Tana River County SMART Survey Report February 2020

Tana River County SMART Survey Report

February 2020

ACKNOWLEDGEMENT Tana River County SMART survey was made successful through the contribution of a number of partners. The County Department of Health led in the survey management. The County appreciates the immense support accorded by partners at different levels in making this year’s SMART survey a success. These partners include; UNICEF and Concern Worldwide. Special gratitude to; The Tana River County Nutrition Technical Forum and Nutrition Information Technical Working Group for their technical guidance during the survey, County government of Tana River for creating an enabling environment during the data collection exercise , Tana River County community for taking time to provide information which will be of importance in making informed decisions in the nutrition sector programming and last but not least the dedicated survey team members who worked hard in ensuring quality data is collected during this exercise.

LIST OF ABBREVIATIONS ARI Acute Respiratory Infection FAO Food and Agriculture Organization BCG Bacillus Chalmette Guerin CIDP County Integrated Development Plan CLTS Community Led Total Sanitation CSG County Steering Group CHS Community Health Strategy CHMT County Health Management Team CSI Coping Strategy Index ENA Emergency Nutrition Assessment GAM Global Acute Malnutrition IPC Integrated Phase Classification KEPI Kenya Expanded Program on Immunization MNPs Micronutrients Powders MUAC Mid Upper Arm Circumference NDMA National Drought Management Authority ODK Open Data Kit OPV Oral Polio Vaccine PLW Pregnant and lactating women SAM Severe Acute Malnutrition SBCC Social Behaviour Change and Communication SMART Standardized Monitoring Assessment on Relief and Transition SPSS Statistical Package for Social Sciences UNICEF United Nation Children Fund WASH Water hygiene and Sanitation WHO World Health Organization. CNC County Nutrition Coordinator NSO Nutrition Support Officer IPs Implementing Partners

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Table of Contents ACKNOWLEDGEMENT ...... ii LIST OF ABBREVIATIONS ...... iii List of Tables ...... vi List of Tables ...... vi EXECUTIVE SUMMARY ...... viii CHAPTER ONE: INTRODUCTION ...... 1 1.1 Background Information ...... 1 1.2 Rationale of the Survey ...... 1 1.3. Survey Objectives ...... 2 1.4. Specific Objectives ...... 2 1.5. Survey Timing ...... 2 CHAPTER TWO: SURVEY METHODOLOGY ...... 3 2.0 Survey Area ...... 3 2.1 Survey Design ...... 3 2.2 Study Population ...... 3 2.3 Sample Size ...... 3 2.4 Cluster and Household Selection ...... 4 2.5 Data Collected ...... 4 2.6 Survey Organisation ...... 4 2.7 Questionnaire ...... 5 2. 8: Data collection ...... 5 2.9 Data Analysis and Report Writing ...... 5 2.10 Referrals ...... 6 2.11 Ethical consideration ...... 6 2.12 Quality Assurance ...... 6 2.13 Survey Limitation ...... 7 CHAPTER THREE: SURVEY FINDINGS AND DISCUSSION ...... 8 3.1 Response Rate ...... 8 3.2 Demographics ...... 8 3.2.1: Marital Status ...... 8 3.2.2. Education Level of the Household Head ...... 8

3.2.3 School Enrolment for 3-18 years ...... 9 3.2.4 Main Occupation and Source of Income of the household head...... 9 3.3 Anthropometric results (based on WHO standards 2006)...... 10 3.3.1 Age Verification ...... 10 3.3.2: Distribution of Age and Sex (Under-fives) ...... 10 3.3.3. Prevalence of Acute Malnutrition (Wasting) ...... 11 3.3.4. Trends of Acute Malnutrition in Tana River County ...... 13 3.3.5 Prevalence of Acute Malnutrition based on MUAC ...... 14 3.3.6 Prevalence of Underweight based on WFA ...... 14 3.3.7 Prevalence of Chronic Malnutrition (Stunting) based on Height for Age (HFA)...... 15 3.4 Children Morbidity and Health Seeking ...... 15 3.4.1 Therapeutic Zinc Supplementation during watery diarrhoea episodes ...... 16 3.4.2 Health Seeking ...... 16 3.5. Child Immunization, Vitamin A and Micronutrients Supplementation and Deworming ...... 17 3.5.1. Immunization ...... 17 3.5.2 Vitamin A Supplementation and Deworming ...... 18 3.6 Maternal Nutrition ...... 18 3.6.1 Women physiological status ...... 19 3.6.2 Iron and Folic Acid Supplementation (IFAS) ...... 19 3.6.3 Maternal Nutrition Status ...... 20 3.7 WATER SANITATION & HYGIENE ...... 20 3.7.1 Main Source of Water ...... 21 3.7.2 Distance to Water Source and Queuing Time ...... 21 3.7.3. Household water treatment ...... 22 3.7.4 Storage of Drinking water ...... 23 3.7.5. Payment of Water and Consumption ...... 23 3.7.6 Hand washing ...... 23 3.7.7 Sanitation Facilities Ownership and Accessibility ...... 24 3.8 FOOD SECURITY ...... 25 3.8.1 Dominant foods and food groups consumed by households and women ...... 25 3.8.2 Minimum Household Dietary Diversity (HHDS) ...... 26 3.8.3 Women Dietary diversity score ...... 28 3.8.4 Food Consumption Score Classification...... 29 3.8.5 Food Consumption Score –Nutrition ...... 30

3.9 Coping strategy Index ...... 31 3.10 Food Fortification ...... 31 CHAPTER FOUR: CONCLUSION AND RECOMMENDATIONS ...... 33 4.1 Conclusion ...... 33 4.2 Recommendation ...... 33 REFERENCES ...... 36 APPENDICES ...... 37 Appendix 1: Overall Score of the Survey ...... 37 Appendix 2: Sampled Villages ...... 37 Appendix 4: Questionnaire ...... 45 Appendix 5: Survey Team ...... 59 Appendix 6: Survey Coordination Team ...... 59

List of Tables Table 1: Summary of Findings ...... viii Table 2: Seasonal Calendar of Tana River County...... 2 Table 3: Sample Size Calculation ...... 3 Table 4: Response Rate ...... 8 Table 5: Reason for not being enrolled in School ...... 9 Table 6: Main Occupation and Source of Income of the Household Head ...... 9 Table 7: Age Verification ...... 10 Table 8: Distribution of age and sex ...... 10 Table 9: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex ...... 11 Table 10: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema .. 13 Table 11: Distribution of acute malnutrition and oedema based on weight-for-height z-scores ...... 13 Table 12: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex ...... 14 Table 13: Prevalence of underweight based on weight-for-age z-scores by sex ...... 15 Table 14: Prevalence of stunting based on height-for-age z-scores and by sex ...... 15 Table 15: Consumption of IFAS ...... 20 Table 16: Maternal Nutrition status using MUAC ...... 20 Table 17: Main Sources of water for drinking ...... 21 Table 18: Handwashing ...... 23 Table 19: Sanitation Facilities ...... 25 Table 20: Coping Strategy Index ...... 31 Table 21: Recommendation ...... 33

List of Tables Figure 1: Tana River County Livelihood Zones ...... 1 Figure 2: Marital Status ...... 8 Figure 3: Education Level for the Household Head ...... 9 Figure 4: WHO Standard Curve for Distribution of Weight for Height of the children surveyed ...... 12

Figure 5: Global Acute Malnutrition Trends for Tana River County...... 14 Figure 6: Child Morbidity ...... 16 Figure 7: Health seeking Behavior ...... 17 Figure 8: Measles and OPV Immunization ...... 17 Figure 9: Vitamin A Supplementation ...... 18 Figure 10: Physiological Status of the women ...... 19 Figure 11: Trekking Distance to the water sources ...... 21 Figure 12: Queueing for water at the water sources ...... 22 Figure 13: Water Treatment ...... 22 Figure 14: Food groups consumed by the household within 24 hour Recall Period ...... 25 Figure 15: Food consumed by Women of Reproductive Age ...... 26 Figure 16: Minimum Household Dietary Diversity ...... 27 Figure 17: Household Consumption of micro nutrient foods ...... 28 Figure 18: Women Dietary Diversity Score ...... 29 Figure 19: Food Consumption Score ...... 29 Figure 20: Frequency Consumption of protein, Vitamin A rich foods and Hem Iron Rich Foods ...... 30 Figure 21: Number of days in a week micronutrient rich foods was consumed ...... 31

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EXECUTIVE SUMMARY Introduction Tana River County is located in the Kenyan Coastal region and is divided in to 3 sub counties namely; Bura (Tana North), Galole (Tana River ) and Garsen (Tana Delta). The County has four main livelihood zones namely; Pastoral, National Park, Marginal mixed farming and Mixed farming. The County department of health with support from UNICEF and Implementing Partners carried out a SMART survey in the entire County in February 2020. The main objective of the survey was to determine the prevalence of malnutrition among the children aged 6 - 59 months, pregnant and lactating mothers in Tana River County. Specifically, the survey aimed at determining the nutrition status of children 6 to 59 months, the nutritional status of women of reproductive age (15-49 years) based on maternal mid upper arm circumference, immunization coverage; measles (9-59 months), OPV1/3 and Vitamin A for children aged 6-59months. The survey also was meant to determine deworming coverage for children aged 12 to 59 months, the prevalence of common illnesses as well to assess maternal and child health care practices, water, sanitation and hygiene practices and prevailing food security situation in the County. Methodology The survey was cross sectional and descriptive by design. Standardized Monitoring and Assessment of Relief and Transition methodology was be adopted in the study. The study applied quantitative approach. Two stage sampling was used in the survey. The first stage involved random selection of clusters from the sampling frame based on probability proportion to population size (PPS)1.Emergency Nutrition Assessment (ENA) for Standardized Monitoring for Assessment of Relief and Transition (SMART) July 2015 was used in calculation of sample size. Household was used as the sampling unit in the second stage sampling or basic Sampling Unit. The survey sample size of 659 households was obtained using ENA software. Based on logistical factors (time taken to arrive from the clusters, introductions, sampling, inter household movement, lunch and time back to the base), it was possible to visit 16 households per cluster per day translating to a minimum of 42 clusters. Simple random sampling was used in household selection. Led by a village guide, the survey teams developed a sampling frame in each of the village sampled during the first stage sampling in case such a list never existed. For the data collection purpose, electronic questionnaire was used. Anthropometric data processing was done using ENA software version 2015 (July). All the other quantitative data were analysed in Ms. Excel and the SPSS (Version 20) computer package. Summary of Findings Table 1: Summary of Findings

TANA RIVER FINDINS FEBRUARY 2020 n % Response Rate Yes 642 97.4% No Of children 596 112.7% Number of clusters 42 100.0% Total Population 3699 No of 0-59 Months 744 No of 0-23 Months 334

1 In this method villages with more population are likely to be selected as compared to those with low population viii

ANTHROPOMETRIC RESULTS WHZ Design Effect : 1.6 Prevalence of GAM based on GAM 77 13.1 %(9.9 - WHZ (-2 z score 17.0) Prevalence of SAM based on SAM 16 2.7 %(1.5 - 4.8) WHZ (-3 z score) and/or edema Prevalence of moderate MAM 61 10.4 % (7.5 - malnutrition 14.1) (<-2 z-score and >=-3 z-score, no oedema) Prevalence of global GAM by MUAC 13 2.2 % (1.2 - 3.9) malnutrition (< 125 mm and/or oedema) by MUAC Prevalence of underweight Global Underweight 138 23.6 % (19.4 - (<-2 z-score) 28.3) Prevalence of severe Severe Underweight 26 4.4 % (2.9 - 6.7) underweight (<-3 z-score) Prevalence of stunting Global Stunting 140 24.5 % (20.5 - (<-2 z-score) 28.9) Prevalence of severe stunting Severe Stunting 37 6.5 %(4.6 - 9.0) (<-3 z-score) HOUSEHOLD CHARACTERSITICS Livestock Herding 186 29.0% Own Farm labour 147 22.9% Employed 47 7.3% Waged (Casual labour) 94 14.6% Main Occupation Petty trade 63 9.8% Merchant/Trader 20 3.1% Firewood/Charcoal 33 5.1% Fishing 9 1.4% Others 43 6.7% Sale of livestock 115 17.9% Sale of livestock products 80 12.5% Sale of crops 110 17.1% Petty trading 107 16.7% Casual labour 148 23.1% Main source of income Permanent Job 24 3.7% Sale of Personnel assets 7 1.1% Remittance 3 0.5% Income earned by Children 10 1.6% Others 33 5.1%

Older Persons Programme 5 0.8% WASH FINDINGS Piped into dwelling 4 0.6% Piped to yard/plot 35 5.5% Piped to Neighbour 28 4.4% Public tap/standpipe 31 4.8% Tube well/Borehole 290 45.2% Water source Protected well 15 2.3% Rain Water 13 2.0% Tanker truck 8 1.2% Cart with small tank 2 0.3% Water Kiosk 22 3.4% Surface Water 194 30.2% Water Treatment 107 16.7% Boiling 12 11.2% Water treatment Methods Chemicals 80 74.8% Traditional herbs 14 13.1% Pot filters 4 3.7% Aware of Hand washing (All households) Yes 513 79.9% After Toilet 457 89.1% When do you wash hands(For Before cooking 323 63.0% all Household with children under twos) Before Eating 481 93.8% After taking children to the toilet 226 44.1% Used to wash hands Soap and water 347 67.6% 4 critical times 4 Critical times 170 33.1% Flush to Pit latrine 5 0.8% Flush to piped sewer system 8 1.2% Flush to septic tank 3 0.5% Ventilated Improved Pit Latrine 8 1.2% Pit latrine with slab 168 26.2% Toilet Facility Pit latrine without slab/open pit 115 17.9% No facility /Bush/field 325 50.6% Composting Toilet 1 0.2% Hanging Toilet/Hanging Latrine 8 1.2% Bucket 1 0.2% FOOD SECURITY FINDINGS <3 27 4.2% Minimum Household Dietary 3 to 5 food groups 271 42.2% Diversity >5 food groups 344 53.6% Cereals and cereal products 564 87.9% Household Dietary Diversity White tubers and roots product 102 15.9%

Vegetables 407 63.4% Fruits 57 8.9% Meat 95 14.8% Eggs 12 1.9% Fish 190 29.6% Pulses/legumes, nuts 277 43.1% Milk and milk products 296 46.1% Oils/fats 580 90.3% Sweets: 541 84.3% Condiments, 470 73.2% Poor Food Consumption 13 2.0% Food consumption score Border Food Consumption 46 7.2% Good Food Consumption 583 90.8% Mosquito Net Coverage Mosquito Net Yes 635 98.9% No 7 1.1% Child Characteristics Health Card/MNCH Booklet 469 70.1% Birth Certificate 38 5.7% Age Verification Baptism Card 1 0.1% Recall 161 24.1% Male 348 52.0% Gender Female 321 48.0% Yes 1169 85.0% school Enrolled 3-18 Years No 207 15.0% Chronic Sickness 7 3.4% Family labour Responsibilities 26 12.6% Household does not Value Education 2 1.0% Reason for not being in school Too poor to buy school items 10 4.8% No school near by 9 4.3% Married 7 3.4% Others i.e. Young to go to School, attending Madrasa 146 70.5% MORBIDITY FINDINGS Yes 212 35.2% Prevalence of Fever 78 36.8% Prevalence of ARI 148 69.8% Morbidity Prevalence of Watery Diarrhoea 27 12.7% Prevalence of Bloody Diarrhoea 1 0.5% Prevalence of Others 18 8.5% Health Seeking Behaviour Health Seeking Behaviour 168 79.2%

