutrition among women aged 15-49 years (MUAC less than 230 mm) was 24.8%, with the highest prevalence recorded among currently pregnant women (34.5%). The prevalence was 24.7% among currently pregnant and/or lactating women. Across study areas, women in Afar are most affected with a prevalence of 41.3%. Table 27: Prevalence of acute malnutrition among women of reproductive age (MUAC <230mm) in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total Prevalence of acute malnutrition [n=286] [n=492] [n=458] [n=1236] (<230mm) Count % Count % Count % Count % Pregnant 19 59.4% 8 26.7% 14 24.6% 41 34.5% Not pregnant but lactating 68 40.0% 83 22.1% 54 17.0% 205 23.7% Pregnant and lactating 3 100% 1 6.7% 5 15.2% 9 17.6% Not Pregnant and not lactating 24 34.8% 11 15.5% 12 24.0% 47 24.7% Not sure / refused to answer 4 33.3% 0 0.0% 0 0.0% 4 33.3% Total pregnant and/or lactating 90 43.9% 92 21.9% 73 17.9% 255 24.7% Total women age 15-49 years 118 41.3% 103 20.9% 85 18.6% 306 24.8%
7.8. Water, Sanitation and Hygiene Water In the study areas, access to safe drinking water was found to be very limited. Only 30% of the households use water from improved sources, with the lowest recorded in Afar (15.4%). Among households that do not use rainwater collection as a primary source of drinking water, 22.2% occasionally use drinking water collected through rain water harvesting (Afar 31.6%, East Hararghe 10.4% and West Hararghe 28.5%).
25 Adult women age 15 years and above are responsible for collecting water in 81.8% households. This finding shows the high work burden on women in addition to other household chores as only 30.6% of households have access to water supply within 30 minutes or less. Table 28: Access to safe water supply in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=286] [n=492] [n=458] [n=1236] Count % Count % Count % Count % Primary source of water for drinking Improved water source 44 15.4% 194 38.6% 140 29.6% 378 30.0% Unimproved water source 240 83.9% 231 46.0% 222 46.9% 693 55.0% Rainwater collection 1 .3% 40 8.0% 38 8.0% 79 6.3% Other 1 .3% 33 6.6% 63 13.3% 97 7.7% Don’t know 0 0 4 .8% 10 2.1% 14 1.1% Time to obtain drinking water (round trip) Less than 30 minutes 50 17.5% 134 26.7% 202 42.7% 386 30.6% 30 minutes to less than 1 hour 49 17.1% 174 34.7% 73 15.4% 296 23.5% 1 hour to less than 2 hours 28 9.8% 157 31.3% 97 20.5% 282 22.4% 2 hour to less than 8 hours 66 23.1% 23 4.6% 71 15.0% 160 12.7% 8 hours or longer 79 27.6% 7 1.4% 22 4.7% 108 8.6% Don't know 14 4.9% 7 1.4% 8 1.7% 29 2.3% Person who usually collects water Female adult 181 63.3% 463 92.2% 387 81.8% 1031 81.8% Male adult 75 26.2% 20 4.0% 48 10.1% 143 11.3% Female child (less than 15 years of age) 12 4.2% 15 3.0% 33 7.0% 60 4.8% Male child (less than 15 years of age) 2 .7% 4 .8% 2 .4% 8 .6% Don’t know 16 5.6% 0 .0% 3 .6% 19 1.5%
Water treatment prior to consumption is important in minimizing the risk of water related illness, especially in areas where access to improved water sources is limited. Although the majority of households use drinking water from unimproved sources, two households in every five (44.1%) do not treat the water at household level. Filtration through cloth, boiling and chlorination were the major water treatment methods used by 20.1%, 18.2% and 16.8% of households respectively.
Table 29: Household water treatment practices in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total Methods usually used at household level to [n=286] [n=492] [n=458] [n=1236] make the water safer to drink Count % Count % Count % Count % Boil water 35 12.2% 85 16.9% 109 23.0% 229 18.2% Add bleach/chlorine 76 26.6% 54 10.8% 82 17.3% 212 16.8% Strain it through a cloth 27 9.4% 126 25.1% 100 21.1% 253 20.1% Use water filter 1 0.3% 14 2.8% 37 7.8% 52 4.1% Solar disinfection 0 0.0% 12 2.4% 37 7.8% 49 3.9% Let it stand and settle 29 10.1% 39 7.8% 57 12.1% 125 9.9% Use purifying tablets 51 17.8% 38 7.6% 25 5.3% 114 9.0% Other 50 17.5% 8 1.6% 50 10.6% 108 8.6% Do not treat water at all 111 38.8% 223 44.4% 222 46.9% 556 44.1% Don’t know 0 .0% 5 1.0% 5 1.1% 10 .8%
Sanitation and Hygiene Only 32.2% of households have a specific hand washing facility. Of which, 8.9% and 5.6% of the facilities are located within 10 paces of toilet facilities and kitchens respectively. Overall, 63.9% of households do not have hand-washing facilities, with the highest in Afar (86.7%).
