TANA RIVER COUNTY SMART SURVEY REPORT

Transcription

1 TANA RIVER COUNTY SMART SURVEY REPORT FEBRUARY P a g e

2 ACKNOWLEDGEMENT The Tana River 2015 SMART survey was carried out through collaborative efforts of a number of partners. We take this opportunity to hail their commitments which led to the successful completion. Special appreciation goes to the County Department of Health Team led by the County Nutrition Coordinator Mr. Omari Makopa and IMC program manager by Mr John Nderi. We would also wish to extend our special thanks to the County government of Tana River for permission to carry out this assessment within its jurisdiction, and the Tana River community especially the caregiver of children under-fives who were instrumental in providing us with information. We also recognise the financial support by UNICEF as well as the technical guidance by the National Nutrition Information Working Group. Lastly, we thank all the survey teams (supervisors, team leaders, enumerators, and data clerks) who worked tirelessly to ensure the results were available on time. 2 P a g e

3 ARI BCG CIDP CNTF CSI ENA FCS FeFo IDP IPC IMAM IMC IYCF ITN GAM HFA Ksh MAM MOH MUAC NCHS NGO ODF OPV PLW PPS SAM SD SMART UNICEF WFA WFH WHO LIST OF ABBREVIATIONS Acute Respiratory Infection Bacille Calmette Guerin County Integrated Development Plan County Nutrition Technical Forum Coping Strategy Index Emergency Nutrition Assessment Food Consumption Score Iron Folic acid (Folate) Internally Displaced Persons Integrated Phase Classification Integrated Management of Acute Malnutrition International Medical Corps Infant and Young Child Feeding Insecticide Treated Nets Global Acute Malnutrition Height for Age Kenya Shillings Moderate Acute Malnutrition Ministry of Health Mid Upper Arm Circumference National Centre for Health Statistics Non Governmental Organisation Open defaecation Free Oral Polio vaccine Pregnant and Lactating Women Probability to proportion size Severe Acute Malnutrition Standard Deviation Standardized Monitoring Assessment on Relief and Transition United Nations Children Fund Weight for Age Weight for Height World Health Organisation 3 P a g e

4 TABLE OF CONTENTS Contents ACKNOWLEDGEMENT... 2 LIST OF ABBREVIATIONS... 3 TABLE OF CONTENTS... 4 LIST OF TABLES... 5 LIST OF FIGURES... 5 EXECUTIVE SUMMARY INTRODUCTION Background Information Survey Rationale Survey Objectives Specific Objectives Survey Timing Survey Geographical Coverage METHODOLOGY SURVEY TYPE SAMPLING PLAN Sampling Frame Sampling Method and Sample Size Calculation Description of Sampling SURVEY TEAMS TRAINING AND ORGANIZATION DATA COLLECTION DATA COLLECTION TOOLS AND INDICATORS MEASURED DATA ENTRY AND ANALYSIS DATA QUALITY CONTROL SURVEY LIMITATION RESULTS GENERAL CHARACTERISTICS OF STUDY POPULATION AND HOUSEHOLDS DISTRIBUTION OF AGE AND SEX (UNDERFIVES) UNDERFIVES NUTRITION STATUS OVERVIEW OF MALNUTRITION AND WHO GROWTH STANDARDS ACUTE MALNUTRITION (WASTING) Analysis of Acute malnutrition in relation to age Analysis of Acute malnutrition based on presence of oedema Prevalence of acute malnutrition based on MUAC Prevalence of Underweight Based on Weight for Age (WHO Standards) Prevalence of Chronic Malnutrition (Stunting) Based on HFA CHILDREN S MORBIDITY AND HEALTH SEEKING BEHAVIOR Therapeutic Zinc Supplementation during Watery Diarrhoea Episodes Health Seeking Behavior CHILDHOOD IMMUNISATION, VITAMIN A SUPPLEMENTATION AND DEWORMING MATERNAL NUTRITION MOSQUITO NETS OWNERSHIP AND UTILISATION WATER SANITATION AND HYNGIENE Main Sources of Water, Distance and Time to Water Sources Water Treatment Water Consumption Storage and Payment Hand washing Sanitation Facility Ownership and Accessibility FOOD SECURITY AND LIVELIHOODS Households Income Sources Household Dietary Diversity Food Consumption Score P a g e

5 Household Coping Strategy DISCUSSION... Error! Bookmark not defined. 5.0 CONCLUSIONS RECOMMEDATIONS CONCLUSION RECOMMEDATIONS APPEDICIES APPENDIX 1: ANTHROPOMETRIC PLAUSIBILITY REPORT SUMMARY APPENDIX 2 SAMPLED VILLAGES APPENDIX 3: SURVEY TEAMS APPENDIX 4: STANDARDISATION TEST FORMS APPEDIX 5: AGE CALCULATION CHART APPENDIX 6: QUESTIONNAIRE LIST OF TABLES Table 1: Results Summary Table Table 2: Tana River County Seasonal Calendar Table 3: Main occupation of household heads Table 4: Age/sex distribution Table 5: Prevalence of acute malnutrition based on weight for height z- score (WHO 2006 Standards) Table 6 : Prevalence of acute malnutrition by age based on WFH z-score Table 7: Distribution of acute malnutrition and oedema based on WFH z-score Table 8: Prevalence of acute malnutrition based on MUAC Table 9: Prevalence of Underweight based on WFA Table 10: Prevalence of stunting based on height-for-age z-scores and by sex Table 11: Vitamin A and Deworming Table 12: Main Water Sources Table 13: Cost of water Ksh/20 liter Jerrican Table 14: Cost of water in Ksh/Month Table 15: Household Sources of Income Table 16: Food Consumption Score Table 17: Household Dietary Diversity Table 18: Coping Strategy Index LIST OF FIGURES Figure 1: Tana River County Livelihood Zones Figure 2: Age Sex Pyramid Figure 3: Graphical Representation of WFH distribution of children assessed Figure 4: Graphical Representation of HFA distribution in reference to WHO standards Figure 5: Health Seeking Points Figure 6: Immunisation Coverage Figure 7: Length of Iron Folate Consumption in days Figure 8: Water Treatment Methods Figure 9: Hand washing in the 4 critical moments Figure 10: Use of Soap for Hand washing Figure 11: Relieving Points Figure 12: Food Consumed at Household level P a g e