Community Health worker 20 11.9% Private Clinic/Pharmacy 14 8.3% Public clinic 122 72.6% Shop/Kiosk 9 5.4% Traditional healer 3 1.8% Mobile Clinic 3 1.8% Local Herbs 1 0.6% SUPPLEMENTATION FINDINGS Zinc Supplementation 19 70.4% Vitamin A Supplementation (12- 59 Months) - Once 419 82.2% Vitamin A Supplementation (12- 59 Months) - Once-Verified by Card 258 50.6% Vitamin A Supplementation (12- 59 Months) - Once-by recall 161 31.6% Vitamin A Supplementation (12- 59 Months) - Twice 236 46.3% Vitamin A Supplementation (6-11 Vitamin A Supplementation Months )- Once 61 66.3% Vitamin A Supplementation (6-11 Months )- Once- Verified by Card 43 46.7% Vitamin A Supplementation (6-11 Months )- Once- by Recall 18 19.6% Vitamin A Supplementation (6-59 Months) -once- Verified By card 300 49.8% Vitamin A Supplementation (6-59 Months) -once 487 80.9% Vitamin A Supplementation (6-59 Months) -by Recall 187 31.1% Deworming Deworming (12-59 Months) 378 74.1% IMMUNIZATION FINDINGS Measles at 9 Months (Yes by Card) 333 59.4% Measles at 9 Months (Yes by Recall) 189 33.7% Measles Measles at 18 Months (Yes by Card) 213 43.9% Measles at 18 Months (Yes by Recall) 163 33.6% BCG BCG by Scar 594 98.7% OPV 1 (Yes by Card) 400 66.4% OPV OPV 1 (Yes by Recall) 196 32.6% OPV 3 (Yes by Card) 396 65.8%

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OPV 3 (Yes by Recall) 184 30.6% MATERNAL NUTRITION Malnourished (<210 mm) 23 3.7% WRA At Risk (210 - <230 mm) 89 14.2% PLW Malnourished (<210 mm) 12 3.9% Pregnant 64 10.2% Lactating 234 37.4% Physiological Status Pregnant and Lactating 10 1.6% None of the above 318 50.8% Yes 266 92.0% Below 90 Days 180 67.7% IFAs 90 to >= 180 81 30.5% Above 180 Days 5 1.9% WOMEN DIETARY DIVERSITY All starchy staple foods 591 94.4% Beans and peas 421 67.3% Nut and seeds 16 2.6% Dairy (Milk) 293 46.8% Flesh foods 214 34.2% Women Dietary Diversity Eggs 32 5.1% Vitamin A rich dark green leafy Vegetables 272 43.5% Other Vitamin A rich vegetables and fruits 73 11.7% Other Vegetables 360 57.5% Other fruits 28 4.5% Minimum Women Dietary < 5 Food groups 449 71.7% Diversity 5 and more food groups 177 28.3% CSI 10.14

Conclusion Overall the nutrition Status of children in Tana River County is classified to be in phase 2 (Serious) according to IPC classification for acute malnutrition with a GAM of 13.1% (9.9-17.0) and SAM of 2.7% (1.5- 4.8). The situation remained the same compared to 2019 where the GAM was 14.8 % (11.7 - 18.4). Stunting rate in 2020 was 24.5% (20.5-28.9) which also remained the same compared to 2019 at 21.7 %( 18.2 - 25.8). Underweight in 2020 was 23.6% (19.4-28.3) also remained the same compared to 2019 at 23.3 % (19.8 - 27.2. According to the February 2020 SRA report, Tana River County has generally improved to Stressed (IPC Phase 2) on improving trend. Pastoral and Marginal mixed farming zones was classified to be in crisis phase (IPC phase 3) and on a worsening trend. Mixed farming zone classified to be in stressed phase and the trend worsening and now the Pastoral Livelihood Zone and the Mixed Farming Livelihood Zone are classified as Stressed Phase (IPC Phase 2) while the Marginal Mixed Farming Livelihood Zone is classified as Crisis

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Phase (IPC Phase 3). In terms of child morbidity, 35.2% of the children were ill based on two weeks recall period, most children had ARI at 69.8% followed by fever at 36.9%. In Tana River County, 80.9% of the children aged 6-59 Months were supplemented with Vitamin A once which is slightly above the national target while 49.8% were supplemented twice. On deworming, 74.1% of the children aged 12-59 months were dewormed which is below the national target of 80%. On measles immunization at 9 months, 93.1% of the children aged 9-59 months were vaccinated while 77.5% children aged 18-59 months were vaccinated with the second dose of measles. On water and sanitation, 79.9% of the household interviewed were aware of hand washing but only 33.1% washed hands at 4 critical times which includes: after toilet, before cooking, before eating and after taking children to the toilet. In terms of hand washing with soap, 67.6% of the household interviewed reported to be using soap while washing hands. Most people (50.6%) in Tana River County have no toilet/latrine facility which is dangerous for the community especially during rainy season when diarrhoea cases increases. On food security, 53.6% of the household consumed more than 5 food groups, with the major food consumed being: Cereals and cereal products, Oils/fats, Condiments, Sugary foods and vegetables. On food consumption score, 90.3% of the household interviewed had good food consumption score. Maternal nutrition status based on MUAC measurement among all women of reproductive age and pregnant and lactating women with the two categories having MUAC of <21cm at 3.7% and 3.9% respectively. Average IFAS consumption mean number of days FeFo was consumed was found to be 64.7 days out of the minimum required days of 180. More advocacy on FeFo utilization is needed to help increase the uptake. On women dietary diversity, only 28.3% of the women of the reproductive age consumed 5 or more food groups. In conclusion it was noted that key drivers of poor nutritional status in Tana River County include; chronic food insecurity, inadequate dietary diversity, Poor access to safe water, Poor hygiene and sanitation practices. Recommendation

Findings Recommendations Timelines Actors (By Who)M

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GAM rate of • Establish a Multi-sectoral platform for high level July 2020 13.1% advocacy and coordination of nutrition activities MOH/TRCG/KRCS/U both sensitive and specific and advocate for NICEF/WVK/Concern recruitment of more nutritionist to help boost nutrition service delivery. • Develop a joint plan of action with all other nutrition sensitive departments to ensure a multi sectoral approach in addressing malnutrition in the county. • Active case findings at the community and Nutrition surveillance. • Scale up of IMAM surge activities at health facilities implementing IMAM. • Continued scale up of MIYCN activities (BFCI and BFHI) as well as IMAM activities. • Conduct integrated medical outreaches. • Provide nutrition commodities in all facilities offering IMAM services to avoid stock outs. • Integrate nutrition commodity supply chain pipeline. 50.6% of the • Sensitize communities on WASH through the MOH/TRCG/KRCS/ October 2020 population local radio stations. UNICEF/WVK/Conc practice OD • Sensitize schools on WASH through school ern health clubs • Scale up CLTS activities in all the CUs within the county. • Support PHOs to enforce construction and use of latrines at the community. • Certify ODF villages in the county. 33% practice • Sensitize the community on importance of MOH,TRCG/KRCS/ August 2020 hand washing hand washing in the 4 critical times. UNICEF/WVK/Conc in 4 critical • Use local FM radio to sensitize the community ern times on hand washing. • Train CHVs on hygiene and sanitation. • Sensitize schools on importance of hand washing in 4 critical times. • Provision of hand washing facilities to schools and other institutions.

1.9% of • Sensitize the communities on importance of MOH,TRCG/KRCS/ Sept 2020 pregnant consuming IFAS during pregnancy through UNICEF/WVK/Conc women media. ern consume IFAS • Train health care providers on IFAS for >180 days guidelines. • Conduct an operational research on IFAS adherence. • Sensitize CHVs on IFAS. • Household monitoring of pregnant mothers consuming IFAS to ensure adherence. • Ensure constant supply of IFAS tablets to avoid stock outs. Vitamin A • Sensitize the community on the importance of MOH,TRCG/KRCS/ Nov 2020 supplementati Vitamin A supplementation and deworming as UNICEF/WVK/Conc on 12 to 59 well as scale up VAS interventions within ern months (2 ECDE, Duks and at the community. doses)-46.3% • Use of radio to sensitize the community.

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CHAPTER ONE: INTRODUCTION 1.1 Background Information Tana River County is located in the Coastal region of Kenya, which occupies approximately 38,437 km2.It has an estimated population of 315, 943 people (2019 KNBS). Tana River County borders Kitui County to the West, Garissa County to the North East, Isiolo County to the North, Lamu County to the South East and Kilifi County to the South. The County has three sub counties namely: Bura, Galore and Garsen. Tana River County has four main livelihood zones namely; Pastoral, Marginal mixed farming, Mixed farming and National park as shown in figure 1. Generally, the county experiences bimodal rainfall pattern which is mostly erratic with long rains falling between April and June and short rains between October and December. The pastoral and marginal mixed farming livelihood zones rely on short rains while mixed farming zone rely on long rains. The mean annual rainfall ranges between 220mm and 500mm except the mixed farming zone, which receives rainfall ranging between 750mm and 1250mm. The County is generally hot and dry with temperatures ranging between 21°C and 38°C with the coldest month in July and hottest months in September and January. It experiences two dry spells every year occurring in December to March and July to October. Most of the County consists of low-lying plains with the highest points being Minjila and Bilbil. The River Tana traverses the County from Tharaka Nithi County in the Figure 1: Tana River County Livelihood Zones North to the Indian Ocean in the South passing through Tana Delta and covering a stretch of approximately 500km, situated in the Eastern side of the county, this provides livelihood opportunity to resident population through flood receded crop farming. 1.2 Rationale of the Survey County drought status was at normal with an improving trend within all livelihood zones due to the short rains in the County according to the December 2019 NDMA bulletin. The 2019 short rains in the county resulted to floods that led to people being displaced and about 4500 hectares under crops within Tana Delta destroyed by floods and farmers counting losses. Last SMART survey conducted in January/February 2019 showed Serious GAM rate of 14.8% (11.7 - 18.4 95% IPC for acute malnutrition phase 3), SAM rate was at 2.6% 1.7 - 4.2 (95% ) and stunting at 21.7%.According to the NDMA Bulletin Dec 2019, the number of children at risk of Malnutrition was 13.3% which is still above the normal ranges of <11.43%. Tthe County was experiencing normal vegetation cover within all the 3 sub counties but there is fear of the locust that have invaded some parts of the County i.e. Bura Dhima village, Mbalambala area where most vegetation has been

1 depleted. Milk production and consumption at household level was very above the normal, this is attributed to heavy showers received which improved the quality of pasture and browse across all livelihood zones. Human and wildlife conflict also affecting some areas in Tana River like Kipini, Chara and Kilelengwani and insecurity threats due to the attacks in the neighbouring counties of Lamu and Garissa. The survey will provide updated information on the current nutrition status and inform on response actions and will be captured into the SRA of February 2020. 1.3. Survey Objectives The main objective of the survey was to determine the prevalence of malnutrition among children aged 6- 59 months old, pregnant and lactating mothers in Tana River County. 1.4. Specific Objectives • To assess current prevalence of acute malnutrition in children aged 6-59 months. • To determine the nutritional status of women of reproductive age (15-49 years). • To determine immunization coverage for measles, OPV1 & 3 and Vitamin A for children aged 6-59 months. • To determine deworming coverage for children aged 12 - 59 months. • To determine the prevalence of common illnesses (diarrhea, measles and ARI). • To assess water, sanitation and hygiene practices. • To establish the coverage of iron/folic acid supplementation and consumption during pregnancy among lactating women. • To assess health seeking behavior among caregivers of children below 5years • To assess the prevailing situation of household food security in the County. 1.5. Survey Timing Tana River SMART survey was done in February 2020. According to the County seasonal calendar, this is usually a short dry spell. At this season, communities in the mixed farming livelihood zone have their farm without crop. Pastures depleting to be considered dry season in the pastoral communities.

Table 2: Seasonal Calendar of Tana River County

Short dry spell Long rains Long dry spell Short rains Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Short rains harvest Land Planting/ Crops at Long Land Planting/ Crops at Preparati weeding green rains Preparati Weeding green on Lean maturity harvest on. Lean Maturity period for period for farmers farmers

CHAPTER TWO: SURVEY METHODOLOGY 2.0 Survey Area The target geographical area Tana River County and it covered all three Sub Counties: Tana North, Galole and Tana Delta. The county conducted one survey. 2.1 Survey Design The survey applied a two stage stratified cluster sampling using the SMART methodology with the clusters being selected using the probability proportional to population size (PPS). Stage one sampling involved the sampling of the clusters to be included in the survey while the second stage sampling involved the selection of the households from the sampled clusters. 2.2 Study Population The target population for the survey was children aged 6 – 59 months for the anthropometric component and women of reproductive age between 15 – 49 years for the maternal nutrition component. 2.3 Sample Size The anthropometric survey sample size was calculated using the SMART survey calculator. The parameters of interest were captured in the ENA 9th July 2015 software and the respective number of children and households required for the survey computed. The sampling frame for this survey was the updated list of villages (with current projected population) from the survey area. Table 3: Sample Size Calculation

Parameter Value Rationale/Source Estimated Prevalence of GAM (%) 11.7 % Used the Lower limit of the GAM rate from January 2019 Survey since according to NDMA Dec 2019 Bulletin the situation is normal on improving trend.

± Desired precision 3.5% Informed by current prevalence Design Effect 1.5 Based on January 2019 SMART Survey Children to be included 529 Average HH Size 4.6 Based on KNBS 2019 % Children under-5 20% Based on DHIS 2020 %Non-response Households 3 % Estimated non response based on the current situation pop migration Households to be included 659

No of Households per day 16

No of clusters 42

No of Teams 7

No of days 6

2.4 Cluster and Household Selection All the villages that were accessible were included in the sampling frame and sampled with probability proportional to size. At the second stage, each team listed all the households in a village/cluster and used the simple random sampling method to select the households to visit. Within the selected households all children 6-59 months were measured. Prior to the survey, a household was defined as a group of people who lived together and shared a common cooking pot. In polygamous families with several structures within the same compound but with different wives having their own cooking pots, the structures were considered as separate households and assessed separately. In cases where there was no eligible child, a household was still considered part of the sample since it was integrated survey other household related information was collected. If a respondent or child was absent during the time of household visit, the teams left a message and re-visited later to collect data for the missing person, with no substitution of households allowed.