26 Table 30: Availability of hand washing station at households in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=286] [n=492] [n=458] [n=1236] Count % Count % Count % Count % Availability of hand washing station and its location Within 10 paces of the toilet facility 2 .7% 48 9.6% 62 13.1% 112 8.9% Within 10 paces of the kitchen 1 .3% 14 2.8% 55 11.6% 70 5.6% Elsewhere in home or yard 8 2.8% 56 11.2% 75 15.9% 139 11.0% Outside yard 16 5.6% 43 8.6% 26 5.5% 85 6.7% No specific place 248 86.7% 331 65.9% 227 48.0% 806 63.9% No permission to see 11 3.8% 10 2.0% 28 5.9% 49 3.9% From the available hand washing stations those having: Water 3 11.1% 65 40.4% 72 33.0% 140 34.5% Soap, detergent or local cleansing agent 4 14.8% 42 26.1% 53 24.3% 99 24.4%
Availability of water and soap/substitute at hand washing facilities was assessed. Only 34.5% of the hand washing facilities had water during the time of visit, indicating family members do not always use the facilities. Soap, detergent or local cleansing agent was found near only 24.4% of the facilities (Figure 8).
50.0% 40.4% Afar East Hararghe West Hararghe Total 40.0% 33.0% 34.5%
30.0% 26.1% 24.3% 24.4%
20.0% 14.8% 11.1% 10.0%
0.0% Water Soap, detergent or local cleansing agent
Figure 8: Percent of hand washing station with water and soap/substitute in Afar and East and West Hararghe, October 2016 Only 13.8% of households use improved toilet facilities that are not shared with other households. Few (6.7%) households use toilet facilities that would be considered improved if they were not shared with other households. The most common toilet facilities in the study areas are unimproved types used by 45.2% of households. Thirteen percent of the toilet facilities are used by more than one household with an average of 4 households using one facility (8 in Afar, 5 in East Hararghe and 4 in West Hararghe). Half (51.5%) of the surveyed households either do not have toilet facilities or family members use open defecation, with the highest in Afar (92%). Women/caregivers were asked what was done to dispose the child’s stool the last time s/he passed stool. As presented in table 31 below, the stool for 47.4% of children were disposed in safe ways (33.2% put into toilets, 8.4% buried and 5.8% children used toilets). The stool for 19.6% and 15% of children was left in the open and thrown into garbage respectively.
27 Table 31: Access to latrine facilities and excreta disposal practices in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=286] [n=492] [n=458] [n=1236] Count % Count % Count % Count % Type of toilet facility used by households Improved facility 5 1.7% 167 33.3% 87 18.4% 259 20.5% Not shared 4 1.4% 126 25.1% 44 9.3% 174 13.8% Shared 1 0.3% 41 8.2% 43 9.1% 85 6.7% Unimproved facility 49 17.1% 261 52.0% 260 55.0% 570 45.2% Not shared 42 14.7% 233 46.4% 216 45.7% 491 38.9% Shared 7 2.4% 28 5.6% 44 9.3% 79 6.3% No facility or open defecation 263 92.0% 158 31.5% 228 48.2% 649 51.5% Methods used to dispose stool the last time child passed stool Child used toilet/latrine 2 0.7% 37 7.4% 34 7.2% 73 5.8% Put/rinsed into toilet or latrine 10 3.5% 240 47.8% 169 35.7% 419 33.2% Put/rinsed into drain or ditch 0 0 9 1.8% 12 2.5% 21 1.7% Thrown into garbage 90 31.5% 48 9.6% 51 10.8% 189 15.0% Buried 25 8.7% 48 9.6% 33 7.0% 106 8.4% Left in the open 67 23.4% 84 16.7% 96 20.3% 247 19.6% Other 44 15.4% 22 4.4% 44 9.3% 110 8.7% Don't know 48 16.8% 14 2.8% 34 7.2% 96 7.6%
7.9. Gender 7.9.1. Public engagement Sixty percent of women and 51.8% of men do not participate in any local committee. The most common types of committees women and men were participating in include; religious groups (13.9% for women and 18.6% for men), village leadership councils (10.3% for women and 14.0% for men), and mother to mother/father to father groups (12.5% for women and 14.3% for men). Table 32: Women and men participation in local committees in Afar and East and West Hararghe, October 2016 Women [n=1261] Men [n=908] Participation in local committees Count % Count % Savings or microfinance groups 40 3.2% 34 3.7% Religious group 175 13.9% 169 18.6% Water management committee 72 5.7% 67 7.4% Natural resource management 70 5.6% 79 8.7% RUSACCO 65 5.2% 72 7.9% VSLA 75 5.9% 71 7.8% Village leadership council 130 10.3% 127 14.0% Mother 2 Mother / Father 2 Father Group 158 12.5% 130 14.3% Women’s / Men’s Development Army 42 3.3% 38 4.2% None 756 60.0% 470 51.8%
Figure 9 presents the opinions of respondents about the participation of women and men in community water supply issues. As shown in the figure, expressing their opinions and participating in decision making about community water supply was found to be low among women as compared with their men counterparts. Around forty percent (35.9%) of women reported that there is a community water supply in their area, of which 68.9% of them said women speak up and voice their opinions about community water supply in public. Slightly more than half (54.1%) of women said women make decisions about plumbing, finance and maintenance of community water supply. From the total men respondents, 41.3% of them confirmed about the availability of community water supply in their area. Among these, 80.5% and 64% said men speak up and voice their opinions about community water supply in public and men make decisions about plumbing, finance and maintenance of community water supply.
