Small Scale Survey Report

Transcription

1 Garbatulla May 2010 Small Scale Survey Report SUMMARY OF KEY FINDINGS > Nutritional status results from the second round Small Scale Surveillance indicate that there was improvement in trends of Global Acute Malnutrition (GAM) rates with 85% probability exceeding the threshold in Garbatulla, down from 14.6% to 12% between February and May > In regards of child morbidity, in Garbatulla, there was a decline in cases of both diarrhoea/vomiting and fever chills like malaria. This was also confirmed by the reported cases of diarrhoea from the District MOH report which showed 62 cases in February and reduced to 13 cases in May However, there was slight increase observed in case of fever with difficulty in breathing. > There was slight increase in trends in the use of mosquito nets from 77.9% to 79.3% during the reporting period. > A considerable proportion of households in the district continued to access water from unsafe 1 sources which accounted for 61.3% and 65% in February and May 2010 respectively. > Households relied and depended primarily on markets as their main source of food in Garbatulla sentinel site. > Reducing meal size and purchase of food on credit from vendors were the leading coping strategies in Garbatulla. Overall, comparing the proportion of households who practiced different types of coping strategies between February and May 2010, a general decreasing trend for most coping strategies was observed in Garbatulla Sentinel Site. 1. INTRODUCTION Garbatulla District is one of the 28 districts in Eastern Province of Kenya located within the Arid and Semi-Arid (ASAL) region which frequently experiences recurrent droughts and high rates of acute malnutrition. The quarterly surveillance, implemented in partnership with the Ministry of Health and Arid Land Resources Management Project (ALRMP) at the District level used a two stage cluster sampling methodology for data collection and an integrated approach focusing on nutrition, water/sanitation and food security/livelihoods. Garbatulla district was selected as one of the sentinel site representing the livelihood zone s of the most vulnerable areas (Pastoral, farming, and Peri-Urban). Through quarterly data collection, the surveillance system aims at monitoring early warning indicators while providing trends that allow for better global and seasonal understanding of the underlying causes of malnutrition in the targeted areas. Therefore, the second round of nutrition and food security integrated small scale survey was conducted in Garbatulla District in May This was at the end of the long rainy 1 Unsafe water sources : unprotected shallow well from Laga/not Laga, earth pan, river flowing, water seller and piped water system from spring ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

2 season which was normal both in amount and distribution 2. The survey was implemented in 30 clusters randomly selected using ENA/SMART software. 2. METHODOLOGY Nutrition data: A small sample was selected using the SMART methodology; 30 clusters of 10 children between 6 and 59 months were randomly selected. The list of sub-locations was obtained from the Garbatulla District Statistics Office. The anthropometric data were entered and analyzed using the ENA Software, October 2007 version. In addition, all anthropometric results were analysed through the probability calculator developed by the Centre for Disease Control (Atlanta, USA) which is used for analysing the probability for the true prevalence to exceed a determined thresholds. The point estimates only provide results with a 5 confidence (very low precision) whereas the estimated confidence intervals provide results with a 95% confidence (higher precision than necessary for the purpose of the small scale surveillance system). Therefore, the 85% probability of exceeding the thresholds is considered to be precise enough to make the most reasonable informed decision. Moreover, a statistical test was employed using the two sample test probability calculator to measure the significance level of difference with the present results and the ones obtained during the previous round of surveillance, in February Food Security, Water & Sanitation data: The data entry processes for Food Security and Water and Sanitation data was performed with SPSS Software Version 13. The results from both surveillances which compares trends over time are presented in the following sections. 2 FEWSNET reports, May 2010 ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