2.5 Data Collected Quantitative data collection method was used to collect the survey data; the following data was collected: 1. Anthropometry (weight, height, edema, MUAC, age, sex) for children aged 6-59 months and MUAC for women of reproductive age. 2. Vaccination information (OPV1 and 3, measles, BCG, and Vitamin A supplementation). 3. Incidences of childhood illnesses in the last 2 weeks prior to the survey. 4. Food security information (Household Dietary Diversity Score, Women dietary Diversity Score, Food consumption Score , Food consumption Score-Nutrition and Coping strategy Index) 5. Water and sanitation Hygiene (Latrine access and coverage, water treatment and hand washing)

The survey adopted the data collection tools recommended in the nutrition survey guidelines with a few modifications to cater for all the objectives of the survey. 2.6 Survey Organisation ▪ Coordination/Collaboration: Before the survey was conducted, meetings were held with the respective authorities and key stakeholders to brief them about the purpose, objectives and methods for the survey. The survey details were discussed with the County Health office, key partners on the ground (NGO and UN). The authorities were requested to officially inform the communities (villages) that were involved in the assessment. This included validation of the methodology at the National Nutrition Information Technical Working Group (NITWG). ▪ Recruiting the Survey Team: Recruitment was done in collaboration with the Department of Health office at the County level in order to give ownership and participation in the assessment. To collect reliable and quality data, a clearly defined criteria for enumerators selection was developed. Enumerators were finally selected based on past experience, ICT knowledge and availability during training to the

entire data collection period. Seven teams of four persons were selected to include two measurers, one enumerator and a team leader. ▪ Training of the Survey Team: The teams were given 4-days training prior to fieldwork, including a standardization test to ensure standardization of measurement where ten children were measured twice by each of the enumerators. All data collectors were trained on taking anthropometric measurements, completion of questionnaires. On sampling method, the teams were trained on listing of all the household when they get to a cluster since the clusters had already been selected using ENA. From the list of all the households, simple random sampling was used to select 16 households through random number generator application. ▪ Piloting: The data collection forms and questionnaires were pilot tested in clusters not selected to be part of the larger survey, to ensure that the interviewers and respondents understood the questions and that interviewers follow correct protocols with each team visiting at least 2 households. ▪ Team work in the field: Seven teams each with four members who have experience in data collection were organized/ selected from the survey area with each team consisting of 1 team leader, interviewer and 2 measurers. In addition, supervisors were the Health workers which included the SCNO and partners which were Concern Worldwide and UNICEF closely supervised the team throughout the survey. In moving from one randomly selected household to another, a village leader, or a community volunteer, depending on the village and availability guided the teams. 2.7 Questionnaire The survey adopted the data collection tools recommended in the Nutrition Information Working Group. 2. 8: Data collection. The data collection took 6 days. Sub County Nutrition Officers with support from implementing partner’s staff supervised the teams throughout the data collection period. Teams administered the standardized questionnaire to the mother or primary caregiver. Each survey team explained the purpose of the survey exercise, issues of confidentiality and thereafter obtained verbal consent before proceeding with the interview. The teams used ODK questionnaire in tablets to record the responses. In addition, the data was uploaded to ONA servers at the end of each day. Subsequently, the anthropometric data was downloaded daily, reviewed/analysed for plausibility and feedback provided to the teams, using daily customized scorecards 2.9 Data Analysis and Report Writing • Data Analysis: the data downloading and analysis was done using ENA for SMART, Excel and SPSS Statistical software version 22. The Concern Worldwide Survey and Surveillance Officer, was responsible for the Data downloading, analysis and report writing. Results are presented using the new WHO reference levels. • Preliminary Results and Final Report: Survey and Surveillance Officer of Concern Worldwide and County Nutrition Coordinator presented the findings to CHMT, CSG stakeholders and the Nutrition Information Working Group (NIWG) within two weeks of completion of the survey fieldwork at County and National level. Indicators, Guidelines and Formulas used in determining Acute Malnutrition Weight for height (WFH) index This was estimated from a combination of the weight for height (WFH) index values (and/or edema) and by

5 sex based on WHO standards 2006. This index was expressed in WFH indices in Z-scores, according to WHO 2006 reference standards. Z-Score: ➢ Severe acute malnutrition is defined by WFH < -3 SD and/or existing bilateral edema, ➢ Moderate acute malnutrition is defined by WFH < -2 SD and >-3 SD and no edema ➢ Global acute malnutrition is defined by WFH < -2 SD and/or existing bilateral edema. Mid upper arm circumference (MUAC) MUAC analysis was also undertaken to determine the nutrition status of sampled children and women of reproductive age (15-49 years). The following MUAC criteria were applied.

MUAC guidelines: Interpretation Children 6-59 Months MUAC<115mm and /or Bilateral Edema Severe Acute Malnutrition MUAC >=115mm and <125mm (no bilateral edema) Moderate acute Malnutrition MUAC>=125mm and <135mm(No bilateral Edema) Risk of Malnutrition MUAC>135mm (No bilateral Edema) Adequate Nutritional Status Women of reproductive age (15-49 Years) MUAC >21-23cm At risk of malnutrition MUAC <21cm Maternal Acute Malnutrition 2.10 Referrals During the survey, all severe and moderately malnourished children as per MUAC and Weight-for-Height cut offs referred to the nearby health service delivery points offering IMAM services. Pregnant and lactating women with MUAC. 2.11 Ethical consideration Sufficient information was provided to the local authorities about the survey including the purpose and objectives of the survey, the nature of the data collection procedures, the target group, and survey procedures. Verbal consent was obtained from all adult participants and parents/caregivers of all eligible children in the survey. The decision of caregiver to participate or withdrawal was respected. Privacy and confidentiality of survey respondent and data was protected. 2.12 Quality Assurance To ensure data collected was valid and reliable for decision-making, a number of measures were put in place. They included; ▪ Thorough 4 days training conducted to survey participants, the training dealt on SMART methodology, survey objectives, interviewing techniques and data collection tools. ▪ Ensuring all anthropometric equipment were functional and standardized. On daily basis, each team was required to calibrate the tools. ▪ During the training exercise, standardization test was done; in addition, piloting of tools was done to ensure all the information was collected with uniformity. ▪ Conducting a review of data collection tools during training and after the pilot test. ▪ All the survey teams were assigned a supervisor during data collection. ▪ The anthropometric data collected was entered daily on ENA software and plausibility check was run. Any issues noted were communicated to the teams before they proceeded to the field the following day. 6

▪ Teams were supervised to ensure all errors were rectified on time. More attention was given to the teams with notable weaknesses. ▪ Adequate logistical planning beforehand and ensuring the assigned households per clusters were be comfortably survey. ▪ A WhatsApp group was formed to ensure close monitoring of the teams and easier for communication. ▪ Close supervision by the CNC, NSO and IPs during data collection period. 2.13 Survey Limitation In Tana Delta sub County, there was issue with insecurity due to terror attacks in Kipini East Ward hence inaccessible. The villages in Kipini East Ward were not included in the sampling frame.

CHAPTER THREE: SURVEY FINDINGS AND DISCUSSION 3.1 Response Rate The survey involved collection of information from 529 children in 659 households. Only 17 sampled households did not participate in the survey. The response rate was therefore 97.4%. The reason for non- response were absenteeism and refusal to participate. The average household size recorded from this survey was 5.8. Table 4: Response Rate

Target per the survey plan Actual No Reached Survey Zone No. of HH No. of Number of No. of HH No. of Children Total House Hold Children Clusters questionnaires Members filled Tana River 659 529 42 642 596 3699 County Percentage 97.4% 112.7%

3.2 Demographics 3.2.1: Marital Status In Tana River County, 85% of the population is married, 8% are widowed and 3% are single and divorced respectively. In addition, 99.2% of the Households were Residents and 0.8% are IDPs in Tana River County.

3% 1% 8% 3%

Married Single Widow Divorced Separated

85%

Figure 2: Marital Status

3.2.2. Education Level of the Household Head Overall, illiteracy levels remain very high at 40.5%. Of those with formal education, 35.0% and 16.0% had primary and secondary education respectively and just 3.3% of the sampled population had received tertiary education. Results show little progress in attaining improved literacy among caregivers, which is a major hindrance to improved care practices, capacity for knowledge and technology transfer at community level

8 and ultimately improved income and livelihood security for optimal nutrition and health outcomes.

50.0% 40.5% 40.0% 35.0% 30.0% 20.0% 16.0%

10.0% 2.2% 3.3% 3.0% 0.0% Pre primary Primary Secondary Tertiary None Others

Figure 3: Education Level for the Household Head 3.2.3 School Enrolment for 3-18 years For the children aged 3 to 18 years, 85.0%( 1169) of them were enrolled in a school. Among the ones not in school, 70.5% said they were too young to be enrolled and 12.6% of them were engaged in family responsibilities. Table 5: Reason for not being enrolled in School

Indicator n Percent Reasons for not being enrolled in School Chronic Sickness 7 3.4% Family labour Responsibilities 26 12.6% Household does not Value Education 2 1.0% Too poor to buy school items 10 4.8% No school near by 9 4.3% Married 7 3.4% Others i.e. Young to go to School, attending Madrasa 146 70.5%

3.2.4 Main Occupation and Source of Income of the household head The Tana River County has three main livelihood zones namely the marginal mixed farming, mixed and pastoral all species comprising of 48, 38 and 14 percent of the population respectively. Overall, results show that almost half (29.0%) of households rely on pastoral economy as main occupation followed by own farm labour at 22.9% then 14.6% practice casual labour. The main source of income in Tana River County was casual labour at 23.1% followed by sale of livestock at 17.9% and then sale of crops at 17.1%.

Table 6: Main Occupation and Source of Income of the Household Head

Indicator n Percent 9

Main Occupation of the Household Head Livestock Herding 186 29.0% Own Farm labour 147 22.9% Employed 47 7.3% Waged (Casual labour) 94 14.6% Petty trade 63 9.8% Merchant/Trader 20 3.1% Firewood/Charcoal 33 5.1% Fishing 9 1.4% Others 43 6.7% Main source of income of the Household Head Sale of livestock 115 17.9% Sale of livestock products 80 12.5% Sale of crops 110 17.1% Petty trading 107 16.7% Casual labour 148 23.1% Permanent Job 24 3.7% Sale of Personnel assets 7 1.1% Remittance 3 0.5% Income earned by Children 10 1.6% Others 33 5.1% Older Persons Programme 5 0.8% 3.3 Anthropometric results (based on WHO standards 2006) 3.3.1 Age Verification Out of all sampled children in the County, 70.1% of them had a health card, 5.7% birth certificate while 0.1% baptism card and these were used to verify their age. Age determination for 24.2% of the children was based on recall, hence prone to bias.. Table 7: Age Verification

Indicator n Percent Age Verification Health Card/MNCH Booklet 469 70.1% Birth Certificate 38 5.7% Baptism Card 1 0.1% Recall 161 24.1%

3.3.2: Distribution of Age and Sex (Under-fives) The total number of children assessed during the survey was 596 (302 boys and 294 girls). The boy to girl ratio was 1.02 and a p-value of 0.743 (boys and girls equally represented) who participated in the survey. Table 6 below is a summary of sex and age distribution of children who were assessed. Age ratio of 6-29 months to 30-59 months: 1.04 (The value should be around 0.85), p-value = 0.013 which is significance difference.

Table 8: Distribution of age and sex

Boys Girls Total Ratio

AGE (mo) no. % no. % no. % Boy:girl 6-17 78 50.6 76 49.4 154 25.8 1.0 18-29 76 50.7 74 49.3 150 25.2 1.0 30-41 63 47.4 70 52.6 133 22.3 0.9 42-53 61 51.7 57 48.3 118 19.8 1.1 54-59 24 58.5 17 41.5 41 6.9 1.4 Total 302 50.7 294 49.3 596 100.0 1.0

Under-fives Nutrition Status Under five nutrition status was assessed using anthropometric indicators namely, Weight for Height and MUAC (wasting or acute malnutrition), Height for Age (stunting or chronic malnutrition) and weight for age (underweight). Analysis was based on 2006 WHO reference standards. 3.3.3. Prevalence of Acute Malnutrition (Wasting) According to UNICEF nutrition glossary (2012), malnutrition is defined a state in which the body does not have enough of the required nutrients (under nutrition) or has excess of the required nutrients (over nutrition). Acute malnutrition is the low weight for height in reference to a standard child of a given age based on WHO growth standards. This form of malnutrition reflects the current form of malnutrition. Acute malnutrition can further be categorized as severe acute malnutrition and moderate acute malnutrition. Severe acute malnutrition is defined as weight for height < -3 standard deviation in comparison to a reference child of the same age. It also includes those children with bilateral edema as well as those with MUAC less than 11.5cm. Moderate Acute Malnutrition on the other hand is defined as weight for height >= -3 and <-2 standard deviation in comparison to a reference child of the same age and sex, but also include those children with MUAC < 12.5 cm and >= 11.5 cm. The global acute malnutrition (GAM) is the Sum of all children with moderate and severe acute malnutrition in the sample.

Prevalence of Acute Malnutrition based on Weight for Height by Sex Analysis of acute malnutrition was based on 589 children aged 6 to 59 months (298 boys and 291 girls). There was an exclusion of 7 children who were flagged off as outliers. From the analysis, Tana River county global acute malnutrition was 13.1% (9.9- 17.0, 95% C.I.) The SAM rate in the County was 2.7% (1.5-4.8, 95% C.I.). The prevalence of oedema is 0.0 %.

Table 9: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

All Boys Girls n = 589 n = 298 n = 291 Prevalence of global malnutrition (77) 13.1 % (46) 15.4 % (31) 10.7 % (<-2 z-score and/or oedema) (9.9 - 17.0 95% (11.5 - 20.5 95% (7.2 - 15.5 95% C.I.) C.I.) C.I.) Prevalence of moderate malnutrition (61) 10.4 % (37) 12.4 % (24) 8.2 % (<-2 z-score and >=-3 z-score, no (7.5 - 14.1 95% (8.8 - 17.2 95% (5.2 - 12.8 95% oedema) C.I.) C.I.) C.I.) Prevalence of severe malnutrition (16) 2.7 % (9) 3.0 % (7) 2.4 % (<-3 z-score and/or oedema) (1.5 - 4.8 95% C.I.) (1.4 - 6.4 95% (1.2 - 4.9 95% C.I.) C.I.)

The Figure below is a graphical representation of distribution of weight for height of children surveyed in 11 relation to the WHO standard curve (reference children). The curve slightly shifts to the left with a mean of - 0.91±0.99 an indication of under nutrition in comparison to reference children.

Figure 4: WHO Standard Curve for Distribution of Weight for Height of the children surveyed

Analysis of Acute Malnutrition by Age Further analysis was done on prevalence of acute malnutrition based on sex and age as indicated in table below. From the analysis older children (30 to 59 months) were more affected by severe and moderate malnutrition as compared to younger children (6 to 29 months).