28 Men Women and men make decisions about the 64.0% Women community water supply 54.1%
Women and men voice their opinions about the 80.5% community water supply in public 68.9%
0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
Figure 9: Opinion about the level of women and men participation in water committees in Afar and East and West Hararghe, October 2016
7.9.2. Attitudes and perceptions The majority of women and men (85.5% for women and 81.4% for men) believe that men and women should carry out equal amounts of household chores. Of which, 57.7% of women and 62.3% of men totally agree while the remaining 27.8% women and 19.1% men partially agree on the issue. Among women respondents, 75.4% have a positive attitude for a woman to work outside the home while her husband takes care of the children at home (49.2% agree and 26.2% partially agree). A lesser proportion of men think it is okay for a woman to work outside the home (41.5% agree and 24.9% partially agree). The majority of women and men believe that it is the man who should decide when to use family planning. Only 23.8% of women and 24.9% men replied “do not agree” when asked if they think it is the man who should decide when to use family planning. Four respondents in every five (86.4% women and 82.4% men) believe women should have equal rights as men on household properties and assets. The vast majority of respondents have a positive attitude towards women’s education where 92.7% of women and 91.4% of men said men should support women’s education. Of which, 69.5% women and 72.2% of men totally agreed on the issue while the remaining partially agreed. Table 33: Attitudes related to gender among women and men in Afar and East and West Hararghe, October 2016 Women [n=1261] Men [n=908]
Count % Count % Men and women should carry out an equal amount of household chores Agree 727 57.7% 566 62.3% Partially agree 350 27.8% 173 19.1% Total (agree and partially agree) 1077 85.5% 739 81.4% It should be ok for a woman to work outside while her husband taking care of the children Agree 620 49.2% 377 41.5% Partially agree 331 26.2% 226 24.9% Total (agree and partially agree) 951 75.4% 603 66.4% It is the man who should decide when to use family planning Do not agree 300 23.8% 226 24.9% Women should have equal rights as men on household property and assets Agree 712 56.5% 506 55.7% Partially agree 377 29.9% 242 26.7% Total (agree and partially agree) 1089 86.4% 748 82.4% Men should support women’s education Agree 876 69.5% 656 72.2% Partially agree 292 23.2% 174 19.2% Total (agree and partially agree) 1168 92.7% 830 91.4%
The perceptions of women on how much control they have over their lives was assessed by reading statements to women respondents and asking them to respond if they strongly agree, agree, are neutral, disagree or strongly disagree with each of the statements.