6 EXECUTIVE SUMMARY International Medical Corps and Tana River County Department of Health jointly carried out a SMART survey in Tana River County in February 2015 (Data Collection from 2 nd and 6 th February 2015).Tana River County is one of the Counties in the Coastal region and experiences erratic rainfall leading to the occurrence of recurring drought episodes. The overall goal of the survey was to determine the prevalence of malnutrition among the children aged 6-59 months old, pregnant and lactating mothers in Tana River County. This was a cross sectional survey that applied the SMART methodology. Two stage cluster sampling was adopted whereby clusters were sampled during the first stage and households in the second stage. All accessible villages in Tana River County were used as the survey s sampling frame. Villages were selected based on proportion to population size (PPS) principle. The second stage involved selection of house-holds from the selected clusters using simple random sampling method. Household was used as a basic sampling unit. In calculating the sample size, ENA software was used. A sample of 397 children and 458 households was obtained upon which 31 clusters were sampled. A standard questionnaire was used in data collection. The questionnaire had 5 sections namely; identification, demographic, anthropometric, maternal, water sanitation and hygiene and food security. Data collection took place for 5 days. Prior, training was done at a central point (Hola town). A total of seven teams participated in the survey. Each team comprised of a team leader and three enumerators. All team leaders were MOH personnel. A team of four people was also engaged for data entry as data clerks. Table 1 summarises the key survey findings. Table 1: Results Summary Table ANTHROPOMETRIC RESULTS WHO 2006 Standards 95% CI 95% CI Design Effect= 1.52 N June 2014 N February 2015 Prevalence of Global Acute Malnutrition (<-2 z- score) Prevalence of Severe Acute Malnutrition (<-3 z- score and/or oedema 561 (42) 7.5( ) 415 (41) 9.9 % ( ) (5) 0.9 % ( ) (4) 1.0 % ( ) Prevalence of stunting (<-2 z-score) % ( ) 393 (94) 23.9 % ( ) Prevalence of severe stunting (<-3 z-score) (50) 9.1 % ( ) (25) 6.4 % ( ) Prevalence of Underweight (<-2 z-score % ( ) 412 (78) 18.9 % ( ) Prevalence of severe underweight (<-3 z-score 4.6 %( ) (15) 3.6 % ( ) IMMUNISATION Measles Coverage (Children 9 months by 88.3% 89.9% 6 P a g e

7 card and recall BCG(Scar present and card 92.6% 91.2% OPV 1 (By card and Recall) 97.8% 98.5% OPV 3(By Card and Recall) 92.8% 96.5% VITAMIN A SUPPLEMENTATION AND DEWORMING Children aged 6-11 months who were supplemented with vitamin A once Children aged who were supplemented with vitamin A at least once Children aged who were supplemented with vitamin A twice Children 12 month old and above who were dewormed at least once Children 12 months old and above who were de-wormed twice % 52 80% % % % % % % % % CHILD MORBIDITY Indicator % June 2014 N % Feb Illness in the last 2 weeks (6-59 months All 58.9% % Fever like Malaria 42.1% % ARI 52.8% % Watery diarrhoea 12.8% % Bloody diarrhoea 0.9% 1 0.4% Therapeutic zinc supplementation during diarrhoea cases 62.8% 57.9% MATERNAL NUTRITION Iron folate supplementation for pregnant women Iron folate supplementation for at least 270 days 67.3% % 0% 0 0% 7 P a g e

8 PLW with MUAC less than 21 cm 3.3% 8 3.4% People who slept under mosquito nets Under fives 78.1% 72% PLW 78.4% 75% WATER SANITATION AND HYGIENE PRACTICES Access to Sanitation Facilities 48.4% % FOOD SECURITY Low Dietary Diversity (3 Food Groups) 1.4% Medium Dietary Diversity (4-5 Food Groups) 17.6% % High Dietary Diversity (>6 Food groups 81.0% % Food Consumption Score 62 Households that were food insecure in the last 7 day 38.6% % Coping Strategy Index Recommendations: To address the gaps the following recommendations were proposed: Conduct active case finding for acutely malnourished children and appropriate referral The CNTF needs to review the recommendations from the previous surveys for further follow up Biannual deworming campaigns to increase coverage- combine with Vitamin A campaign Increased sensitization on ANC attendance and consumption of iron/folate supplements Improve the supply chain for essential drugs e.g. Iron, folate. Increase toilet coverage in the county and establishment of ODF villages. A KAP survey needs to be done in the county to give in depth information on child care practices 8 P a g e