Table 10: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting Moderate Normal Oedema (<-3 z-score) wasting (> = -2 z score) (>= -3 and <-2 z- score ) Age Total No. % No. % No. % No. % (mo) no. 6-17 150 3 2.0 9 6.0 138 92.0 0 0.0 18-29 149 2 1.3 19 12.8 128 85.9 0 0.0 30-41 133 8 6.0 16 12.0 109 82.0 0 0.0 42-53 116 3 2.6 13 11.2 100 86.2 0 0.0 54-59 41 0 0.0 4 9.8 37 90.2 0 0.0 Total 589 16 2.7 61 10.4 512 86.9 0 0.0

Analysis of Acute Malnutrition based on presence of Oedema Presence of bilateral edema is a sign of severe acute malnutrition. Analysis was therefore done based on this indicator. As shown in table below, no edema case was recorded among the children surveyed.

Table 11: Distribution of acute malnutrition and oedema based on weight-for-height z-scores

<-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor. 0 Kwashiorkor. 0 (0.0 %) (0.0 %) Oedema absent Marasmic Not severely malnourished. 576 No. 20 (96.6 %) (3.4 %)

3.3.4. Trends of Acute Malnutrition in Tana River County The County has generally improved to Stressed (IPC Phase 2).The Pastoral Livelihood Zone and the Mixed Farming Livelihood Zone are classified as Stressed Phase (IPC Phase 2) while the Marginal Mixed Farming Livelihood Zone is classified as Crisis Phase (IPC Phase 3)2.

2 Tana River SRA February 2020 Report 13

18.0% 16.0% 14.0% 12.0% 10.0% 8.0% 6.0%

% Prevalence % 4.0% 2.0% 0.0% 2012 2013 2014 2015 2016 2017 2018 2019 2020 GAM 13.5% 13.8% 7.5% 9.9% 14.0% 13.7% 15.6% 14.8% 13.1% SAM 3.1% 2.2% 0.9% 1.0% 1.5% 3.0% 2.2% 2.6% 2.7%

Figure 5: Global Acute Malnutrition Trends for Tana River County 3.3.5 Prevalence of Acute Malnutrition based on MUAC Malnutrition can also be diagnosed using MUAC. MUAC is a good indicator of muscle mass and can be used as a proxy of wasting (United Nation System Standing Committee on Nutrition). It is also a very good predictor of the risk of death. Very low MUAC (< 11.5 cm for children 6 to 59 months), is considered a high mortality risk and is a criteria for admission of outpatient therapeutic or in patient therapeutic program (when accompanied with complications) for treatment of severe acute malnutrition. A MUAC reading of 11.5 cm to <12.5 cm is considered as moderate malnutrition. Analysis of the nutrition status for children aged 6 to 59 months based on MUAC and or presence of Oedema resulted to GAM of 2.2% and SAM of 0.3% as indicated in table below. Table 12: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex

All Boys Girls n = 596 n = 302 n = 294 Prevalence of global malnutrition (13) 2.2 % (2) 0.7 % (11) 3.7 % (< 125 mm and/or oedema) (1.2 - 3.9 95% (0.2 - 2.7 95% (2.1 - 6.7 95% C.I.) C.I.) C.I.) Prevalence of moderate malnutrition (11) 1.8 % (2) 0.7 % (9) 3.1 % (< 125 mm and >= 115 mm, no oedema) (0.9 - 3.6 95% (0.2 - 2.7 95% (1.5 - 6.0 95% C.I.) C.I.) C.I.) Prevalence of severe malnutrition (2) 0.3 % (0) 0.0 % (2) 0.7 % (< 115 mm and/or oedema) (0.1 - 1.4 95% (0.0 - 0.0 95% (0.2 - 2.8 95% C.I.) C.I.) C.I.)

3.3.6 Prevalence of Underweight based on WFA Underweight is defined as low weight for age relative to National Centre for Health and Statistics or World Health Organization reference median. In this survey, the later was used. Children with weight for age less than -2 SD in relation to a reference child are classified as underweight while those with less than -3 SD are classified as severe underweight. Underweight is a composite form of under nutrition and has elements of both acute under nutrition (wasting) as well as chronic under nutrition (stunting). As indicated in table 11 below, the prevalence of underweight among children aged 6 to 59 months in Tana River County was 23.6% while those who were severely underweight was 4.4%.

Table 13: Prevalence of underweight based on weight-for-age z-scores by sex

All Boys Girls n = 585 n = 297 n = 288 Prevalence of underweight (138) 23.6 % (80) 26.9 % (58) 20.1 % (<-2 z-score) (19.4 - 28.3 95% (21.6 - 33.0 95% (15.5 - 25.7 95% C.I.) C.I.) C.I.) Prevalence of moderate underweight (112) 19.1 % (62) 20.9 % (50) 17.4 % (<-2 z-score and >=-3 z-score) (16.1 - 22.6 95% (16.4 - 26.2 95% (13.2 - 22.5 95% C.I.) C.I.) C.I.) Prevalence of severe underweight (26) 4.4 % (18) 6.1 % (8) 2.8 % (<-3 z-score) (2.9 - 6.7 95% C.I.) (3.8 - 9.6 95% (1.2 - 6.2 95% C.I.) C.I.) 3.3.7 Prevalence of Chronic Malnutrition (Stunting) based on Height for Age (HFA). WHO define stunting as height for age less than – 2 SD from median height for age of reference population. Childhood stunting is an outcome of maternal under nutrition as well as inadequate infant and young child feeding. It is associated with impaired neurocognitive development, a risk maker of non-communicable diseases and reduced productivity later in life (WHO 2013). Analysis of stunting prevalence based on height for age revealed an overall stunting rate of 24.7% In addition, a severe stunting (HFA< -3 in reference to standard population) rate of 6.5% as shown in table below. Boys were more stunted than girls were.

Table 14: Prevalence of stunting based on height-for-age z-scores and by sex

All Boys Girls n = 572 n = 286 n = 286 Prevalence of stunting (140) 24.5 % (81) 28.3 % (59) 20.6 % (<-2 z-score) (20.5 - 28.9 95% C.I.) (23.0 - 34.3 95% (16.2 - 25.9 95% C.I.) C.I.) Prevalence of moderate stunting (103) 18.0 % (59) 20.6 % (44) 15.4 % (<-2 z-score and >=-3 z-score) (14.9 - 21.6 95% C.I.) (16.6 - 25.4 95% (11.6 - 20.1 95% C.I.) C.I.) Prevalence of severe stunting (37) 6.5 % (22) 7.7 % (15) 5.2 % (<-3 z-score) (4.6 - 9.0 95% C.I.) (5.0 - 11.6 95% (3.2 - 8.4 95% C.I.) C.I.) 3.4 Children Morbidity and Health Seeking According to the UNICEF conceptual framework on the causes of malnutrition, disease is categorized as one of the immediate cause alongside inadequate diet. There is a relationship between the two whereby disease may alter food intake while inadequate intake of some key nutrients may lead to infection. Ultimately they all lead to one outcome; malnutrition. Assessment was done on the diseases that affected children 6 to 59 months in the past 2 weeks. Caregivers were asked whether their children had been ill in the past 2 weeks prior to the survey date. Those who gave an affirmative answer to this question were further probed on what illness affected their children and whether they sought assistance and where they sought any assistance when their child/children were ill. Those who indicated that their child/children suffered from watery diarrhoea were probed on the kind of treatment that was given to them. Among the children assessed 35.2 %( 212) were ill in the past 2 weeks prior to the survey date. Among those who were sick, majority (69.8%) suffered from ARI/Cough, 36.8% fever with chills and 12.7% suffered from

15 watery diarrhoea. CHILD MORBIDITY 80.0% 69.8%

60.0%

36.8% 40.0%

20.0% 12.7% 8.5% 0.5% 0.0% Prevalence of Fever Prevalence of ARI Prevalence of Prevalence of BloodyPrevalence of Others Waterly Diarrhoea Diarrhoea

Figure 6: Child Morbidity 3.4.1 Therapeutic Zinc Supplementation during watery diarrhoea episodes Based on compelling evidence from studies that, show efficacy of zinc supplementation in reducing duration and severity of diarrhoea in 2004 WHO and UNICEF recommended incorporating zinc supplementation (20 mg/day for 10-14 days for children 6 months and older, 10 mg/day for children under 6 months of age) as an adjunct treatment to low osmolality oral rehydration salts (ORS), and continuing child feeding for managing acute diarrhoea. Kenya has adopted these recommendations (Innocent report 2009). According to Kenyan policy guideline on control and management of diarrheal diseases in children below five years in Kenya, all under-fives with diarrhoea should be given zinc supplements as soon as possible. The recommended supplementation dosage is 20 milligrams per day for children older than 6 months or 10 mg per day in those below the age six months, for 10–14 days during episodes of diarrhoea. This survey sought to establish the number of children who suffered from watery diarrhoea and supplemented with zinc. Among the children with watery diarrhoea 70.4% (27) were supplemented with zinc. 3.4.2 Health Seeking Majority of caregivers (79.2%) whose children fell ill in the past 2 weeks prior to the survey date sought assistance. Among those who sought assistance, 72.6% did so in public clinic while 8.3% did so in private clinic and 5.4% did so in a shop or kiosk. Overall 82.3% of caregivers whose children were sick sought assistance from appropriate sources such as public clinic, private clinic or mobile clinic as shown in figure below.

Health Seeking Behaviour 80.0% 72.6% 70.0% 60.0% 50.0% 40.0% 30.0% 11.9% 20.0% 8.3% 5.4% 10.0% 1.8% 1.8% 0.6% 0.0%

Figure 7: Health seeking Behavior

3.5. Child Immunization, Vitamin A and Micronutrients Supplementation and Deworming 3.5.1. Immunization Kenya aimed to achieve 90% under one immunization coverage by the end of second medium term plan (2013- 2017). The Kenya guideline on immunization define a fully immunized child as one who has received all the prescribed antigens and at least one Vitamin A dose under the national immunization schedule before the first birthday. This survey assessed the coverage of 4 vaccines namely, BCG, OPV1, OPV3, and measles at 9 and 18 months. From this assessment, 98.7% of children were confirmed to have been immunized by BCG based on the presence of a scar. Those who were immunized by OPV1 and OPV3 were 99.0% and 96.4% respectively while 93.1% and 77.5% had been immunized for measles at 9 and 18 month respectively, as indicated in figure below.

OPV 3 65.80% 30.60%

OPV 1 66.40% 32.60%

Measles at 18 Months 43.90% 33.60%

Measles at 9 Months 59.40% 33.70%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%

Yes By Card Yes By Recall

Figure 8: Measles and OPV Immunization

3.5.2 Vitamin A Supplementation and Deworming Evidence shows that, giving vitamin A supplements to children reduces the rate of mortality and morbidity. Vitamin A reduces mortality risk by 24% (WHO 2011). Guaranteeing high supplementation coverage is critical, not only to eliminating vitamin A deficiency as a public-health problem, but also as a central element of the child survival agenda. Delivery of high-dose supplements remains the principal strategy for controlling vitamin A deficiency. Food-based approaches, such as food fortification and consumption of foods rich in vitamin A, are becoming increasingly feasible but have not yet ensured coverage levels similar to supplementation in most affected areas (UNICEF 2007). The major challenges associated with low Vitamin A coverage is : poor data management of vitamin A logistics, inadequate social mobilization to improve vitamin uptake and placement of vitamin A at lower level of priority among other interventions (MOH Vitamin A Supplementation Operational Guidelines for Health Workers 2012). To assess vitamin A supplementation, parents and caregivers were probed on the number of times the child had received vitamin A in the past one year. Reference was made to the child health card and in case the card was not available recall, method was applied. Analysis of vitamin A supplementation for children aged 6-11 months indicates that 66.3% of this age group had been supplemented with vitamin A. Among those aged 12 to 59 months, 46.3% had been supplemented with vitamin A twice in the past one year. Among 6 to 59 Months, 80.9% had been supplemented once in the past one year. Assessment on deworming for children aged 12 to 59 months indicates a small uptake of deworming drugs at 74.1% had taken de-wormers once in the past one year. Low Vitamin A supplementation and deworming was attributed to longer distances to the health facilities as children from villages far away from health facilities were more likely not to be supplemented with vitamin A or dewormed. Vitamin A Supplementation

90.0% 82.2% 80.9% 80.0% 66.3% 70.0% 60.0% 46.3% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Vitamin A Vitamin A Vitamin A Vitamin A Supplimentation (6-11 Supplementation (12-59 Supplementation (12-59 Supplementation (6-59 Months )- Once Months) - Once Months) - Twice Months) -once

Figure 9: Vitamin A Supplementation

3.6 Maternal Nutrition Evidence shows that the current total deaths in children younger than five years can be reduced by 15% if populations can access ten evidence-based interventions when implemented at scale with a coverage of

90% (Bhutta, et.al. 2013). One of these strategies, has a positive effect on child survival during ‘the window of opportunity’ which is also referred to as the 1st 1000 days (from conception to two years of age). One of them is optimal maternal nutrition during pregnancy, an enhanced nutrition package for the infant and young child focusing on promotion of exclusive breastfeeding. Pregnancy and lactation imposes a big nutrient-need load on mothers, which in the absence of adequate extra nutrients leads to utilization of body nutrient reserves leading to malnutrition. Gestational malnutrition leads to low birth weights and may ultimately culminate in poor child growth and development, thus there is an urgent need to address high rates of malnutrition among pregnant women. Household food insecurity is a key indicator/determinant of poor adult nutritional status. A high number of malnourished PLWs increase the risk of growth retardation of the fetus and consequently an increase in low birth weight and malnutrition burden spreads to both U5 children and caretakers from the same household faced with food insecurity and related vulnerabilities, a common scenario during nutrition emergency episodes. 3.6.1 Women physiological status The figure below indicates that majority of the surveyed women of Reproductive age (15-49 years) were neither lactating nor pregnant and lactating 51.0% and 37.0% respectively, but it is worth noting 2.0% of them were both lactating and pregnant. Physiological Status of the Women

10%

51% Pregnant Lactacting Pregnant and Lactacting 37% None of the above

Figure 10: Physiological Status of the women 3.6.2 Iron and Folic Acid Supplementation (IFAS) During pregnancy, women have increased need for additional iron to ensure they have sufficient iron stores to prevent iron deficiency. Iron supplementation is recommended in resource limited settings as strategy to prevent and correct iron deficiency and anaemia among pregnant women. WHO recommends daily consumption of 60mg elemental iron and 0.4mg folic acid throughout the pregnancy 3 .These recommendations have since been adopted by Kenya government in its 2013 policy guidelines on supplementation of iron folic acid supplementation (IFAS) during pregnancy. During the survey, iron folic supplementation was assessed by asking mothers of children below 2 years if they consumed iron folate in their most recent pregnancy. Results showed 92.0 %( 266) of the mothers of children below 2 years had been supplemented with IFAS in their pregnancy. The mean number of days IFAS was consumed by the women was 64.7 days. 67.7% of the mothers

3 WHO. Guideline: Daily iron and folic acid supplementation in pregnant women. Geneva, World Health Organization, 2012. 19 consumed less than 90 days in Tana River County and only 1.9% who consumed above 180 Days. While access to IFAS is high, the main challenge is now on utilization, an indication of poor health seeking behaviour where mother seek ANC services late in their last trimester of pregnancy and limited counselling and peer support to encourage continued intake of IFAS. Table 15: Consumption of IFAS

Indicator n Percent Consumption of IFAS Below 90 Days 180 67.7% 90 to >= 180 81 30.5% Above 180 Days 5 1.9%

3.6.3 Maternal Nutrition Status Maternal malnutrition is usually associated with high risk of low birth weights and it is recommended that before, during and after birth, the maternal nutrition status should be adequate. The nutrition status of women was determined using MUAC. Women with MUAC less than 21 cm are classified as malnourished. Among the women of reproductive age, 3.7% (23) were malnourished. Of these malnourished women, 3.9% (12) were PLW. The table below is a summary of maternal nutrition status. Table 16: Maternal Nutrition status using MUAC

Indicator n Percent MUAC for Women of Reproductive age Malnourished (<210 mm) 23 3.7% At Risk (210 - <230 mm) 89 14.2% MUAC for Pregnant and lactating women Malnourished (<210 mm) 12 3.9%

3.7 WATER SANITATION & HYGIENE International human rights consider access to water and sanitation as a human right.4 This means that all individuals are entitled to have access to an essential amount of safe drinking water and to basic sanitation facilities. The human right to water entitles everyone to sufficient, safe, acceptable, physically accessible and affordable water for personal and domestic use. Water and sanitation are deeply interrelated. Sanitation is essential for conservation and sustainable use of water resources, while access to water is required for sanitation and hygiene practices. Furthermore, the realization of other human rights, such as the right to the highest attainable standard of health, the right to food, right to education and the right to adequate housing, depends very substantially upon implementation of the right to water and sanitation. Research has shown that poor WASH indicators are linked to under nutrition and more so on high Stunting levels. Diarrhoea, the leading killer of young children is closely linked to poor/inadequate WASH (Pruss-Ustun, et al. 2014), which often causes under nutrition, which in turn reduces a child’s resistance to subsequent infections, thus creating a vicious circle. An estimated 25% of stunting is attributable to five or more episodes of diarrhoea before 24 months of age (Checkley, et al. 2008).