29 The findings showed that the majority of women (77.7%) are confident to do anything they want to do and 75.8% believe they are responsible for their own success. Two-thirds (67.9%) of women believe their misfortunes are the result of mistakes they made and 71% said they are responsible for their failures. On the other hand, the vast majority of women think they do not have control over things that happened in their lives. Only few women replied “disagree” or “strongly disagree” for the statements; “the really good things that happen to me are due to luck” (19.1%), “if something good is going to happen to me it will” (17%), and “I have little control over bad things that happen to me” (27.4%). Across the study areas, positive perception towards control over their lives among women was found to be lowest in Afar. Table 34: Perceptions related to gender among women in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=286] [n=502] [n=473] [n=1261] Count % Count % Count % Count % I can do anything I set my mind to Strongly agree 26 9.1% 218 43.4% 177 37.4% 421 33.4% Agree 126 44.1% 223 44.4% 210 44.4% 559 44.3% Total (strongly agree and agree) 152 53.2% 441 87.8% 387 81.8% 980 77.7% I am responsible for my own successes Strongly agree 26 9.1% 178 35.5% 140 29.6% 344 27.3% Agree 156 54.5% 245 48.8% 210 44.4% 611 48.5% Total (strongly agree and agree) 182 63.6% 423 84.3% 350 74.0% 955 75.8% My misfortunes are the result of mistakes I have made Strongly agree 30 10.5% 143 28.5% 129 27.3% 302 23.9% Agree 130 45.5% 222 44.2% 203 42.9% 555 44.0% Total (strongly agree and agree) 160 56.0% 365 72.7% 332 70.2% 857 67.9% I am responsible for my failures Strongly agree 26 9.1% 171 34.1% 117 24.7% 314 24.9% Agree 140 49.0% 221 44.0% 220 46.5% 581 46.1% Total (strongly agree and agree) 166 58.1% 392 78.1% 337 71.2% 895 71.0% The really good things that happen to me are due to luck Disagree 36 12.6% 85 16.9% 79 16.7% 200 15.9% Strongly disagree 1 0.3% 6 1.2% 33 7.0% 40 3.2% Total (disagree & strongly disagree) 37 12.9% 91 18.1% 112 23.7% 240 19.1% If something good is going to happen to me it will Disagree 18 6.3% 83 16.5% 70 14.8% 171 13.6% Strongly disagree 1 0.3% 3 0.6% 39 8.2% 43 3.4% Total (disagree & strongly disagree) 19 6.6% 86 17.1% 109 23.0% 214 17.0% Most of my problems are due to bad breaks Disagree 48 16.8% 104 20.7% 74 15.6% 226 17.9% Strongly disagree 2 0.7% 13 2.6% 42 8.9% 57 4.5% Total (disagree & strongly disagree) 50 17.5% 117 23.3% 116 24.5% 283 22.4% I have little control over bad things that happen to me Disagree 42 14.7% 138 27.5% 97 20.5% 277 22.0% Strongly disagree 2 0.7% 24 4.8% 42 8.9% 68 5.4% Total (disagree & strongly disagree) 44 15.4% 162 32.3% 139 29.4% 345 27.4%
7.9.3. Household decision-making Data on household decision-making was analyzed for male-headed households and the results are presented in table 35 and figure 10 below. Husbands (men) are the ultimate decision maker to buy meat for the family mentioned by 69.2% of women and 53.6% men respondents. Findings on the final decision-maker about how food is shared among family members if there is not enough food in the household varies between responses by women and men.
30 Half (49.5%) of women said husbands are the final decision-makers on how food is shared among family members and 46.3% of men replied “my wife”. Table 35: Decision-maker on household issues in male-headed households in Afar and East and West Hararghe, October 2016 Women [n=1120] Men [n=840]
Count % Count % Decision maker to buy meat for the family The respondent 207 18.5% 450 53.6% Spouse 775 69.2% 231 27.5% Mother/Father In-law 20 1.8% 38 4.5% Mother/Father 100 8.9% 104 12.4% Other Family 5 0.4% 9 1.1% Other 13 1.2% 8 1.0% Decision maker how food is shared among family members The respondent 429 38.3% 281 33.5% Spouse 554 49.5% 389 46.3% Mother/Father In-law 20 1.8% 42 5.0% Mother/Father 98 8.8% 110 13.1% Other Family 2 0.2% 5 0.6% Other 17 1.5% 13 1.5% Decision maker about large household purchases The respondent 108 9.6% 537 63.9% Spouse 871 77.8% 118 14.0% Mother/Father In-law 20 1.8% 45 5.4% Mother/Father 110 9.8% 127 15.1% Other Family 2 0.2% 6 0.7% Other 9 0.8% 7 0.8% Decision maker how to use money earned by the wife The respondent 255 22.8% 388 46.2% Spouse 690 61.6% 260 31.0% Mother/Father In-law 39 3.5% 53 6.3% Mother/Father 123 11.0% 120 14.3% Other Family 3 0.3% 6 0.7% Other 10 0.9% 13 1.5% Decision maker how to use money earned by the husband The respondent 200 17.9% 480 57.1% Spouse 770 68.8% 167 19.9% Mother/Father In-law 32 2.9% 45 5.4% Mother/Father 112 10.0% 132 15.7% Other Family 1 0.1% 7 0.8% Other 5 0.4% 9 1.1% Decision maker about woman (wife’s) health care The respondent 323 28.8% 355 42.3% Spouse 610 54.5% 288 34.3% Mother/Father In-law 45 4.0% 52 6.2% Mother/Father 127 11.3% 131 15.6% Other Family 2 0.2% 2 0.2% Other 13 1.2% 12 1.4%
The decision making role on large household purchases inclined in favor of men in which 77.8% of women said it is the husband that makes such decisions and 63.9% of men responded “myself” for the question. Women have little control over income earned by them as well as income brought by their husbands/spouses. Only 22.8% and 17.9% of women reported that they are the final decision makers on how to use their own income and income earned by their husbands/spouses respectively. In contrast, 57.1% of men said they are the final decision makers on how to use their own income and 46.2% decide on how to use their wives’ income.