9 1.1 Background Information 1. INTRODUCTION Tana River County is located in the Coastal region of Kenya. The County which occupies an area of approximately 38,437 km 2 has an estimated population of 276,965 people 1. 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 is divided in to 3 sub counties namely; Bura, Galore and Garsen. 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 North to the Indian Ocean in the South passing through Tana Delta and covering a stretch of approximately 500km. It is situated in the Eastern side of the county and provides livelihood opportunity to resident population through flood receded crop farming. Generally the county experiences bimodal rainfall pattern which is mostly erratic with long rains falling between April and June and short rains being experienced between October and December. As indicated in figure 1 below, the county has 4 main livelihood zones namely; Pastoral, Marginal mixed farming, Mixed farming and National park. Figure 1: Tana River County Livelihood Zones , DHIS Population Estimates 9 P a g e

10 The pastoral and marginal mixed farming livelihood zones rely on the short rains while the mixed farming areas are dependent on the long rains (April June). 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 being experienced in July and hottest months being September and January. It therefore experiences two dry spells every year occurring in December to March and July to October. Early warning assessment (January 2015), indicated the County as alert state of drought cycle. The situation however was deteriorating in all livelihood zones apart from mixed farming livelihoods where the situation was stable. During the December January, Tana River County only received 7.6mm compared to the normal mm. The poor state of infrastructure and road network in the county affects access to health services and to markets especially during episodes of flooding. 92% of the health facilities in the County are currently functional. The main relief programmes in the county are food aid (GFD and Food for Assets), nutrition (Supplementary and therapeutic feeding programmes), Water sanitation and hygiene programmes as well as food security interventions. 1.2 Survey Rationale The purpose of this survey was to find out the nutrition situation in Tana River County. The results will form a solid basis for planning appropriate future interventions. 1.3 Survey Objectives The main objective of the survey was to determine the prevalence of malnutrition among the children aged 6-59 months old, pregnant and lactating mothers in Tana River County Specific Objectives 1. To determine the nutritional status of women of reproductive age (15-49) years based on maternal mid upper arm circumference (MUAC). 2. To determine immunization coverage; measles (9-59 months), OPV1/3 and Vitamin A for children aged 6-59months. 3. To determine deworming coverage for children aged 12 to 59 months. 4. To determine the prevalence of common illnesses (diarrhea, measles and ARI). 5. To assess maternal and child health care practices. 6. To assess water, sanitation and hygiene practices. 7. To assess the prevailing situation of household food security in the County Survey Timing This survey is planned for at the short dry spell. At this period there is usually the harvesting of produce (short rain harvest) by the farming community. For pastoralists, it is usually a lean period characterized by drop in milk yields, livestock movements towards the dry grazing areas, water stress in traditional grazing areas as well as decline in livestock prices. This survey will help to assess the effects of short rain assessment (SRA 2014). 10 P a g e

11 Table 2: Tana River County Seasonal Calendar 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 Preparatio n Planting/weeding Lean period for farmers Crops at green maturity Long rains harvest Land Preparatio n. Planting/Weeding Lean period for farmers Crops at green maturity 1.6. Survey Geographical Coverage This survey took place in the entire Tana River County. The County comprises of 3 Sub- Counties namely; Bura, Galole and Garsen. 11 P a g e

12 2.1. SURVEY TYPE 2. METHODOLOGY The survey was cross- section and applied Standardized Monitoring and Assessment for Relief and Transition (SMART) methodology. Data collected during the exercise included household, anthropometric, morbidity, child immunization and food security data SAMPLING PLAN Sampling Frame The sampling frame constituted of the entire population of Tana River County (276,965 people). All villages (clusters/sampling units) in Tana River County which were accessible, secure or not deserted were included in the sampling frame Sampling Method and Sample Size Calculation Two stages Cluster sampling was used during the survey. The first stage involved random selection of clusters from the sampling frame based on probability proportion to population size (PPS) 2.Emergency Nutrition Assessment (ENA) for Standardized Monitoring for Assessment for Relief and Transition (SMART) November 2014 was be used in calculation of sample size. In calculating the sample size, an estimated prevalence of 7.5% which was the prevalence for the immediate previous survey (June 2014) was entered in the ENA software. This was informed by the fact that there was no suspected change in prevalence. Other variables used included a desired precision of 3% informed by the previous survey prevalence, a design effect of 1.23 obtained from the June 2014 survey. From this a total of 397 Children was obtained as the under-five sample size. In order to obtain the number of household required; 3 more variables were used. These variables included; the average house size. According to Tana River County CIDP, the average household size is 6. The DHIS/AWP estimate for under-five population of 16.2% and the non-response rate of 1% based on June 2014 survey were also used. A total of 458 households were used as the sample size. A household was used as sampling unit in the second stage sampling Description of Sampling The number of households obtained from ENA planning (458) was used for the survey. After taking into account the time to be spent to and from the survey sites, introduction at sites, breaks, survey and introduction time in each household, and time spent from one household to the next, 15 households were visited in every cluster. This translated into 31 clusters which were covered during the survey. Simple random sampling method was used in household selection. Household selection was based on an updated list of households provided by chiefs or respective village elders for the sampled clusters. Questionnaires were administered in each of the selected household SURVEY TEAMS TRAINING AND ORGANIZATION Six teams participated in the survey. Each team comprised of a team leader and three enumerators (2 data collectors/ assistants and 1 measurer). All team leaders were MOH personnel. A team of four people was engaged for data entry as data clerks. The County Nutrition Coordinator and IMC program officers were tasked with supervisory roles. The survey team leaders, data clerks and enumerators were first recruited through a process which included; advertisement of positions, shortlisting of candidates and rigorous interviews conducted in a central place in Tana River County headquarters (Hola) 2 In this method villages with more population are likely to be selected as compared to those with low population 12 P a g e