4 The UN committee on economic, Cultural and Social rights states in its General Comment of November 2002 20

3.7.1 Main Source of Water Accessibility to improved water sources is of fundamental significance to lowering the faecal risk and frequency of associated diseases. Its association with other socioeconomic characteristics, including education and income, makes it a good universal indicator of human development. Drinking water coverage is presented as a two-step ladder that includes the proportion of the population using: • Unimproved drinking water sources which include: Unprotected dug well, unprotected spring, cart with small tank/drum, tanker truck, and surface water (river, dam, lake, pond, stream, canal, irrigation channels), bottled water • Improved drinking water sources also piped water which include: Public taps or standpipes, tube wells or boreholes, protected dug wells, protected springs and rainwater collection, Piped household water connection located inside the user’s dwelling, plot or yard. There are three main water sources in Tana River County: Surface water, (which includes river, dam, lake, ponds stream and canals), Tube well/boreholes and lastly piped to the yard. Table 17: Main Sources of water for drinking

Indicator n Percent Main water sources for drinking Piped into dwelling 4 0.6% Piped to yard/plot 35 5.5% Piped to Neighbour 28 4.4% Public tap/standpipe 31 4.8% Tube well/Borehole 290 45.2% Protected well 15 2.3% Rain Water 13 2.0% Tanker truck 8 1.2% Cart with small tank 2 0.3% Water Kiosk 22 3.4% Surface Water 194 30.2%

3.7.2 Distance to Water Source and Queuing Time

According to SPHERE handbook for minimum standards for WASH, the Trekking Distance for Water maximum distance from any household to 80.0% 71.3% 70.0% the nearest water point should be 500 60.0% meters. It also gives the maximum queuing 50.0% time at a water source, which should be not 40.0% 30.0% 22.7% more than 15 minutes, and it should not 20.0% 5.9% 10.0% 0.0% Less tha 500m >500m to <2km(15 More than 2 km (<15min) to 1 hr)

Figure 11: Trekking Distance to the water sources

take more than three minutes to fill a 20-litre Queueing for Water container. On the distances to water sources, 60.0% 56.9% 71.3% of the households interviewed obtained

50.0% their water from sources less than 500m (less than 15 minutes walking distance), 22.7% took 40.0% 35.6% between 15 min to 1 hour (approximately 500m

30.0% to 2km) while the rest (5.9%) walked as far as more than 2Km (1- 2hrs) to their water sources. 20.0% On the proportion of household queuing for

10.0% 7.5% water, 27.1% (174) of the population in Tana River queue for water. Out of those that were 0.0% queuing for water in the county , (56.9%) of the Less than 30 30-1 hr More than 1 hr minutes respondents were waiting for less than 30

minutes while 35.6% of the households were Figure 12: Queuing for water at the water sources queuing for 30 and 60 minutes and 7.5% are queuing for more than 1 hour. 3.7.3. Household water treatment It is no doubt that water quantity and quality is of vital importance for the ecosystem.5 The lack of water is further aggravated by insufficient treatment of water, particularly with rapid population growth. Despite most of the households obtaining water from unsafe sources, only 16.7% (n=107) of households sampled were treating their water before drinking. Even though just 2 in 10 households treated water for drinking, use of chemicals such as PUR or aqua tabs were the dominant method used since the county government and WASH partners have invested heavily in supply of water purifying chemicals especially during and after emergency. Water Treatment 80.0% 74.8% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 11.2% 13.1% 10.0% 3.7% 0.0% Boiling Chemicals Traditional herbs Pot filters

Figure 13: Water Treatment

5 UNEP, Green Hills, Blue Cities: An Ecosystems Approach to Water Resources Management for African Cities. A Rapid Response Assessment, UNEP, Nairobi 2011. 22

3.7.4 Storage of Drinking water Storing water is a good survival skill to learn as it is our planet’s most precious resource and should never be wasted. In addition, it is important to have for drinking, making food and personal hygiene. Out of the sampled households across the county over 92% were storing their drinking water in a closed container preventing it from contamination. 3.7.5. Payment of Water and Consumption With regard to water payment, 36.9% (237) of the respondent pay for water in Tana River County. Of those who pay for water, 43.5% pay per 20l Jerri can and the rest on a monthly basis. According to the sphere standards a household members is required to consume at least 15 litres per day.6 In terms of consumption, only 38.9% of the population in Tana River consume more than 15 litres per day per Person. 3.7.6 Hand washing Hand washing with soap is one of the most effective and inexpensive interventions for preventing diarrheal diseases and pneumonia, which together account for 3.5 million child deaths annually worldwide.7 Hand washing is important for good health. Effective washing can be practiced with alternatives to soap and using a variety of different hygienic facilities. Overall, interventions to promote hand washing might save a million lives a year. Each person should be able to wash hands with water and soap after toilet use, before food preparation, before eating and after cleaning babies. With regard to hand washing, around 79.9% of the respondent in Tana River County were aware of hand washing practices. When hand washing with soap is carried out properly at the four critical times, it breaks key contamination routes. This includes contact with an object or food that eventually goes into one’s mouth. Contamination refers to the transmission of disease-causing germs from one human to another or via contact with human or animal faeces. (A single gram of human faeces can contain up to one trillion germs, (Franks, et.al. 1998) .Adults and children who practice proper hand washing will enjoy direct health benefits and other benefits. Hand washing at 4 critical times, the practice was poor with only 33.1% reporting to have washed their hands at the critical times. 8 Hand washing with soap is one of the most effective and inexpensive interventions for preventing diarrheal diseases and pneumonia, which together account for 3.5 million child deaths annually worldwide (Cairncross & Valdmanis, 2006). The survey indicated that 67.6% of the households were using soap and water for hand washing. Hand washing without soap does not offer effective protection against germs.

Table 18: Hand washing

Indicator n Percent Aware of Hand washing Yes 513 79.9%

6 SPHERE hand book 7 Cairncross, S. and Valdmanis V. (2006) Chapter 41: Water Supply, Sanitation, and Hygiene Promotion. In D.T. Jamison, J.G. Breman, A.R. Measham, et al. (Editors), Disease Control Priorities in Developing Countries, 2nd edition (771-792). Washington (DC): World Bank. 8 People wash their hands with soap at four critical times: after defecation, after changing diapers, before preparing food, and before eating 23

When do you wash your hands After Toilet 457 89.1% Before cooking 323 63.0% Before Eating 481 93.8% After taking children to the toilet 226 44.1% Hand washing with Soap and water Yes 347 67.6% Hand washing at 4 Critical times 170 33.1%

3.7.7 Sanitation Facilities Ownership and Accessibility People with at least basic sanitation services are considered to have safely managed sanitation services if the excreta from their homes is transported through sewers and treated off-site. Poor management of excreta is linked to transmission of diseases such as cholera, diarrhoea, dysentery, hepatitis A, typhoid and polio, and also contributes to malnutrition. Inadequate sanitation is estimated to cause 280 000 diarrhoeal deaths annually and is a major factor in several neglected tropical diseases, including intestinal worms, schistosomiasis, and trachoma. Proper sanitation facilities (for example, toilets and latrines) promote health because they allow people to dispose of their waste appropriately. Sanitation Facilities are classified as: • Improved sanitation, which include: • Flush toilet • Connection to a piped sewer system • Connection to a septic system • Flush / pour-flush to a pit latrine • Pit latrine with slab • Ventilated improved pit latrine (abbreviated as VIP latrine) • Composting toilet • Unimproved Sanitation which include: • Public or shared latrine (meaning a toilet that is used by more than one household) • Flush/pour flush to elsewhere (not into a pit, septic tank, or sewer) • Pit latrine without slab • Bucket latrines • Hanging toilet / latrine • No facilities / bush / field (open defecation) If organic solid waste is not disposed of well, major risks are incurred due to fly breeding and surface water pollution, which is a major cause of diarrheal diseases. Solid waste often blocks drainage channels and leads to environmental health problems associated with stagnant and polluted surface water. Analysis of relieving points revealed that, most household are still relieving themselves in bushes and other open places. Open defecation was practiced by 50.6% of the households as indicated in figure below.

Table 19: Sanitation Facilities

Indicator n Percent Sanitation Facilities used Flush to Pit latrine 5 0.8% Flush to piped sewer system 8 1.2% Flush to septic tank 3 0.5% Ventilated Improved Pit Latrine 8 1.2% Pit latrine with slab 168 26.2% Pit latrine without slab/open pit 115 17.9% No facility /Bush/field 325 50.6% Composting Toilet 1 0.2% Hanging Toilet/Hanging Latrine 8 1.2% Bucket 1 0.2%

3.8 FOOD SECURITY 3.8.1 Dominant foods and food groups consumed by households and women In assessing the nutritional quality and quantity of the food consumed by the survey population, 24 hour household dietary diversity questionnaire was administered that would also help to determine the households’ economic capacity to consume various foods in the sub-counties. In the entire county the five main foods consumed 24 hours prior to the survey were cereal and cereal products (87.9%), oil (90.3%), sweets (84.3%), Condiments (73.2%) and Vegetables (63.4%). The least consumed are eggs (1.9%) followed by fruits (8.9%) and then meat (14.8%).

Condiments, 73.2% Sweets: 84.3% Oils/fats 90.3% Milk and milk products 46.1% Pulses/legumes, nuts 43.1% Fish 29.6% Eggs 1.9% Meat 14.8% Fruits 8.9% Vegetables 63.4% White tubers and roots product 15.9% Cereals and cereal products 87.9%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Figure 14: Food groups consumed by the household within 24 hour Recall Period

Women of reproductive age (WRA)9 are often nutritionally vulnerable because of the physiological demands

9 For the purposes of this document and indicator, WRA are defined as those 15–49 years of age. 25 of pregnancy and lactation. Requirements for most nutrients are higher for pregnant and lactating women than for adult men10. Outside of pregnancy and lactation, other than for iron, requirements for WRA may be similar to or lower than those of adult men, but because women may be smaller and eat less (fewer calories), they require a more nutrient-dense diet 11 Insufficient nutrient intakes before and during pregnancy and lactation can affect both women and their infants. Yet in many resource poor environments, diet quality for WRA is very poor, and there are gaps between intakes and requirements for a range of micronutrients12. In assessing the nutritional quality and quantity of the food consumed by the surveyed women of reproductive age, a 24-hour recall period household dietary diversity questionnaire was administered and consumption of 10 food groups is depicted in the table below. In the County, WRA mainly consume three major food groups: All starchy staple foods (94.4%), Beans and pulses (67.3%) and other vegetables (57.5%). The least consumed by WRA are Nuts and seeds (2.6%), other fruits (4.5%) and eggs (5.1%).

Other fruits 4.5% Other Vegetables 57.5% Other Vitamin A rich vegetables and fruits 11.7% Vitamin A rich dark green leafty Vegetables 43.5% Eggs 5.1% Flesh foods 34.2% Dairy (Milk) 46.8% Nut and seeds 2.6% Beans and peas 67.3% All starchy staple foods 94.4%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Figure 15: Food consumed by Women of Reproductive Age 3.8.2 Minimum Household Dietary Diversity (HHDS) Household dietary diversity Score (HDDS) is a qualitative measure of food consumption that reflects household access to a variety of foods. It is not meant to be used in accessing dietary diversity at individual level (FAO, 2010). Minimum Household Dietary Diversity is indicator of whether or not a household has consumed at least three out of twelve defined food groups within the last 7 days. At least more than 53.6% of the household surveyed had consumed more than 5 food groups in Tana River County. 42.2% of them consumed 3 to 5 food groups.

10 National Research Council, 2006; World Health Organization [WHO]/Food and Agriculture Organization of the United Nations [FAO], 2004 11 “Nutrient density” refers to the ratio of nutrients (such as vitamins and minerals) to the energy content of foods. 12 Arimond et al., 2010; Lee et al. 2013 26

4.2%

53.6% 42.2%

<3 Food Groups 3 to 5 food groups >5 food groups

Figure 16: Minimum Household Dietary Diversity

The poor quality of the habitual diet and the lack of dietary diversity in much of the developing world contribute to micronutrients deficiencies. Micronutrient malnutrition is a global problem much bigger than hunger and imposes enormous costs on societies in terms of ill health, lives lost, reduced economic productivity and poor quality of life. Addressing the global challenge of micronutrient malnutrition requires the need for many strategies – both short- and intermediate-term and long-term sustainable approaches. In addition to the conventional approaches of micronutrient supplementation and fortification, promoting sustainable food based approaches to enable adequate intakes of micronutrients by much of the population includes dietary diversification strategies and agriculture-based approaches. Dietary diversification is possible by promotion of homestead food production, which includes home gardening, small livestock rearing and fishing as well as the processing and preservation of food. Agriculture and agricultural biotechnology offer the opportunity of increasing crop yields and have the potential to improve the micronutrient content of staple foods and cereal crops, thus contributing to better nutrition of populations and thereby helping to achieve nutrition security. By ensuring food and nutrition security and by reducing the widespread problem of micronutrient malnutrition we may hope to achieve the targets set for the Sustainable Development Goals. An analysis of micronutrient intake showed a serious deficit in meeting the recommended daily allowances as shown in figure below. The intake of Vitamin A and Iron rich foods was very poor.