31 Similarly, women are not the ultimate decision maker on their own health care. More than half (54.5%) of women reported that it is their husband who makes the final decision on their (women’s) health care and 42.3% of men said they usually make decisions about their wives’ health care.
The respondent Spouse The respondent Spouse The respondent Spouse
Women respondents Men respondents Women respondents Men respondents Women respondents Men respondents
14.0% 19.9% 31.0%
61.6% 68.8% 77.8%
63.9% 57.1% 46.2%
22.8% 17.9% 9.6%
Decision maker about large Decision maker how to use Decision maker how to use household purchases money earned by the wife money earned by the husband
Figure 10: Decision-maker on household issues in male-headed households in Afar and East and West Hararghe, October 2016 8. Discussion This IYCF survey has shown that breastfeeding is a widely prevalent practice in the study areas. This will not come as a surprise with many studies, including the latest national EDHS survey telling the same. According to the latest EDHS 2016, 95% of under two children in Ethiopia are breastfed. However, the practice of pre-lacteal feeding that affects nearly a third of newborns should be a concern, as it is also one reason to breach recommended exclusive breastfeeding practices thereby making newborns vulnerable to infections. Considering the relatively stagnating newborn mortality rate in Ethiopia, and thus the current focus on this age group, promoting avoidance of pre-lacteal feeding is an intervention area to work on in conjunction with the routine antenatal care services and the community newborn care package (CBNC) in study areas. Regarding Exclusive Breastfeeding Rates, the findings of this survey are in line with that of the latest national finding. According to EDHS 2016, national EBF rate is around 58% and it progressively declines from 74% during the first month to 36% among infants aged 4-5 months. Giving plain water, cow’s milk and complementary foods were also stated as food types disrupting EBF at national level. In this study, confusion around understanding of exclusive breastfeeding in the community seems to exist as in the case of Afar, where pre-lacteal feeding is reported to be around 40%, EBF rate at the first month of life was reported to be around 90%. Low continued breastfeeding rate recorded in Afar is also a point of concern. Breastfeeding, with higher uptakes, fulfills significant proportion of energy and fat requirements of a young child, even after the first year of life and considering the lack of access to diverse food in the study areas, promotion of continued breast feeding needs to be a programmatic focus. Nationally, continued breastfeeding rate among those 12-17 months old children stood at 91.4% (EDHS 2011). While low bottle-feeding practice is reported in this survey, in line with the latest national survey that found out the practice to be 9% among under two children, relatively higher rate is reported in West Hararghe in this study. Such finding may signify the need for tailored messages across the different intervention areas.
32 Regarding complementary feeding practices, Minimum dietary diversity (and acceptable diet) remains to be the most challenging indicators according to both the findings of this survey and the national data. Although, figures from this study look somehow better, still three-quarters of all assessed children do not consume the minimum recommended diverse diet. While this low rate can be attributed to limited availability and access to diverse food, variation in meal diversity seen in this survey among age groups may inform that there is misconception on the need of diversifying complementary food starting from 6 months of age. Findings of this survey also showed that the majority of under-two children did not consume iron-rich foods thus are left vulnerable to anemia. The latest national prevalence rate of anemia among children age 6-59 months stands at 56% (EDHS 2016). The above mentioned IYCF practices as well as multiple basic and underlying factors contribute to the prevailing malnutrition condition in the study areas. Higher levels of acute malnutrition of all forms may be attributed to the drought