13 The survey teams were rigorously trained together for 5 days in Hola town from 28 th January 2015 to 1 st February The training topics included; introduction to SMART methodology, malnutrition, anthropometric measurements, sampling methods, data collection tools, accurate measurements and recording, interviewing techniques and administration of the questionnaires. On the fourth day, a standardization test was done to ascertain the accuracy and precision of taking anthropometric measurement by the enumerators. On the the fifth day, pre-test was done to a nearby village (Laza) which had not been sampled for the survey DATA COLLECTION The data collection exercise took place in the sampled villages between 2 nd and 6 th February DATA COLLECTION TOOLS AND INDICATORS MEASURED One questionnaire was used in data collection. The questionnaire had the following sections: Identifying information: This included data collector s name, team leader s name, survey date, County, Sub- County name. Divisions, location, sub- location and village names also included were cluster number, Household and team numbers. Demographic Information: Household demographics, namely; household composition by age groups, sexes, school enrollment, attendance and completion, residency status, household income, possession and utilization of mosquito nets was collected under this section. Anthropometric information: Children aged 6-59 months anthropometric data was collected under this section. Such information included, Child s date of birth, sex, weight, height, MUAC and presence or absence of edema. Health seeking Behavior: Mothers/Caregivers were requested to provide morbidity (sickness) status of their children in the past 2 weeks, the type of illness and in case of watery diarrhea, whether therapeutic zinc supplementation was given. They were also asked to provide information on whether they sought any assistance during this period and in case they did where they got it from. Vitamin A Supplementation, Deworming and Child Immunization: Under this section, information on vitamin A supplementation for children aged 6 to 59 months, the number of times the child was supplemented in the last one year and whether supplementation was done at the health facility/outreach or during a mass campaign. Deworming information for children aged 12 to 59 months was also captured under this session. Other information collected included immunization for BCG, OPV1 and OPV3 and also measles. Maternal Nutrition: The nutrition status of women of reproductive age (15 to 49 years) was assessed using MUAC. The physiological status of this group was also assessed. This was done in order to establish whether there were differences in nutrition status of normal women, pregnant and lactating women (who are normally under nutrition stress). Iron- folate supplementation and the number of days it was done was also assessed. Water Hygiene and Sanitation: The main sources for drinking water of each household were assessed. Trekking distances, queuing time was assessed based on sphere standards. Also assessed were water treatment and storage practices and also water payment rates. On hygiene and sanitation hand washing during the four critical moments and human waste disposal practices were interrogated. Food security Information: Household food security was assessed using food frequency and household dietary diversity (HDD) based on a 7 days recall. The information on the main source of dominant food items in each of the 16 food groups was also collected. The last part under this section was coping strategies through which coping strategy index was computed DATA ENTRY AND ANALYSIS Anthropometric data entry and processing was done using ENA software version 2014 (November). World Health Organization Growth Standards (WHO-GS) data cleaning and flagging procedures were used to identify outliers which enabled data cleaning as well as exclusion of discordant 13 P a g e

14 measurements from anthropometric analysis. The ENA software generated weight-for-height, height-for-age and weight-for-age Z scores to classify them into various nutritional status categories using WHO standards and cut-off points and exported back to SPSS for further analysis. All the other quantitative data was entered and analysed using Excel DATA QUALITY CONTROL To ensure data collected was valid and reliable for decision making, a number of measures were taken. These measures included; 1. Thorough training of teams was done in 5 days for all survey participants, the training dwelt on SMART methodology, survey objectives, interviewing techniques and data collection tools. 2. Ensuring all anthropometric equipments were functional and standardized. On daily basis each team was required to calibrate the tools 3. During the training exercise, standardization was done, in addition piloting of tools was done to ensure all the information was collected with uniformity 4. Review of data collection tools during training and after the pilot test was conducted. 5. All the survey teams were assigned a supervisor during data collection. 6. 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 next day. 7. Teams were followed up by the supervisors to ensure all errors were rectified on time. More attention was given to the teams with notable weaknesses. 8. Adequate logistical planning beforehand and ensuring the assigned households per clusters can be comfortably surveyed. 2.8 SURVEY LIMITATION The Previous survey was done in a different season and it was therefore difficult to compare the results with the immediate previous survey. 14 P a g e

15 3.0 RESULTS 3.1 GENERAL CHARACTERISTICS OF STUDY POPULATION AND HOUSEHOLDS Data collection was done in 450 household in 30 clusters out of the sampled 458 households representing a response rate of 98.3%. The non-response rate was attributed to migration of household members to another area where they could not be traced. The average household size was 4.9%. Majority (98.7%) of the respondents were residents of their respective villages with 0.9% and 0.4% indicating IDP and refugees as their residency status respectively. The main occupation of heads of households visited was working on their own farm, livestock herding as well as waged casual labour at 26.4%, 24.0% and 21.6% respectively. Other household heads occupations are as indicated in table 3 below. In terms of household incomes, majority of households sourced their income from casual labour (23.3%), sale of crops at 20.5% while petty trade and sale of livestock accounted for 20.3% each as indicated in table 13. In terms of marital status majority of the respondents (88.2%) were married. The rest were windowed (7.8%), divorced (2.2%), separated (1.1%) and single (0.7% Table 3: Main occupation of household heads Household head occupation n Percent Livestock herding % Own farm labor % Employed(salaried) % Waged labor casual % Petty trade % Merchant/trader % Firewood/Charcoal % Fishing 1 0.2% Others % 3.2 DISTRIBUTION OF AGE AND SEX (UNDERFIVES) A total of 421 children under five years were assessed during the survey. They included 194 boys and 227 girls. The boys: girls ratio was 0.85 (p= 0.108) meaning that, overall, boys and girls were equally represented. Table 4 below shows the overall age and sex distribution. Figure 2 show the age/sex pyramid. Table 4: Age/sex distribution Boys Girls Total Ratio Age (months no. % no. % no. % Boy:girl Total P a g e