100.0% 3.4% 90.0% 22.9% 9.7% 80.0% 70.0% 62.8% 60.0% 79.6% 80.5% 43.8% 85.0% 50.0% 40.0% 86.9% 30.0% 15.1% 20.0% 33.3% 10.0% 19.8% 17.0% 22.1% 9.8% 0.0% 0.6% 2.5% 5.1% STAPLES PROTEIN FRUITS &VEGES Iron Vitamin A Oils/Fats

None Some(1-5 Days) Frequent(6-7Days)

Figure 17: Household Consumption of micro nutrient foods

3.8.3 Women Dietary diversity score Women of reproductive age (WRA) are often nutritionally vulnerable because of the physiological demands of pregnancy and lactation. Requirements for most nutrients are higher for pregnant and lactating women than for adult men (National Research Council, 2006), World Health Organization [WHO]/ Food and Agriculture Organization of the United Nations (FAO, 2016). Outside of pregnancy and lactation, other than for iron, requirements for WRA may be similar to or lower than those of adult men, but because women may be smaller and eat less (fewer calories), they require a more nutrient-dense diet (Torheim and Arimond, 2013). Insufficient nutrient intakes before and during pregnancy and lactation can affect both women and their infants. Yet in many resource-poor environments, diet quality for WRA is very poor, and there are gaps between intakes and requirements for a range of micronutrients (Arimond ,et al. 2010; Kavle, 2017). MDD-W13 is a dichotomous indicator of whether or not women 15-49 years of age have consumed at least five out of ten defined food groups the previous day or night. The proportion of women 15–49 years of age who reach this minimum in a population can be used as a proxy indicator for higher micronutrient adequacy, one important dimension of diet quality. The indicator constitutes an important step towards filling the need for indicators for use in national and subnational assessments. It is a population-level indicator based on a recall period of a single day and night, so although data are collected from individual women, the indicator cannot be used to describe diet quality for an individual woman. This is because of normal day-to-day variability in individual intakes. At the County only 28.3% of the WRA are taking 5 or more food groups.

13 Additional background on the indicator is available at: http://www.fantaproject.org/monitoring-and-evaluation/ minimum-dietary-diversity- women-indicator-mddw.

Women Dietary Diversity Score

28.3%

< 5 Food groups 5 and more food groups

71.7%

Figure 18: Women Dietary Diversity Score 3.8.4 Food Consumption Score Classification The food consumption score is an acceptable proxy indicator to measure caloric intake and diet quality at household level, giving an indication of food security status of the household. It’s a composite score based on dietary diversity, food frequency and relative nutritional importance of different food groups. Food consumption score classifies households in to 3 categories namely: poor, borderline and acceptable (FAO, 2010). In Tana River County, 90.8% of the household surveyed had acceptable food consumption Score, 7.2% had borderline and 2.0% had poor consumption score. This is as shown in the figure below: According to the NDMA bulletin for the Month of February 2020, there was higher proportion of households with poor food consumption gaps in Pastoral (50.8%) and mixed farming livelihood zones (42.6%). The proportion of households with borderline food consumption score was high in mixed farming livelihood zones at 16.7% and lowest in marginal mixed farming livelihood zones at 11.1%. A proportion of 88.9%, 63.3% and 50% of the households across marginal mixed, mixed and pastoral livelihood zones have acceptable food consumption score respectively.

Good Food Consumption 90.8%

Border Food Consumption 7.2%

Poor Food Consumption 2.0%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Figure 19: Food Consumption Score

3.8.5 Food Consumption Score –Nutrition WFP’s key corporate indicator for measuring food insecurity is the Food Consumption Score (FCS) used to define categories of household (HH) food insecurity. The information gathered to develop the FCS additionally provides a wealth of unexploited data that can be used to inform on nutrient rich groups consumed by the HH and which are essential for nutritional health and well-being: protein, iron and vitamin A. All macronutrients (carbohydrates, proteins and lipids) and micronutrients (vitamins and minerals) are important to ensure a healthy life, and all nutrients should be represented in a sufficient quantity for a balanced diet. Macronutrients are good sources of energy. A lack in energy quickly leads to acute under nutrition. An insufficient intake of protein (essential for growth) is a risk for wasting and stunting. It also has an impact on micronutrient intake as protein foods are rich sources of vitamins and minerals. Deficiencies in micronutrients, such as vitamin A and iron, over a long period, lead to chronic under nutrition. Iron deficiency leads to anaemia and Vitamin A deficiency leads to blindness and interferes with the normal functioning of the immune system, growth and development as well as reproduction. This tool chooses to focus on three key nutrients; Protein, Vitamin A and Iron (hem iron) primarily for their nutritional importance but also those foods rich in these nutrients can be easily grouped from food consumption data. With regard to Food consumption Score Nutrition, among the household surveyed in Tana River County, 76.6% consumed protein rich foods, 15.4% consumed Vitamin A rich foods and 27.4% consumed Hem Iron rich foods for 7 days. 42.5% of the household surveyed consumed Vitamin A and 30.4% consumed Hem Iron Foods for 0 days. 100.0% 90.0% 42.2% 15.4% 80.0% 70.0% 60.0% 30.4% 50.0% 42.1% 40.0% 76.6% 30.0% 20.0% 42.5% 10.0% 20.9% 0.0% 2.5% 0 Days 1-6 Days 7 Days Protein Rich foods Vit A rich Foods Hem Iron Rich Foods

Figure 20: Frequency Consumption of protein, Vitamin A rich foods and Hem Iron Rich Foods

In terms of average number of days micronutrient are consumed in a household, the major micronutrient consumed in Tana River County were protein, staples and oil/fats which were consumed over 5 days in a week. The least consumed was Vitamin A, which was consumed for 1 day in a week. These results explain the deficiency in dietary micronutrient intake among households.

7 6.2 6.2 6.3 6 4.8 5

4 2.9 3

1 0.5

0 STAPLES PROTEIN FRUITS &VEGES Iron Vitamin A Oils/Fats

Figure 21: Number of days in a week micronutrient rich foods was consumed

3.9 Coping strategy Index The Coping Strategy Index (CSI), a tool developed by the World Food Programme, is commonly used as a proxy indicator for access to food14 and change in the consumption patterns of a given household. For each coping strategy, the frequency score (0 to 7) is multiplied by the universal severity weight. A weighted score allows one to measure the frequency and severity of coping strategies. Data is collected on the number of days in the last seven days a household used a specific coping strategy due to a shortage of food and/or income. The average CSI for Tana River was 10.14, an indication that the sampled households were food insecure and still engaging in different survival tactics. According to February 2020 NDMA bulletin, households in marginal mixed livelihood zone employed most coping strategies at 18.0 followed by pastoral at 13.5.The mixed farming livelihood zones employed least coping mechanisms at 8.3. Table 20: Coping Strategy Index

Weighted Percentage of HH(346) Frequency score (0-7) Severity score (1-3) score=Freq*weight Rely on less preferred and less expensive foods 2.04 1 2.04 Borrow food, or rely on help from a friend or relative 0.8 2 1.6 Limit portion size at mealtimes 1.8 1 1.8 Restrict consumption by adults in order for small children to eat 0.8 3 2.4 Reduce number of meals eaten in a day 2.3 1 2.3 10.14

3.10 Food Fortification Fortification is adding vitamins and minerals to foods to prevent nutritional deficiencies. The nutrients regularly used in grain fortification prevent diseases, strengthen immune systems, and improve productivity and cognitive development. Wheat flour, maize flour, and rice are primarily fortified to:

14 ‘Access to food’ is just one of the three pillars of food security. Other pillars include, ‘food availability’ and ‘food utilization’. 31

• Prevent nutritional anaemia • Prevent birth defects of the brain and spine • Increase productivity • Improve economic progress Food fortification was identified as the second strategy of four by the WHO and FAO to begin decreasing the incidence of nutrient deficiencies at the global level.15 As outlined by the FAO, the most common fortified foods are cereals (and cereal based products), milk (and milk products), fats and oils, accessory food items, tea and other beverages, and infant formulas.16 Undernutrition and nutrient deficiency is estimated globally to cause between 3 and 5 million deaths per year. With regard to the survey, only 17.9% (115)) of the households in Tana River County had heard/learnt about food fortification with most hearing through radio (43.5%) followed by through a TV show at 29.6%. With regard to sign of fortification, 70.4% (81) knew about it.

15 World Health Organization and Food and Agriculture Organization of the United Nations Guidelines on food fortification with micronutrients. Archived 26 December 2016 at the Wayback Machine. 2006 [cited on 2011 Oct 30]. 16 Micronutrient Fortification of Food: Technology and Quality Control Archived 2 September 2016 at the Wayback Machine 32

CHAPTER FOUR: CONCLUSION AND RECOMMENDATIONS 4.1 Conclusion Overall the nutrition status of children in Tana River County was classified to be in phase 2 (Serious) according to IPC classification for acute malnutrition with a GAM of 13.1% (9.9-17.0) and SAM of 2.7% (1.5- 4.8). The situation remained the same compared to 2019 where the GAM was 14.8 % (11.7 - 18.4). Stunting rate in 2020 was 24.5% (20.5-28.9) which also remained the same compared to 2019 at 21.7 %( 18.2 - 25.8). Underweight in 2020 was 23.6% (19.4-28.3) also remained the same compared to 2019 at 23.3 % (19.8 - 27.2. According to the February 2020 SRA report, Tana River County has generally improved to Stressed (IPC Phase 2). The Pastoral Livelihood Zone and the Mixed Farming Livelihood Zone are classified as Stressed Phase (IPC Phase 2) while the Marginal Mixed Farming Livelihood Zone is classified as Crisis Phase (IPC Phase 3). In terms child morbidity, 35.2% of the children were ill based on two weeks recall period, most children had ARI at 69.8% followed by fever at 36.9%. In Tana River County, 80.9% of the children aged 6-59 Months were supplemented with Vitamin A once which is slightly above the national target while 49.8% were supplemented twice. On deworming, 74.1% of the children aged 12-59 months were dewormed which is below the national target of 80%. On measles at 9 months, 93.1% of the children aged 9-59 months were vaccinated while 77.5% children aged 18-59 months were vaccinated the second dose of measles. On water and sanitation, 79.9% of the household interviewed were aware of hand washing but only 33.1% washed hands at 4 critical times which include: after toilet, before cooking, before eating and after taking children to the toilet. In terms of hand washing with soap, 67.6% of the household interviewed reported to be using soap while washing hands. Most people (50.6%) in Tana River County have no toilet/latrine facility which is dangerous for the community especially during rainy season when diarrhoea cases increases. On food security, 53.6% of the household consumed more than 5 food groups, with the major food consumed being: Cereals and cereal products, Oils/fats, Condiments, Sugary foods and vegetables. On food consumption score, 90.3% of the household interviewed had good food consumption score. Maternal nutrition status based on MUAC measurement among all women of reproductive age and pregnant and lactating women with the two categories having MUAC of <21cm at 3.7% and 3.9% respectively. Average IFAS consumption mean number of days FeFo was consumed was found to be 64.7 days out of the minimum required days of 180. More advocacy on FeFo utilization is needed to help increase the uptake. On women dietary diversity, only 28.3% of the women of the reproductive age consumed 5 or more food groups. In conclusion it was noted that key drivers of poor nutritional status in Tana River County include; chronic food insecurity, inadequate dietary diversity, Poor access to safe water, Poor hygiene and sanitation practices. 4.2 Recommendation

Table 21: Recommendation

Findings Recommendations Timelines Actors (By Who)M

GAM rate of • Establish a Multi-sectoral platform for high level July 2020 13.1% advocacy and coordination of nutrition activities MOH/TRCG/KRCS/U both sensitive and specific and advocate for NICEF/WVK recruitment of more nutritionist to help boost nutrition service delivery. • Develop a joint plan of action with all other nutrition sensitive departments to ensure a multi sectoral approach in addressing malnutrition in the county • Active case findings at the community and Nutrition surveillance. • Scale up of IMAM surge activities at health facilities implementing IMAM. • Continued scale up of MIYCN activities (BFCI and BFHI) as well as IMAM activities • Conduct integrated medical outreaches • Provide nutrition commodities in all facilities offering IMAM services to avoid stock outs • Integrate nutrition commodity supply chain pipeline 50.6% of the • Sensitize communities on WASH through the MOH/TRCG/KRCS/ October 2020 population local radio stations UNICEF/WVK practice OD • Sensitize schools on WASH through school health clubs • Scale up CLTS activities in all the CUs within the county • Support PHOs to enforce construction and use of latrines at the community • Certify OD villages in the county 33% practice • Sensitize the community on importance of MOH,TRCG/KRCS/ August 2020 hand washing hand washing in 4 critical times UNICEF/WVK in 4 critical • Use local FM radio to sensitize the community times on hand washing • Train CHV on hygiene and sanitation • Sensitize schools on importance of hand washing in 4 critical times • Provision of hand washing facilities to schools and other institutions

1.9% of • Sensitize the communities of importance of MOH,TRCG/KRCS/ Sept 2020 pregnant consuming IFAS during pregnancy through UNICEF/WVK women media. consume IFAS • Train health care providers on IFAS guidelines for >180 days • Conduct an operational research on IFAS adherence • Sensitize CHVs on IFAS • Household monitoring of pregnant mothers consuming IFAS to ensure adherence • Ensure constant supply of IFAS tablets to avoid stock outs. Vitamin A • Sensitize the community on the importance of MOH,TRCG/KRCS/ Nov 2020 supplementati Vitamin A supplementation and deworming as UNICEF/WVK on 12 to 59 well as scale up VAS interventions within months (2 ECDE, Duks and at the community doses)-46.3% • Use of radio to sensitize the community

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3. WHO e- library of evidence of nutrition action (E LENA); zinc supplementation in management of diarrhea

4. Kenya policy guidelines on control and management of diarrhea diseases in children below 5 years in Kenya (March 2010)

5. Kenya national guidelines on immunization (2013)

6. WHO guideline: Vitamin A supplementation in infant and children 6 to 59 months of age, Geneva, World Health Organization 2011.