condition, which affected all districts during the study period in the selected areas. According to the latest national hotspot classification (August 2016), all intervention districts did fall under Hotspot Priority 1 category signifying the severity of the drought on health and nutrition. Regarding sex variations in acute malnutrition distribution in the study, more boys are affected than girls across all the study areas. The larger discrepancies (as seen in the case of East Hararghe) may need to be taken with caution and gender related socio-cultural factors need to be sought for. Stunting remains to be a public health problem in all the study areas, though it is highly pronounced in East Hararghe. The latest EDHS 2016 has reported that 38% of all Ethiopian children are affected by stunting. As in the case of acute malnutrition, boys tend to be affected more by stunting in this survey. Other global studies have also conformed to such sex distribution of stunting. Regarding age distribution of stunting, it is shown to affect children older than 18 months and this finding is in line with the case in Ethiopia where around 48% of stunting (EDHS 2011) occurred among those 12-23 months old children. Childhood illnesses, especially diarrhea, significantly affect the nutritional status of children. High rate of diarrhea prevalence is recorded in the study areas, higher than the national average of 12% from EDHS 2016. Unavailability of safe drinking water and poor sanitation and hygiene practices are contributing to the high diarrhea prevalence. The percentage of households that use drinking water from improved sources is by far lower than the national average for rural areas. According to EDHS 2016, 56% of households in rural areas use drinking water from improved sources. Open defecation practice is also higher (51%) as compared with the 32% figure from EDHS 2016 and remains to be given due attention. The low dietary diversity score shows that women and men in the study areas are not getting diversified diet. This has contributed to the high prevalence of acute malnutrition among women in the reproductive age groups, especially in Afar. 9. Recommendations • Highlight the issue of pre-lacteal feeding into existing routine health programs (e.g. ANC) and newborn care initiatives such as Community Based Newborn Care Programs going on in these Woredas and project specific activities. Some specific activities include; o Emphasizing the need of avoiding pre-lacteal feeds in the trainings of HEWs and HDAs o Conducting discussions during pregnancy forums and mother support group sessions (especially in Afar) and facilitate platforms where traditional leaders and other influential people are involved o Strengthening nutrition counseling during Antenatal Care on avoidance of pre-lacteal feeds • Promote continued support to mothers in the first months after delivery as high rates of exclusive breastfeeding in the first month are seen rapidly declining
33 o Promotion of EBF should follow a community-wide approach targeting the whole family and neighbors rather than being mother specific • Encourage continued breastfeeding in all areas, particularly in case of Afar, as lack of breast milk is highly likely to affect nutritional status added to lack of other essential food types in the child’s diet o Prepare area specific messaging along this line • Address low dietary diversity (both for children and adults) and minimum acceptable diet rates by; o Teaching and counseling mothers within different income generation groups, (including VSLAs) on how to diversify child’s diet o Working together with agricultural and livelihood related interventions in the Woredas to increase production of diversified food, particularly animal products and vegetables o Developing tailored program messages: As the practice of providing complementary foods seem to increase along an increase in children’s ages, craft programmatic messages on the equal need for diverse diet among all children • Further engage in identifying area specific iron-rich foods in the intervention areas and promote their production and consumption (gardening to promote production of dark green vegetables were possible) o Also consider advocacy works