16 54 to 59 m 42 to 53m 30 to 41 m Girls Boys 18 to 29 m 6 to 17 m Figure 2: Age Sex Pyramid The overall Age distribution was problematic with a score of 10.Younger children (6-29) were found to be more than the older ones (30-59 months) (1.24).This could possibly be attributed to campaign by local politicians to increase births (though with some reservations). The increasing trend of facility-based delivery from DHIS is used as a proxy- from 142 in 2010, to 1813 in 2011, to 2019 in In as much as 31% of children did not have a document to verify age, it may not be a significant issue since the distribution is not skewed. Error! Reference source not found UNDERFIVES NUTRITION STATUS OVERVIEW OF MALNUTRITION AND WHO GROWTH STANDARDS According to Kenya National Guideline on Integrated Management of Acute Malnutrition (2009), malnutrition is defined as a state when the body does not have enough of the required nutrients (under-nutrition) or has excess of the required nutrients (over-nutrition). One of the effective and commonly used methods of assessment of nutrition status is use of anthropometric measurements. For analysis of under-fives malnutrition, WHO in 2006 came up with reference standards to replace the 1977 NCHS child growth reference standards ACUTE MALNUTRITION (WASTING) Acute malnutrition is defined as low weight for height in reference to a standard child of a given age based on WHO growth standard. Acute malnutrition can be categorised as severe or moderate (SMART methodology 2006). It reflects the current form of 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 with bilateral oedema as well as those, whose MUAC is less than 11.5 cm 3 Moderate acute malnutrition is defined as weight for height less than -2SD but more than -3SD or MUAC below 12.5 cm and more or equal to 11.5cm. Global Acute Malnutrition (GAM) refers to the sum prevalence of malnutrition (all SAM and MAM cases/ <-2 z-score). Analysis of acute malnutrition involved the assessment of 415 children (192 boys and 223 girls), with exclusion of 6 cases which were flagged. From the assessment, the GAM was 9.9 %( , 95% CI) whereas the SAM rate was 1.0 %( , 95% CI) as indicated in table 5 below. 3 WHO growth Standards and identification of severe acute malnutrition 16 P a g e

17 Table 5: Prevalence of acute malnutrition based on weight for height z- score (WHO 2006 Standards) Prevalence of global malnutrition (<-2 z-score and/or oedema) Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema) Prevalence of severe malnutrition (<-3 z-score and/or oedema) All n = 415 (41) 9.9 % ( % (37) 8.9 % ( % (4) 1.0 % ( % Boys n = 192 (19) 9.9 % ( % (17) 8.9 % ( % (2) 1.0 % ( % Girls n = 223 (22) 9.9 % ( % (20) 9.0 % ( % (2) 0.9 % ( % There were pockets of high rates of malnutrition specifically in cluster 6 (Konoramadha) and Cluster 7 (Gubatu) which gave a Poisson of 1.These are the pastoralists areas in the northern parts of the county, and have also consistently shown higher IMAM admission rates. Figure 3 below is a graphical representation of distribution of WFH of children surveyed in relation to WHO 2006 standard curve. The curve slightly shifts to the left (0.65±1.01) an indication of under nutrition in comparison to reference children. Figure 3: Graphical Representation of WFH distribution of children assessed Analysis of Acute malnutrition in relation to age Further analysis was done on the prevalence of acute malnutrition based on age as indicated in table 6 below. Whereas younger children (below 30 months) are affected by severe malnutrition it is older children (over 30 months) that are affected by moderate malnutrition. 17 P a g e

18 Table 6 : Prevalence of acute malnutrition by age based on WFH z-score Severe wasting (<-3 z-score) Moderate wasting (>= -3 and <-2 z- score ) Normal (> = -2 z score) Oedema Age (mo) Total no. No. % No. % No. % No. % Total Analysis of Acute malnutrition based on presence of oedema Presence of oedema is a sign of severe acute malnutrition. Analysis for acute malnutrition was also based on the presence of oedema. As indicated in table 7, there was no oedema case that was recorded in the survey. Table 7: Distribution of acute malnutrition and oedema based on WFH z-score <-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor No. 0 (0.0 %) Kwashiorkor No. 0 (0.0 %) Oedema absent Marasmic No. 5 (1.2 %) Not severely malnourished No. 413 (98.8 %) Prevalence of acute malnutrition based on MUAC Apart from the WHO standards 2006, MUAC is used for screening to determine malnutrition in children 6-59 months. According to Kenya guideline on Integrated Management of Acute Malnutrition (2009), A very low MUAC (<11.5cm for children under five years) is considered a high mortality risk and is a criteria for admission with severe acute malnutrition. MUAC reading of 11.5 cm to < 12.5 cm is an indicator of MAM. Analysis of nutrition status for children 6 to 59 months based on MUAC of less than 12.5 cm and presence or absence of edema resulted to a GAM rate of 1.4 % ( % and a SAM rate of (based on MUAC less than 11.5 cm and/or oedema) of 0.5 % ( % as indicated in table 8 below. 18 P a g e