7. UNICEF (2007), Vitamin A supplementation; A decade of progress.

8. Ministry of Health (2013), maternal, infant and young child nutrition; National operation guideline for health workers

9. The SPHERE project (2004), Humanitarian charter and minimum standards in disaster response

10. FAO (2010); guidelines for measuring household and individual dietary diversity.

11. WFP (2015), Food Consumption Score, Nutrition Quality Analysis (FCS-N)

12. FAO and FHI 360, 2016. Minimum Dietary Diversity for Women: A guideline for measurement. Rome: FAO

13. KFSSG (2020), Short Rain Assessment, Tana River County.

14. Tana River County SMART Survey (February 2019)

APPENDICES Appendix 1: Overall Score of the Survey Indicator Acceptable Tana River values/range

Flagged data (% of out of range subjects) <7.5 0(1.2%)

Overall sex ratio (significant CHI square) >0.001 0 (p=0.743)

Age ratio (6-29vs 30-59) Significant CHI square >0.001 4 (p=0.013)

Dig. prevalence score-weight <20 0 (2)

Dig. prevalence score-height <20 0 (5)

Dig. prevalence score-MUAC <20 0 (5)

Standard Dev. Height WHZ >0.80 0 (0.99)

Skewness WHZ <±0.6 0 (-0.10)

Kurtosis WHZ <±0.6 0 (-0.06)

Poisson WHZ -2 >0.001 1 (p=0.028)

OVERALL <24 5% (Excellent)

Appendix 2: Sampled Villages

SUB - COUNTY Ward VILLAGE Cluster Number TANA DELTA GARSEN WEST BILISA A 39 TANA DELTA GARSEN WEST HAMESA A 34 TANA DELTA GARSEN WEST CHIRA A 35 VI SHIRIKISHO BULA WACHU TANA NORTH HIRIMANI /V 2 7 TANA NORTH HIRIMANI BULA MARARA/TYPE CDEF 6 GALOLE CHEWANI MALINDI YA NGWENA'A' 13 GALOLE CHEWANI KALAULE 14 GARSEN TANA DELTA CENTRAL DANISA A 25 GARSEN TANA DELTA CENTRAL BANDI 26 GARSEN TANA DELTA CENTRAL DUMI B 27 TANA NORTH CHEWELE WADESA DAM 5 TANA NORTH CHEWELE CHARIDENDE 3

GALOLE KINAKOMBA Bulla/Vukoni Juu 16 GALOLE KINAKOMBA Kipendi 18 TANA DELTA GARSEN SOUTH IDSOWE 31 TANA DELTA GARSEN SOUTH DIDA ADE 2 32 TANA DELTA GARSEN SOUTH TARASAA MAIN 33 TANA NORTH CHEWELE BAWAMA 4 TANA NORTH MADOGO ANOLE 10 GALOLE WAYU WALDENA TC DAMSA 22 GALOLE WAYU ANABU /ELBOKA TOKOCHI 23 TANA DELTA KIPINI WEST CHAMWANAMUMA 40 TANA DELTA KIPINI WEST SHIRIKISHO 42 TANA DELTA KIPINI WEST KIKOMO 41 TANA NORTH SALA TALEO 12 TANA NORTH SALA SOMBO 11 GALOLE MIKINDUNI LAFUMA 20 GALOLE MIKINDUNI MKUYUNI 21 TANA DELTA GARSEN WEST Assa 36 GARSEN TANA DELTA CENTRAL GALILI 28 TANA DELTA GARSEN SOUTH GUBANI ORMA 37 TANA NORTH BANGALE HABACHO 1 TANA NORTH BANGALE MATAARBA 2 GALOLE WAYU Koticha/Moti Boka 24 GALOLE CHEWANI DAFWOMA 15 TANA DELTA GARSEN NORTH BAOMO 29 TANA DELTA GARSEN NORTH Maziwa A 30 TANA DELTA GARSEN NORTH SAILONI 38 TANA NORTH MADOGO MADOGO 'B' 8 TANA NORTH MADOGO CARLFONIA 'A' 9 GALOLE MIKINDUNI KONE B 19 GALOLE KINAKOMBA GAFURU 'B' 17

Appendix 3:Calendar of Events Appendix 3.1 Tana Delta Calendar of Events LOCAL CALENDER OF EVENTS TANA DELTA MONTH 2015 2016 2017 2018 2019 2020 JANUARY New Year/ KDF Opening of school/Nw Opening Drought/New New Elhadi Attack Year School/New Year 13 Year/Openin 49 37 Year/Animal g of school Migration 1 25

FEBRUAR Cholera Drought/Nurses Strike Long Drought Locust/ Y Outbreak 36 Rains/Maembe 12 Kamudhe 48 Season 24 Attack/Coro na Virus 0

MARCH Easter Holiday Easter Drought Floods Drought 59 47 35 Occurrence/Hand 11 shake 23

APRIL Garissa Uni Attack Death Of Lucy School Opening/Easter Cholera Easter 58 Kibaki 46 34 Bura/Easter/World 10 Cup 22 MAY Labour Day/Opening Labor Labor Day/ School Labor Ramadhan school Day/Measles Opening/Ramadhan Day/Ramadhan/Sch 9 57 Campaign 33 ool Opening 45 21

JUNE Madaraka Day Madaraka Day Idu - Fitr/Madaraka Madaraka Day/Idul- Ramadhan Idd 56 44 Day/Nurses Strike Fitr 20 8 32 39

JULY Idul - Fitr/Net Idul-Fitr/ Nurses Strike/ Idul-Fitr Polio Campaign Polio Distribution 55 Burning of 31 19 Campaign schools 7 43

AUGUST Sch Holiday/Harvest Beyond Zero Elections/Nurses School Idul Haji Season Idul Haji 42 strike/School Holiday Holiday/Idul- 6 54 30 Haji/Polio/Harvets 18

SEPTEMBE Opening of school Opening of Nurses strike/Opening School Tana River R 53 school of school Opening/Iddu - Cultural Day 41 29 Adhaa 17 /Idu-ADHAA 5

OCTOBER Mashujaa/KCPE KCPE/Mashuja Second KCPE/Mashujaa 4 52 a Day 40 Election/Mashujaa/KCP Day E 28 16

NOVEMBE KCSE/Pope Visit KCSE End of nurese KCSE Kalalani R 51 39 strike/KCSE 27 15 Destruction 3

DECEMBE Holiday/Jamhuri/Christ Holiday/Christ Christmas/Jamhuri/Holi Christmas/Jamhuri Floods/Christm R mas 50 mas 38 day 26 14 as 2

First check for date of birth on health cards, immunization cards, etc. If possible then calculate the exact age in months

Appendix 3.2 Tana North Calendar of Events

LOCAL CALENDER OF EVENTS TANA NORTH MONTH 2015 2016 2017 2018 2019 2020

JANUARY New Year/ KDF Opening of school/Nw Opening Drought/New New Elhadi Attack Year School/New Year 13 Year/Openin 49 37 Year/Animal g of school Migration 1 25

FEBRUAR Cholera Drought/Nurses Strike Long Drought Locust/ Y Outbreak 36 Rains/Maembe 12 Kamudhe 48 Season 24 Attack/Coro na Virus 0

MARCH Easter Holiday Easter Drought Floods Drought 59 47 35 Occurrence/Hand 11 shake 23

JUNE Madaraka Day Madaraka Day Idu - Fitr/Madaraka Madaraka Day/Idul- Ramadhan Idd 56 44 Day/Nurses Strike Fitr 20 8 32

JULY Idul - Fitr/Net Idul-Fitr/ Nurses Strike/ Idul-Fitr Polio Campaign Polio Distribution 55 Burning of 31 19 Campaign schools 7 43

AUGUST Sch Holiday/Harvest Beyond Zero Elections/Nurses School Idul Haji Season Idul Haji 42 strike/School Holiday Holiday/Idul- 6 54 30 Haji/Polio/Harvets 18

SEPTEMBE Opening of school Opening of Nurses strike/Opening School Tana River R 53 school of school Opening/Iddu - Cultural Day 41 29 Adhaa 17 /Idu-ADHAA 5

OCTOBER Mashujaa/KCPE KCPE/Mashuja Second KCPE/Mashujaa 4 52 a Day 40 Election/Mashujaa/KCP Day E 28 16

NOVEMBE KCSE/Pope Visit KCSE End of nurese KCSE Kalalani R 51 39 strike/KCSE 27 15 Destruction 3

DECEMBE Holiday/Jamhuri/Christ Holiday/Christ Christmas/Jamhuri/Holi Christmas/Jamhuri Floods/Christm R mas 50 mas 38 day 26 14 as 2

First check for date of birth on health cards, immunization cards, etc. If possible then calculate the exact age in months

Appendix 3.3 : Galole Calendar of events LOCAL CALENDER OF EVENTS GALOLE MONTH 2015 2016 2017 2018 2019 2020 JANUARY New Year Opening of school/Nw Opening School/New Drought/New New Year 49 Year Year/Animal Year 13 1 37 Migration 25

FEBRUARY 48 Drought Long Rains/Maembe Drought 0 36 Season 24 12

MARCH 59 Easter Drought Floods Drought 47 35 Occurrence/Hand 11 shake 23

APRIL Garissa Attack 46 School Opening/Easter Cholera Easter 58 34 Bura/Easter/World 10 Cup 22 MAY Labour Day Labor Day Labor Day/ School Labor Ramadhan 57 45 Opening/Ramadhan Day/Ramadhan/Scho 9 33 ol Opening

JUNE Madaraka Day Madaraka Day Idu - Fitr/Madaraka Madaraka Day/Idul- Ramadhan Idd 56 44 Day/Nurses Strike Fitr 20 8 32

JULY Idul - Fitr/Net Idul-Fitr/ Nurses Strike/ Idul-Fitr Polio Campaign 7 Distribution 55 Burning of 31 19 schools 43

AUGUST Sch Beyond Zero Idul Elections/Nurses School Holiday/Idul- Idul Haji Holiday/Harvest Haji 42 strike/School Holiday Haji/Polio/Harvets 6 Season 30 18

Opening of Opening of Nurses strike/Opening of Tana River SEPTEMBE school school school Cultural Day R 53 41 29 5 OCTOBER Mashujaa/KCPE KCPE/Mashujaa Second KCPE/Mashujaa Day 4 52 Day 40 Election/Mashujaa/KCPE 16 28

NOVEMBE KCSE/Pop John KCSE End of nurese KCSE Kalalani R 51 39 strike/KCSE 27 15 Destruction 3

DECEMBER Mango Holiday/Christm Christmas/Jamhuri/Holid Christmas/Jamhuri Floods/Christm Season/Christm as 38 ay 26 14 as 2 as 50

First check for date of birth on health cards, immunization cards, etc. If possible then calculate the exact age in months

Appendix 4: Questionnaire 1.IDENTIFICATION 1.1 Data Collector______1.2 Team Leader______1.3 Survey date (dd/mm/yy)------1.4 County 1.5 Sub 1.6 Ward 1.7 Location 1.8 Sub- 1.9 Village 1.10 Cluster No 1.11 HH No 1.12 Team No. County Location

1.13 Latitude Longitude Household ______geographical coordinates 2. Household Demographics 2.1 2.2a 2.2b 2.3 2.4 2.5 2.6 2.7a 2.7b 2.8 2.10 Age Please give me Please Age (Record Childs Sex If between 3 and Main reason 2.7a, What What is the If the Group the names of the indicate age in age 18 years old, Is for not is the child highest household persons who the MONTHS for verified 1= Male the child attending doing when level of usually live in household children <5yrs by attending school not in education owns your household. head (write and YEARS for 2= school? (Enter one school? attained?(le mosquito HH on the those ≥ 1=Health Female code from vel net/s, who member’s 5 years’s) card list) 1=Working completed) slept column) 2=Birth 1=Chronic on family From 5 yrs certificate 1 = Yes Sickness farm and above under the Year Month / 2 = No 2=Weather 2=Herding mosquito s s notificatio (If yes go to 2.8; If (rain, floods, Livestock 1 =Pre net last n no go t o 2.7) storms) 3=Working primary night? 3=Baptis 3=Family for payment 2= Primary m card labour away from 3=Secondar (Probe- 4=Recall responsibilities home y enter all 5. other 4=Working 4=Left home 4=Tertiary responses ______outside home for 5= None mentioned specify 5=Teacher elsewhere 6=others(spe absenteeism/l 5=Child cify) (Use 1 if ack of living on the Go to “Yes” 2 if teachers street question to “No and 3 if 6= Fees or 6: Other not costs specify 2.9 ↓ 7=Household ______applicable) doesn’t see go to value of question schooling 2.11 8 =No food in the schools 9 = Migrated/ moved from school area (including displacements ) 10=Insecurity/ violence 11-No school Near by 12=Married 13. Pregnant/ taking care of her own child 13=others (specify)…… …………….. < 5 YRS 1 2 3 4 >5 TO <18 5 YRS 6

8 9 10 11 12 ADULT (18 13 years and 14) above) 15 16

2.9 How many mosquito nets does this household have? ______(Indicate no.) go to question 2.10 before proceeding to question 2.11 2.11 Main Occupation of the Household Head – HH. 2.12. What is the main current source of income of the household? (enter code from list) 1. =No income 1=Livestock herding 2=Own farm labour 2. = Sale of livestock 3=Employed (salaried) 3. = Sale of livestock products 4=Waged labour (Casual) 4. = Sale of crops 5=Petty trade 5. = Petty trading e.g. sale of firewood 6=Merchant/trader 6. =Casual labor 7=Firewood/charcoal 7. =Permanent job 8=Fishing 8. = Sale of personal assets 9= Income earned by children 9. = Remittance

10=Others (Specify) 10. Other - Specify |____| |____| 2.13 Marital status of the respondent 2.14. What is the residency status of the household? 1. = Married 2. = Single 1. IDP 3. = Widowed 2.Refugee 4. = separated 3. Resident |____| 5. = Divorced. |____| 2.15 Are there children who have come to live with you recently? 2.15b If yes, why did the child/children come to live with you? 1. YES 2. NO 1= Did not have access to food 2=Father and Mother left home 3=Child was living on the street, 4=Care giver died 5= Other specify ______

Fever with Malaria: Cough/ARI: Any episode Watery diarrhoea: Any Bloody diarrhoea: Any High temperature with severe, persistent episode of three or more episode of three or more with shivering cough or difficulty watery stools per day stools with blood per day breathing 3. 4. 5. CHILD HEALTH AND NUTRITION (ONLY FOR CHILDREN 6-59 MONTHS OF AGE; IF N/A SKIP TO SECTION 3.6) Instructions: The caregiver of the child should be the main respondent for this section 3.1 CHILD ANTHROPOMETRY 3.2 and 3.3 CHILD MORBIDITY (Please fill in ALL REQUIRED details below. Maintain the same child number as part 2) A B C D E F G H I J K 3.2 a 3.2 b 3.3 a 3.3 b 3.3 c Child No. what is the SEX Exact Age in Weight Height Oedema MUAC Is the If yes to Has your If YES, which When the child If the response If the child had relationship Female Birth months (KG) (CM) Y= Yes (cm) child in questio child illness (multiple was sick did you is yes to watery diarrhoea in of the …...F Date XX.X XX.X N= No XX.X any n J. (NAME) responses seek question # 3.2 the last TWO (2) respondent nutrition which been ill in possible) assistance? where did you WEEKS, did the with the Male program nutrition the past 1 = Fever with 1.Yes seek child get: child/childr …..….M 1. Yes progra two chills like 2. No assistance? 1. ORS en 2. No m? weeks? malaria (More than one 2. Zinc 1=Mother 1.OTP 2 = ARI /Cough response supplementatio 2=Father If no skip 2.SFP 1.Yes 3 = Watery possible- n? 3=Sibling to 3.BSFP 2. No diarrhoea 1. Traditional Show sample and 4=Grandmot question Other 4 = Bloody healer probe further for this her s 3.2 Specify If No, skip diarrhoea 2.Community component 5=Other ______to 3.4 5 = Other health worker check the remaining (specify) (specify) 3. Private clinic/ drugs(confirm from mother child booklet) See case pharmacy definitions 4. Shop/kiosk above 5.Public clinic 6. Mobile clinic 7. Relative or friend 8. Local herbs 9.NGO/FBO 01