for consideration of possibilities of iron fortification in the intervention areas • Higher figures in acute malnutrition entail the need for full emergency nutrition support in the intervention Woredas. Thus; o Assess if there is an existing, emergency nutrition response implemented by other partners, including the routine government CMAM intervention and identify support areas o Use emergency intervention as a good entry point for IYCF interventions. And in highly affected areas, consider supporting IYCF-E o Where discrepancy in sex variation among those affected by acute malnutrition is high, as in East Hararghe, consider further investigation for existence of gender related factors that to identify pertinent measures • Further assess factors related with relatively better complementary feeding practices as well as the lower stunting rate in West Hararghe and see what can be taken as best practice to the other intervention areas • Given the high diarrhea prevalence, emphasis should be given to improve the water, sanitation and hygiene situation in the areas. Specific interventions include; o Promoting of household latrine facilities through dissemination of area specific and tailored messages. Undertaking formative assessment of factors (barriers and facilitators) affecting the installation of latrines is essential for developing tailored messages across the intervention areas o Promoting of household water treatment could be considered as an immediate intervention as access to safe water sources is low and increasing the coverage needs long term intervention
34 Annexes Annex 1: Foods and liquids given to 0-5 month infants Table 36: Foods and liquids given to 0-5 month infants in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=26] [n=45] [n=34] [n=105] Count % Count % Count % Count % Liquids Plain water 15 57.7% 23 51.1% 15 44.1% 53 50.5% Infant formula 0 0.0% 2 4.4% 3 8.8% 5 4.8% Animal milk 4 15.4% 7 15.6% 7 20.6% 18 17.1% Fruit juice or juice drinks 0 0.0% 4 8.9% 4 11.8% 8 7.6% Broth (chicken soup, vegetable soup bean soup 0 0.0% 4 8.9% 6 17.6% 10 9.5% etc.) Other water-based liquids (e.g. Soft drinks like 0 0.0% 6 13.3% 5 14.7% 11 10.5% Pepsi, Coca Cola, Sprite, Fanta ) Sour milk or yogurt or skimmed milk, curd 4 15.4% 5 11.1% 6 17.6% 15 14.3% Thin porridge (cannot pick with hands) 1 3.8% 7 15.6% 4 11.8% 12 11.4% Tea or coffee 2 7.7% 1 2.2% 4 11.8% 7 6.7% Vitamin syrup, cough syrup, other medicines 1 3.8% 4 8.9% 4 11.8% 9 8.6% Oral Rehydration Solution 1 3.8% 4 8.9% 2 5.9% 7 6.7% Any other liquid (write liquid below) 3 11.5% 4 8.9% 5 14.7% 12 11.4% Foods Cereals (grains) 13 50.0% 28 62.2% 10 29.4% 51 48.6% Vitamin a rich vegetables & tubers 3 11.5% 12 26.7% 3 8.8% 18 17.1% White tubers & roots 0 0.0% 9 20.0% 4 11.8% 13 12.4% Dark green/leafy vegetables 0 0.0% 9 20.0% 3 8.8% 12 11.4% Other vegetables 2 7.7% 11 24.4% 5 14.7% 18 17.1% Vitamin a rich fruits 0 0.0% 4 8.9% 3 8.8% 7 6.7% Other fruits 0 0.0% 7 15.6% 7 20.6% 14 13.3% Organ meat (iron-rich) 2 7.7% 5 11.1% 4 11.8% 11 10.5% Flesh meats 1 3.8% 9 20.0% 3 8.8% 13 12.4% Eggs 3 11.5% 4 8.9% 10 29.4% 17 16.2% Fish 0 0.0% 5 11.1% 1 2.9% 6 5.7% Legumes, nuts and seeds 1 3.8% 13 28.9% 8 23.5% 22 21.0% Milk products 13 50.0% 17 37.8% 10 29.4% 40 38.1% Red palm oil 0 0.0% 17 37.8% 4 11.8% 21 20.0% Oils and fats 1 3.8% 15 33.3% 4 11.8% 20 19.0% Other fortified foods 0 0.0% 15 33.3% 7 20.6% 22 21.0% Other spices, condiments 0 0.0% 16 35.6% 7 20.6% 23 21.9% Other foods 4 15.4% 10 22.2% 10 29.4% 24 22.9%
Annex 2: Food types consumed among 6-8 months old infants Table 37: Food types consumed among 6-8 months old infants in Afar and East and West Hararghe, October 2016 Afar East Hararghe West Hararghe Total [n=17] [n=26] [n=24] [n=67] Count % Count % Count % Count % Foods Cereals (grains) 8 47.1% 25 96.2% 16 66.7% 49 73.1% Vitamin a rich vegetables & tubers 0 0.0% 6 23.1% 3 12.5% 9 13.4% White tubers & roots 1 5.9% 5 19.2% 6 25.0% 12 17.9% Dark green/leafy vegetables 1 5.9% 0 0.0% 6 25.0% 7 10.4% Other vegetables 1 5.9% 9 34.6% 4 16.7% 14 20.9% Vitamin a rich fruits 0 0.0% 0 0.0% 7 29.2% 7 10.4% Other fruits 0 0.0% 0 0.0% 7 29.2% 7 10.4% Organ meat (iron-rich) 0 0.0% 0 0.0% 4 16.7% 4 6.0%