19 Table 8: Prevalence of acute malnutrition based on MUAC Prevalence of global malnutrition (< 125 mm and/or oedema) Prevalence of moderate malnutrition (< 125 mm and >= 115 mm, no oedema) Prevalence of severe malnutrition (< 115 mm and/or oedema) All n = 419 (6) 1.4 % ( % (4) 1.0 % ( % (2) 0.5 % ( % Boys n = 193 (1) 0.5 % ( % (1) 0.5 % ( % (0) 0.0 % ( % Girls n = 226 (5) 2.2 % ( % (3) 1.3 % ( % (2) 0.9 % ( % Prevalence of Underweight Based on Weight for Age (WHO Standards) Underweight is a composite form of under nutrition that includes elements of stunting and wasting. It is defined as the percentage of children aged 0 to 59 months whose weight for age is below minus two standard deviations (moderate and severe underweight) and minus three standard deviations (severe underweight) from the median of the WHO Child Growth Standards (UNICEF 2013) 4. The prevalence of underweight in Tana River County for Children 6-59 months based on this assessment was 18.9% ( , 95% CI), while that of severe underweight was 3.6%( , 95% CI) as shown in table 9 below. Table 9: Prevalence of Underweight based on WFA Prevalence of underweight (<-2 z-score) Prevalence of moderate underweight (<-2 z-score and >=-3 z-score) Prevalence of severe underweight (<-3 z-score) All n = 412 (78) 18.9 % ( % (63) 15.3 % ( % (15) 3.6 % ( % Boys n = 190 (41) 21.6 % ( % (36) 18.9 % ( % (5) 2.6 % ( % Girls n = 222 (37) 16.7 % ( % (27) 12.2 % ( % (10) 4.5 % ( % Prevalence of Chronic Malnutrition (Stunting) Based on HFA Stunting means low height for age of a reference child. Childhood stunting is an outcome of maternal under nutrition and inadequate infant and young child feeding (IYCF), a correlate of impaired neurocognitive development, and a risk marker for non-communicable diseases and reduced productivity in later life(who 2013) 5 Stunting results from causes that extend beyond hunger and food availability, and have wide ranging consequences that prevent communities and nations from achieving their social and economic development aspirations. Because stunting is not treatable it calls for preventive measures nested in multiple development sectors and requires a response that draws from a cross-section of disciplines. 4 Improving Child Nutrition: The achievable imperative for global progress 5 Childhood Stunting: Challenges and Opportunities 19 P a g e

20 Analysis of stunting revealed an overall stunting rate of 23.9 %( , 95% CI). Boys were significantly stunted compared to girls as indicated in table 10 below. Table 10: Prevalence of stunting based on height-for-age z-scores and by sex All Prevalence of stunting (<-2 z-score) Prevalence of moderate stunting (<-2 z-score and >=-3 z-score) Prevalence of severe stunting (<-3 z-score) n = 393 (94) 23.9 % ( % (69) 17.6 % ( % (25) 6.4 % ( % Boys n = 183 (55) 30.1 % ( % (40) 21.9 % ( % (15) 8.2 % ( % Girls n = 210 (39) 18.6 % ( % (29) 13.8 % ( % (10) 4.8 % ( % Figure 4 below is a graphical representation of HFA distribution in relation to WHO standard curve. There is a left shift from the standard curve with a mean -1.61±1.18, an indication of overall stunting in relation to the reference children. Figure 4: Graphical Representation of HFA distribution in reference to WHO standards 20 P a g e

21 3.4 CHILDREN S MORBIDITY AND HEALTH SEEKING BEHAVIOR According to UNICEF conceptual framework on causes of malnutrition, disease is categorised as an immediate cause of malnutrition. It also affect food intake which is also categorised as an immediate cause. It is important therefore to assess morbidity and whether it had some effect on malnutrition. To assess child morbidity mothers/caregivers of children aged 6 to 59 months were asked to recall whether their children had been sick in the past 2 weeks. Those who gave an affirmative answer to this question were further probed on what illness affected their children and whether 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. From the assessment, 56.8% of the assessed children were reportedly sick in the past two weeks prior to the survey. Among those who were sick, majority (53.5%) were affected by acute respiratory infection (ARI). Fever like malaria affected 34.4%, while 13.9% suffered from watery diarrhoea Therapeutic Zinc Supplementation during Watery Diarrhoea Episodes Based on compelling evidence from efficacy studies that zinc supplementation reduces the duration and severity of diarrhea, in 2004 WHO and UNICEF recommended incorporating zinc supplementation (20 mg/day for 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 diarrhea 6. Kenya has adopted these recommendations. According to Kenyan policy guideline on control and management of diarrheal diseases in children below five years in Kenya, all under-fives with diarrhea 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 days during episodes of diarrhea. The survey also sought to establish the number of children who suffered from watery diarrhea and supplemented with zinc. Slightly than half (57.9%) of those who suffered from watery diarrhea were supplemented with zinc Health Seeking Behavior Mothers and caregivers whose children were sick in the past 2 weeks were further asked where they sought assistance. Majority (88.9%) sought assistance from appropriate service delivery points namely, public hospital (70.9%), private clinic/pharmacy (17.1%). From such places they are likely to get assistance from trained health personnel with proper diagnosis and treatment being done. Apparently a number of them (10.2%) sought assistance either from a shop/kiosk, relatives and friends, traditional healers or local herbs. In such places, they were likely to be misdiagnosed and receive inappropriate treatment as the service providers lacked expertise and knowledge of offering treatment services. Another 14.3% never sought any assistance. Figure 5 below summarizes the health seeking behavior in Tana River County. 6 Klemm RDW, Harvey PWJ, Wainwright E, Faillace S, Wasantwisut, E. Micronutrient Programs: What Works and What Needs More Work? A Report of the 2008 Innocenti Process. August 2009, Micronutrient Forum, Washington, DC. 21 P a g e