3.4 Maintain the same child number as part 2 and 3.1 above

A1 A2 B C D E F G H I Child How many Has the How many If Vitamin A FOR Has the child Has child Has child Has child Has child No. times has child times did received CHILDREN received BCG received OPV1 received OPV3 received received the child received the child how many 12-59 vaccination? vaccination vaccination? measles second received vitamin A receive times in the MONTHS Check for BCG vaccination at 9 measles Vitamin A supplement vitamin A past one scar. 1=Yes, Card 1=Yes, Card months vaccination (18 in the past in the past capsules year did the How many 2=Yes, Recall 2=Yes, Recall (On the upper to 59 months ) year? 6 months? from the child times has 1 = scar 3 = No 3 = No right (On the upper (show facility or receive child 2=No scar 4 = Do not know 4 = Do not know shoulder)? right sample) out reach verified by received shoulder)? Card? drugs for 1=Yes, Card worms 2=Yes, Recall 1=Yes, Card in the past 3 = No 2=Yes, Recall year? 4 = Do not 3 = No (show know 4 = Do not Sample) know 01

3.5 MNP Programme Coverage. Maintain the same child number as part 2 and 3.1 above. Ask all the relevant questions (3.5.1 to 3.6.4) before moving on to fill responses for the next child. THIS SECTION SHOULD ONLY BE ADMINISTERED IF MNP PROGRAM IS BEING IMPLEMENTED OR HAS BEEN IMPLEMENTED

3.5 Enrolment in an MNP program 3.6 Consumption of MNPs 3.5.1. 3.5.2 3.6.1 3.6.2 3.6.3 3.6.4 Is the child enrolled in the MNP If the child, 6-23months, is not enrolled for Has the child If yes, how frequent do you give If no, since when did you What are the reasons to stop program?(show the example of MNP, give reason. (Multiple answers consumed MNPs MNP to your child? (record the stop feeding MNPs to your feeding your child with MNPs? the MNP sachet) possible. Record the code/codes in the in the last 7 code in the respective child’s child? (record the code in (Multiple answers possible. (record the code in the respective child’s number. DO NOT days?(shows the number) the respective child’s Record the code/codes in the respective child’s number) READ the answers) MNP sachet) number) respective child’s number. DO (record the Every day ……...... ……….1 NOT READ the answers) Yes =1 Do not know about MNPs …...... ………1 code in the Every other day ...... ….……..2 1 week to 2 weeks ago ....1 No=0 Discouraged from what I heard from respective Every third day ……...... ……..3 2 week to 1 month ago ....2 Finished all of the sachets ...... 1 others ……...... 2 child’s number) 2 days per week at any day ....4 More than 1 month ...... 3 Child did not like it ...... 2 If no go to 3.5.2, The child has not fallen ill, so have not Any day when I remember..…5 Husband did not agree to give to If yes go to section 3.6.1 gone to the health facility …. YES = 1 the child ...... 3 ….....…..3 N0= 0 Sachet got damaged ………….4 Health facility or outreach is far ….....…4 Child had diarrhea after being given Ch ild receiving therapeutic or If no skip to vitamin and mineral powder ……..5 supplementary foods ...... 5 3.6.3 Child fell sick...... 6 Other reason, specify ...…….....……….6 Forgot …………………….…..7 Child enrolled in IMAM program …8 Skip to 3.7 Other (Specify)______..9

Child 1

Child 2

Child 3

Child 4

MATERNAL NUTRITION FOR WOMEN OF REPRODUCTIVE AGE (15-49 YEARS)(Please insert appropriate number in the box) 3.7 3.8 3.9 3.10 3.11 Woman ID. What is the mother’s / Mother/ caretaker’s During the pregnancy of the If Yes, for how many days (all women in the HH caretaker’s physiological MUAC reading: (name of the youngest did you take? aged 15-49 years from status ____.__cm biological child below 24 the household 1. Pregnant months) did you take the ( probe and demographics – 2. Lactating following supplements? approximate the section 2 ) 3. not pregnant and not indicate lactating 1. Yes number of days ) 4. Pregnant and 2. No lactating 3. Don’t know 4. N/A

Iron Folic Combined Iron Folic Combined tablet acid iron and tablets acid iron and s folic acid syrup folic acid syrup supplement suppleme s nts

4.0 WATER, SANITATION AND HYGIENE (WASH)/- Please ask the respondent and indicate the appropriate number in the space provided 4.1 What is the MAIN source of drinking water for the 4.2 a What is the trekking distance to the current 4.2b – Who household NOW? main water source? MAINLY piped water 1=less than 500m (Less than 15 minutes) goes to fetch piped into dwelling ...... 11 2=more than 500m to less than 2km (15 to 1 hour) water at your piped to yard / plot ...... 12 3=more than 2 km (1 – 2 hrs) current main 4=Other(specify) water piped to neighbour ...... 13 |____| source? public tap / standpipe ...... 14 1=Women, tube well / borehole ...... 21 2=Men, 3=Girls, dug well 4=Boys protected well ...... 31 unprotected well ...... 32 spring protected spring ...... 41 unprotected spring ...... 42

rainwater ...... 51 tanker-truck ...... 61 cart with small tank ...... 71 water kiosk ...... 72 surface water (river, dam, lake, pond, stream, canal, irrigation channel) ...... 81

packaged water bottled water ...... 91 sachet water ...... 92

1. 4.2.2a How long do you queue for water? .3 Do you do anything to your water before drinking? 1. Less than 30 minutes (MULTIPLE RESPONSES POSSIBLE) (Use 1 if YES and 2 |____| 2. 30-60 minutes if NO). 3. More than 1 hour 1. Nothing 4. Don’t que for water 2. Boiling………… ……………………………………. 1. |____| 3. Chemicals (Chlorine,Pur,Waterguard)…………… |____| 4. Traditional herb……………………………………... |____| 5. Pot filters…………………………………………….. |____|

4.3a 6.

|____| 4.4 Where do you store water for drinking? 4.5 How much water did your household use YESTERDAY 1. Open container / Jerrican (excluding for animals)? 2. Closed container / Jerrican |____| (Ask the question in the number of 20 liter Jerrican and convert to liters & write down the total quantity used in liters) |____|

4.6 Do you pay for water? 4.6.1 If yes, how much per 20 liters 4.6.2 If paid per 1. Yes jerrican ______KSh/20ltrs month how much 2. No (If No skip to Question 4.7.1) |____| |____| 4.7.1a We would like to learn about where members of this 4.7.1b Is soap or detergent or ash/mud/sand present at the household wash their hands. place for handwashing? Can you please show me where members of your household most often wash their hands? YES, PRESENT ...... 1 Record result and observation. NO, NOT PRESENT ...... ……………………2

OBSERVED FIXED FACILITY OBSERVED (SINK / TAP) IN DWELLING ...... 1 IN YARD /PLOT...... 2 MOBILE OBJECT OBSERVED (BUCKET / JUG / KETTLE) ...... 3

NOT OBSERVED NO HANDWASHING PLACE IN DWELLING / YARD / PLOT ...... 4 NO PERMISSION TO SEE ...... 5

4.7.1 Yesterday (within last 24 hours) at what instances did you wash your hands? (MULTIPLE RESPONSE- (Use 1 if “Yes” and 2 if “No”) 1. After toilet……………………………………………………………………………………………………………… |____| 2. Before cooking………………………………………………………………………………………………………... |____| 3. Before eating…………………………………………………………………………………………………………. |____| 4. After taking children to the toilet……………………………………………………………………………………. |____| 5. Others…………………………………………………………………………………………………………………. |____|

4.7.2 If the caregiver washes her hands, then probe further; 4.8 What kind of toilet facility do members of your what did you use to wash your hands? household usually use? 1. Only water 2. Soap and water If ‘Flush’ or ‘Pour flush’, probe: 3. Soap when I can afford it Where does it flush to? 4. traditional herb |____| 5. Any other specify |____| If not possible to determine, ask permission to observe the facility.

flush / pour flush flush to piped sewer system 11 flush to septic tank 12 flush to pit latrine 13 flush to open drain 14 flush to DK where 18 pit latrine ventilated improved pit latrine 21 pit latrine with slab 22 pit latrine without slab / open pit 23

composting toilet 31

bucket 41 hanging toilet /

hanging latrine 51 no facility / bush / field 95

1. OTHER (specify) 96

5.0: Food frequency and Household Dietary Diversity

*Type of food* Did members of your If yes, mark days the food was consumed in the last 7 days? What was the main household consume source of the WOMEN DIETARY DIVERSITY any food from these 0-No dominant food item ONLY FOR WOMEN AGE 15 TO 49 food groups in the last 1-Yes consumed in the YEARS. REFER TO THE 7 days?(food must have HHD? HOUSEHOLD DEMOGRAPHICS been cooked/served at 1.Own production SECTION Q2.3 AND Q2.5 the household) 2.Purchase Please describe the foods that 3.Gifts from 0-No friends/families you ate or drank yesterday 1-Yes 4.Food aid during day and night at home or 5.Traded or outside the home (start with the Bartered first food or drink of the 6.Borrowed morning) 7.Gathering/wild 0-No fruits 1-Yes 8.Other (specify)

D1 D2 D 3 D 4 D5 D 6 D7 TOTAL Woman Woman Woman Woman ID……… ID…….. ID ……. ID…….. 5.1. Cereals and cereal products (e.g. sorghum, maize, spaghetti, pasta, anjera, bread)? 5.2. Vitamin A rich vegetables and tubers: Pumpkins, carrots, orange sweet potatoes 5.3. White tubers and roots: White potatoes, white yams, cassava, or foods made from roots 5.4 Dark green leafy vegetables: Dark green leafy vegetables, including wild ones + locally available vitamin A rich leaves such as cassava leaves etc.

5.5 Other vegetables (e.g., tomatoes, egg plant, onions)? 5.6. Vitamin A rich fruits: + other locally available vitamin A rich fruits 5.7 Other fruits 5.8 Organ meat (iron rich): Liver, kidney, heart or other organ meats or blood based foods 5.9. Flesh meats and offals: Meat, poultry, offal (e.g. goat/camel meat, beef; chicken/poultry)? 5.10 Eggs? 5.11 Fish: Fresh or dries fish or shellfish 5.12 Pulses/legumes, nuts (e.g. beans, lentils, green grams, cowpeas)? 5.13 Milk and milk products (e.g. goat/camel/ fermented milk, milk powder)? 5.14 Oils/fats (e.g. cooking fat or oil, butter, ghee, margarine)? 5.15 Sweets: Sugar, honey, sweetened soda or sugary foods such as chocolates, sweets or candies 5.16 Condiments, spices and beverages:

6. COPING STRATEGIES INDEX Frequency score: Number of days out of the past seven (0 -7). In the past 7 DAYS, have there been times when you did not have enough food or money to buy food? If No; END THE INTERVIEW AND THANK THE RESPONDENT If YES, how often has your household had to: (INDICATE THE SCORE IN THE SPACE PROVIDED) 1 Rely on less preferred and less expensive foods? 2 Borrow food, or rely on help from a friend or relative? 3 Limit portion size at mealtimes? 4 Restrict consumption by adults in order for small children to eat? 5 Reduce number of meals eaten in a day? TOTAL HOUSEHOLD SCORE: END THE INTERVIEW AND THANK THE RESPONDENT

4.1 FOOD FORTIFICATION (FF)/- Please ask the respondent and indicate the appropriate number in the space provided 1.1 Have you heard about food fortification? 1. Yes 2. No 3. Don’t know

If yes, where did you hear or learn about it? (MULTIPLE RESPONSE ARE POSSIBLE- (Use 1 if “Yes” and 2 if “No”) 6. Radio……………………………………………………………………………………………………………… |____| 1.1.1 7. Road show………………………………………………………………………………………………………... |____| 8. In a training session attended……………………………………………………………………………………. |____| 9. On a TV show……………………………………………………………………………………. |____| 10. Others…………………………………………………………………………………………………………………. |____|

1.2 Respondent’s knowledge on the food fortification logo (Show the food fortification logo to the respondent and record the response). Do you know about this sign? 1. Yes 2. No 3. Don’t know |____|

1.3 What is the MAIN source of Maize flour for the 1.1b Do you know if the maize flour household NOW? you consume is fortified or not? 2. Bought from the shops, supermarket e.t.c 3. Maize is taken for milling at a nearby Posho Mill 1. Yes 4. Bought from a nearby Posho Mill 2. No 5. Other (Please specify) 3. Don’t know |______|

1.4 What brands of the following foods does your household consume? 1. Maize flour |______| 2. Wheat flour |______| 3. Margarine |______| 4. Oils |______| 5. Fats |______| 6. Sugar |______|

Appendix 5: Survey Team

Supervisor Team Leader Enumerator PENINA ITONGA FATUMA DIRAMO DIRIVO ISMAIL DIDO YUSSUF FELIX O ODHIAMBO MWANADIE H OMAR WESLY ODHIAMBO JUMA TANGULIA WAYU GHAMACHANA MWANADIE SUMBA ABDIRIZAK ISMAIL ABDI CHPKEMEI PRISCILLAH HASSAN RASHID ABDOW ZAKARIA ELYAS FARHIA MUSTAFA MOHAMED B SAFARI VERONICA WANGUI WAIGWA MWANAJUMA ADIA OMAR TUMAINI CHARO TSOFWA ZEITUN J BILAL ADHAN MOHAMED RACHA LILLIAN M SHARI AHMED IBRAHIM ZAINAB HAWA IBRAHIM OMAR BAKERO SAID LAVENDER HADIRIBO AMINA GALGALO BORU PENINA NDARAMA MANASE HARRY N MUTETI PATIENCE K CHENGO

Appendix 6: Survey Coordination Team

Coordination Team Tana River County Makopa Omari (CNC Tana River County and overall survey Coordinator) Department of Health Flora Abio (Galole Sub County nutrition coordinator) Zipporah Musyoki (Galole Sub County Nutrition Officer)

Kahindi Tuva( Tana Delta Sub County Nutrition Coordinator) Yasmin Ismael (Tana North Sub County Nutrition Coordinator Oliver Kamar (UNICEF, Nutrition Support Officer),Felicity Munene (Concern Worldwide, Partner Supervisors Survey and Surveillance Officer), Caroline Mugo (Concern Worldwide, Health and Nutrition Manager) Yvonne Ouma (Concern Worldwide Nutrition Officer).