35 Afar East Hararghe West Hararghe Total [n=17] [n=26] [n=24] [n=67] Count % Count % Count % Count % Flesh meats 0 0.0% 0 0.0% 5 20.8% 5 7.5% Eggs 0 0.0% 1 3.8% 9 37.5% 10 14.9% Fish 0 0.0% 0 0.0% 1 4.2% 1 1.5% Legumes, nuts and seeds 0 0.0% 1 3.8% 7 29.2% 8 11.9% Milk products 14 82.4% 7 26.9% 11 45.8% 32 47.8% Red palm oil 2 11.8% 7 26.9% 9 37.5% 18 26.9% Oils and fats 5 29.4% 4 15.4% 8 33.3% 17 25.4% Other fortified foods 2 11.8% 4 15.4% 6 25.0% 12 17.9% Other spices, condiments 4 23.5% 11 42.3% 13 54.2% 28 41.8% Other foods 1 5.9% 7 26.9% 13 54.2% 21 31.3%
Annex 3: Prevalence of underweight Table 38: Prevalence of underweight based on weight-for-age z-scores and by sex among children of age 6-59 months in Afar and East and West Hararghe, October 2016 All Boys Girls n = Afar=180; East Hararghe=285; n = Afar =100; East Hararghe =163; n = Afar =80; East Hararghe =122; West Hararghe=325; Total =790 West Hararghe =193; Total =456 West Hararghe =132; Total =334 Prevalence of underweight (<-2 z-score) (43) 23.9 % (28) 28.0 % (15) 18.8 % Afar (18.2 - 30.6 95% C.I.) (20.1 - 37.5 95% C.I.) (11.7 - 28.7 95% C.I.) East (59) 20.7 % (42) 25.8 % (17) 13.9 % Hararghe (16.4 - 25.8 95% C.I.) (19.7 - 33.0 95% C.I.) (8.9 - 21.2 95% C.I.) West (46) 14.2 % (36) 18.7 % (10) 7.6 % Hararghe (10.8 - 18.4 95% C.I.) (13.8 - 24.7 95% C.I.) (4.2 - 13.4 95% C.I.) (148) 18.7 % (106) 23.2 % (42) 12.6 % Total (9.3 - 34.1 95% C.I.) (13.0 - 38.0 95% C.I.) (4.1 - 32.5 95% C.I.) Prevalence of moderate underweight (<-2 z-score and >=-3 z-score) (29) 16.1 % (18) 18.0 % (11) 13.8 % Afar (11.5 - 22.2 95% C.I.) (11.7 - 26.7 95% C.I.) (7.9 - 23.0 95% C.I.) East (32) 11.2 % (24) 14.7 % (8) 6.6 % Hararghe (8.1 - 15.4 95% C.I.) (10.1 - 21.0 95% C.I.) (3.4 - 12.4 95% C.I.) West (28) 8.6 % (21) 10.9 % (7) 5.3 % Hararghe (6.0 - 12.2 95% C.I.) (7.2 - 16.1 95% C.I.) (2.6 - 10.5 95% C.I.) (89) 11.3 % (63) 13.8 % (26) 7.8 % Total (5.3 - 22.3 95% C.I.) (7.4 - 24.4 95% C.I.) (2.2 - 23.9 95% C.I.) Prevalence of severe underweight (<-3 z-score) (14) 7.8 % (10) 10.0 % (4) 5.0 % Afar (4.7 - 12.6 95% C.I.) (5.5 - 17.4 95% C.I.) (2.0 - 12.2 95% C.I.) East (27) 9.5 % (18) 11.0 % (9) 7.4 % Hararghe (6.6 - 13.4 95% C.I.) (7.1 - 16.8 95% C.I.) (3.9 - 13.4 95% C.I.) West (18) 5.5 % (15) 7.8 % (3) 2.3 % Hararghe (3.5 - 8.6 95% C.I.) (4.8 - 12.4 95% C.I.) (0.8 - 6.5 95% C.I.) (59) 7.5 % (43) 9.4 % (16) 4.8 % Total (3.4 - 15.5 95% C.I.) (5.6 - 15.5 95% C.I.) (1.0 - 19.7 95% C.I.)
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Table 39: Prevalence of underweight based on weight-for-age z-scores and by age among children of age 6-59 months in Afar and East and West Hararghe, October 2016 Total Severe underweight Moderate underweight (>= -3 and <-2 z-score ) (<-3 z-score) no. No. % No. % Afar 6-11 months 30 1 3.3 4 13.3 12-17 months 45 5 11.1 5 11.1 18-23 months 41 3 7.3 8 19.5 24-59 months 64 5 7.8 12 18.8 East Hararghe 6-11 months 26 2 7.7 3 11.5 12-17 months 90 7 7.8 10 11.1 18-23 months 75 6 8.0 8 10.7 24-59 months 94 12 12.8 11 11.7 West Hararghe 6-11 months 68 3 4.4 2 2.9 12-17 months 90 3 3.3 7 7.8 18-23 months 66 5 7.6 4 6.1 24-59 months 101 7 6.9 15 14.9 Total 6-11 months 124 6 4.8 9 7.3 12-17 months 225 15 6.7 22 9.8 18-23 months 182 14 7.7 20 11.0 24-59 months 259 24 9.3 38 14.7
Annex 4: Baseline values for key indicators Table 40: Baseline values for key indicators, October 2016 Indicator Afar East Hararghe West Hararghe Total Proportion of boy and girl children 6-59 months with Length- 35.4 % 49.3 % 32.2 % 39.1 % for-Age < -2 sd (Stunted) Proportion of boy and girl children d-59 months with Weight- 13.5 % 23.0 % 10.8 % 10.2 % for-Length < -2 sd (Wasted) % change in pregnant and lactating women with MUAC <23 43.9% 21.9% 17.9% 24.7% cm % of children 0-59 months who receive MAD by meeting MMF 8.7% 14.2% 34.9% 20.2% and MDD in previous 24 hours % of children 0 – 5 months who are exclusively breastfed 54.4% 58.7% 51.4% 55.5% % of women who meets minimum Dietary Diversity 16.4% 31.3% 37.8% 30.4% % of communities ODF* 8.0% 68.5% 51.8% 48.5% % of HH with access to improved water sources 15.4% 38.6% 29.6% 30.0% *Percentage of households whose family members always use latrines (do not practice open defecation)
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