22 Places assistance was sought when the child was sick Public Clinic 70.9% Private Clinic/Pharmacy 17.1% Shop 8.5% NGO/FBO 0.9% Local Herb 0.9% CHW 0.9% Relative or Friend 0.4% Traditional Healer 0.4% Figure 5: Health Mobile Seeking Clinic Points 0.0% 3.5. CHILDHOOD IMMUNISATION, VITAMIN A SUPPLEMENTATION AND DEWORMING 0% 10% 20% 30% 40% 50% 60% 70% Childhood Immunization Kenya aims to achieve 90% under one immunization coverage by the end of second medium term plan ( ). The Kenya guideline on immunization define a fully immunized child is one who has received all the prescribed antigens and at least one Vitamin A dose under the national immunization schedule before the first birthday. According to the MOH child survival and development strategy , there was a significant in-crease in immunization coverage between 2001 and 2008 attributed to successful supplemental immunization activities for polio, measles, maternal and neonatal tetanus which ultimately reduced the incidences of EPI targeted diseases. This survey assessed the coverage of 4 vaccines namely, BCG, OPV1, OPV3, and measles at 9 and 18 months. From this assessment, 91.2% of children were confirmed to have been immunised by BCG 7. Those who were immunised by OPV1 8 and OPV3 were 98.5% and 96.5% respectively while 89.9% had been immunised for measles. However quite a small number (partly 25%) would confirm to have been immunised with the second dose of measles antigen at 18 months as indicated in figure 6 below. 7 The BCG vaccine has variable efficacy or protection against tuberculosis (TB) ranging from 60-80% for a period ranging from years. It is known to be effective in reducing the likelihood and severity of military TB and TB meningitis especially in infants and young children. This is especially important in Kenya where TB is highly prevalent, and the chances of an infant or young child being exposed to an infectious case are high. 8 In Kenya infants receive 4 doses of trivalent OPV before one year of age 1st dose is given immediately at birth or within two weeks of birth. This is known as the birth dose or Zero dose The other 3 doses should be given at 6 (OPV1) 10(OPV2) and 14 weeks (OPV3 of age 22 P a g e

23 Measles at % 13.6% 72% 3.0% Measles at % 35.1% 9% 0.7% OPV3 60.8% 35.7% 3% 0.7% OPV1 62.8% 35.7% 1% 0.7% Figure 6: Immunisation Coverage 0% 20% 40% 60% 80% 100% 120% Vitamin A supplementation and deworming 23 P a g e Yes by Card Yes by Recall No Do not Know According to Kenya Demo-graphic and Health Survey 2008/2009, vitamin A coverage among 6-11 months in Kenya was estimated to be 81.8%. For months, the coverage was estimated to be 14.3%, with an average coverage of 6-59 months being at 30%. Poor data management on vitamin A logistics, inadequate social mobilization to improve vitamin uptake and placement of vitamin A at lower level of priority among other interventions has been cited as major challenges in achieving the supplementation targets (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. Among those who were supplemented, 85% was confirmed by the use of health cards with only 14% who were confirmed by recall. Majorly vitamin A supplementation in the County is done at the health facility or at an outreach site as 75.6% answered affirmatively to this question. Analysis of vitamin A supplementation for children aged 6months to 1 year indicates that 80% of this age group had been supplemented with vitamin A. Among those aged 12 to 59 months, 63.6% had been supplemented with vitamin A for 2 times in the past one year. Assessment on deworming for children aged 12 to 59 months indicates a small uptake of deworming drugs; only 20.1% had taken de-wormers twice in the past one year as indicated in table 11 below. Table 11: Vitamin A and Deworming Factor Number Percentage Vitamin A Supplementation 6 to 11 months 1 time to 59 months At least 1 time At least 2 times Deworming (12 to 59 months) 1 time times

24 3.6 MATERNAL NUTRITION During pregnancy, women need to consume additional iron to ensure they have sufficient iron stores to prevent iron deficiency. Therefore, in most low- and middle-income countries, iron supplements are used extensively by pregnant women to prevent and correct iron deficiency and anemia during gestation. WHO recommends daily consumption of 60mg elemental iron as well as 0.4mg folic acid throughout the pregnancy (WHO 2012) 9. These recommendations have since been adopted by Kenya government in its 2013 policy guidelines on supplementation of FEFO during pregnancy Maternal nutrition was assessed by measuring MUAC of all women of reproductive age (15 to 49) in all sampled household. Analysis was further done for pregnant and lactating women. Mothers of children below 2 years were also asked if they consumed iron folate in their most recent pregnancy. From the analysis, 2.9% of all women of women of reproductive age were malnourished (MUAC 21.0 cm). Further analysis of pregnant and lactating women indicated that 3.4% of them were malnourished based on the same criteria. Majority (66.9%) of women with children below 2 years had been supplemented with iron folate supplements during their most recent pregnancy. However none of the interviewed mother had taken the supplements in the recommended 270 days, with only 9.5% having taken the supplement in 90 days and over, while the rest (90.5%) took the supplement in less than 90 days as indicated in figure 7 below. 80% 70% Iron Folate Consumption in days 67.9% 60% 50% 40% 30% 20% 10% 22.6% 9.5% 0% Less than 30 days days 90 days Figure 7: Length of Iron Folate Consumption in days 9 WHO. Guideline: Daily iron and folic acid supplementation in pregnant women. Geneva, World Health Organization, P a g e

25 3.7 MOSQUITO NETS OWNERSHIP AND UTILISATION Malaria is one of the health issues affecting the County. It is one of the biggest 5 diseases affecting the County. One of the preventive measures put in place is the use of ITN. Overall 72.9% of the households surveyed have at least one mosquito net. Among the under-fives, 72% slept under a mosquito net in the night prior to the survey, while among the pregnant women 75% slept under the mosquito nets in the same period. 3.8 WATER SANITATION AND HYNGIENE Main Sources of Water, Distance and Time to Water Sources Everyone has the right to water. This right is recognized in international legal instruments and provides for sufficient, safe, acceptable, physically accessible and affordable water for personal and domestic uses. An adequate amount of safe water is necessary to prevent deaths due to dehydration, to reduce the risk of water-related disease and to provide for consumption, cooking, and personal and domestic hygienic requirements 10. According to SPHERE handbook for minimum standards for WASH, The average water use for drinking, cooking and personal hygiene in any household should be at least 15 litres per person per day. The maximum distance from any household to the nearest water point should be 500 meters. It also gives the maximum queuing time at a water source which should be no more than 15 minutes and it should not take more than three minutes to fill a 20-litre container. Water sources and systems should be maintained such that appropriate quantities of water are available consistently or on a regular basis. Majority of the households obtained their drinking water from piped systems boreholes, protected springs or protected shallow wells. These are safe sources of drinking water compared to the rest (38.9%) who obtained their drinking water from other sources whose safety could be compromised. Such sources include, unprotected shallow wells, River/spring, earthpan/dam, earthpan/dam with infiltration, water trucking and vendors are as indicated in table 12 below. Table 12: Main Water Sources Water Source n Percent Piped System/borehole/ protected spring/protected shallow well % Unprotected Shallow well % River/Spring % Earthpan/dam % Earthpan/dam with infiltration well 6 1.3% Water tracking/water vendor % Others 2 0.4% Analysis of distances to water sources indicated that, majority of the households (71.5%) obtained their water from sources not more than 500m or less than 15 minutes walking distance. 25.3% took between 15 min to 1 hour or a distance of approximately 500m to 2km. The rest (2.4%) walked as far as more than 2Km (1-2hrs) to their water sources. Regarding the queuing time at the water sources, 37.3% of the respondents queued for water. For 10 The Sphere project- Humanitarian Charter and Minimum Standards in disaster response P a g e

26 those who queued, 64.8% queued for less than 30 minutes, 29.2% between 30 minutes and 1 hour. Only 6% queued for water for more than 1 hour Water Treatment Majority of the households (82.7%) did nothing to their drinking water. Among those who treated their drinking water, use of chemicals (chlorine, Pur or water guard) was the most applied method. 65.4% used this method. Boiling was used by 17.9%, this is due to the fact that the respondents feel that the water changes it taste after boiling. 14.1% used traditional herbs while 2.6% used pot filters as shown in figure 8 below. Water Treatment Methods 70% 65.4% 60% 50% 40% 30% 20% 17.9% 14.1% 10% 2.6% 2.6% 0% Boiling Chemicals(Chlorine, Pur, Waterguard) Traditional Herbs Pot filters Others Figure 8: Water Treatment Methods Water Consumption Storage and Payment Despite the fact that majority of Tana River residents do not treat their water, it is apparent that majority of them(92.9%) store their drinking water properly in closed containers/jerry cans where it is less likely to have physical water contamination. The rest 7.1% indicated that they stored their water in open containers/jerry cans exposing it to physical contamination. Less than 0.5% of the households consumed 15 liters of water per day which is the minimum average household water use for drinking cooking and personal hygiene (SPHERE Hand book 2004). Approximately 46% of the households pay for water. Among those who pay for water 79.7% do so on Ksh/20 liter jerrican while the rest, pay on monthly basis. For those who pay water per 20 litre jerrican approximately 70 % pay Ksh 5 or less as indicated in table 13 below. Table 13: Cost of water Ksh/20 liter Jerrican Payment(Ksh/20 liter jerrican n Percent P a g e

27 Total % For those who paid on monthly basis, majority paid over Ksh 500 per month. Table 14 summarizes the payment of water per month. Table 14: Cost of water in Ksh/Month Payment Ksh/Month n Percent 1 to to to to to to Over Total Hand washing The importance of hand washing after defecation and before eating and preparing food, to prevent the spread of disease, cannot be over-estimated. Users should have the means to wash their hands after defecation with soap or an alternative (such as ash), and should be encouraged to do so. There should be a constant source of water near the toilet for this purpose. (SPHERE Handbook 2004). Assessment of hand washing in the 4 critical times in Tana River county indicated that majority of them (93.1%) washed their hands before eating. Quite a number (77.1%) indicated that they washed their hands before cooking while 71.1% mentioned after visiting the toilet. Only 40.7% indicated that they did so after taking children to toilet as indicated in figure 9 below. 100% 90% 80% 70% 60% 71.1% 77.1% Handwashing Moments 93.1% 50% 40% 40.7% 30% 20% 10% Figure 0% 9: Hand washing in the 4 critical moments After Toilet Before Cooking Before Eating After taking children to toilet 27 P a g e

28 Majority of respondents (58%) use water and soap to wash their hands compared to 33.7% who used water only. Very few said they used soap when they could afford it as indicated in figure 9 below. 60% 58.0% 50% 40% 33.3% 30% 20% 10% 0% 8.7% Water only Water and Soap Soap whe I can afford Figure 10: Use of Soap for Hand washing Sanitation Facility Ownership and Accessibility 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 defaecation was practiced by 56.9% of the respondents. Toilet ownership remained low at 24.0% while 18.9% shared sanitary facilities or used neighbours toilets to relieve themselves as indicated in figure 11 below. 24.0% In bushes, Open defeacation 18.9% 56.9% Neighbors or shared traditional pit/improved latrine Own traditional pit/improved latrine Figure 11: Relieving Points 28 P a g e