3 3. RESULTS OF NUTRITION, HEALTH AND CARE PRACTICES DATA 3.1. Acute Malnutrition Prevalence The computed point estimate of GAM and SAM rates using ENA software for SMART revealed that the GAM and SAM rates had respectively decreased from 17.2% in Ferbruary to 14. in May 2010 and from 3.8% (February) to 1.4% (in May). The timing of the second round small scale survey was end of May 2010 right after end-up long rain season. The probable explanation for such improvement in nutritional status in the district includes the general food distribution made by WFP and the government as well as availability of milk production at household level. Table 1: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by gender 3 WHO references NCHS references Feb 10 May 10 Feb 10 May 10 Global Acute Malnutrition (<-2 z-score and/or oedema) 17.2 % ( ) 14. ( ) 16.6% ( ) 14.9% ( ) Moderate Acute Malnutrition (<-2 and >=-3 z-score and no oedema) 13.4 % ( ) 12.6% ( ) 15.3% ( ) 14.6% ( ) Prevalence of severe malnutrition (<-3 z-score and/or oedema) 3.8% ( ) 1.4% ( ) 1.4% ( ) 0.3% ( ) > According to the CDC probability calculator, the surveyed population has 85% probability to reach 12.8% for GAM, and 0.1% of SAM in May Table 2: GAM and SAM rates with 85% probability threshold February 2010 May 2010 N=Sample size Global Acute Malnutrition (<-2 z-score and/or oedema) Prevalence of severe malnutrition (<-3 z-score and/or oedema) 14.6% 12.8% 2.6% 0.1% > According to the CDC probability calculator using the 85% threshold, the results obtained in both rounds of surveillance are NOT statistically different for the GAM rates, both expressed in WHO and NCHS standards. They are statistically different however, for the SAM rate expressed in WHO standards. We can therefore assume that there is a significant decrease in the prevalence of SAM between both rounds 3.2. Morbidity Diseases are immediate causes of malnutrition, which determines the wellbeing of a child. The information was collected through household questionnaires and complemented by information from the health facilities in the district. When comparing the February 2010 result with the May 2010, there is a noticeable decline in cases of diarrhoea/vomiting and fever with chills like malaria. However, there was a slight increase in fever with difficulty in breathing. According to the health facilities statistics report, the trends of diarrheal prevalence was significantly reduced from 62 cases reported in February 2010 to 13 cases in May Figures in brackets are 95% confidence intervals 4 Garbatulla District MOH Monthly Progress Report ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

4 Figure 1: The Three Common Illnesses of Children in the Two Weeks before the Survey (Gerbatulla) Diarrhea/Vomitting Fever with chills like malaria Fever, cough, diffcult in breathing 4. RESULTS OF WATER, SANITATION AND HYGIENE PRACTICES DATA 4.1. Water Sources and Use The greater proportion of households in the Sentinel sites of Garbatulla continued to access water from unsafe sources 5 - with about 61.3% and 65% in February and May 2010, respectively. Those who accessed from safe sources (piped water system/borehole and protected shallow well with a working hand pump) accounted up to 34.7%. Promotion of water treatment interventions could contribute to improved health and nutritional status of children. Figure 2: Trends of Water Use from Safe/ Unsafe Sources, February & May Feb May Use of Safe Sources Use of Unsafe Sources In this reporting period, there was a reduction in the percentage of households whose per capita water usage for domestic 6 purposes fell below the SPHERE standards 7 (from 63% in February to 47% in May) and/or National standards 8 (from 75.7% in February to 61.3% in May). 5 Data on water sources are grouped into safe (piped system, hand/motor piped well, tap or underground tank filled by piped water); unsafe (shallow well traditional, shallow well with cover, earth pan/dam, river, digging in dry riverbed, donkey cart seller, earth pan/dam with IW, roof rain catchments, underground tank or birkad filled by rain (rural); piped water system from spring water point and water trucking in its own. 6 Domestic purposes = drinking, cooking and washing. 7 SPHERE standards = 15 l/p/d 8 National standards = 20l/p/d ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

5 Figure 3: Per Capita water Consumption in Litres Per Day Emergency level (< 7.5 l/p/d) Low (<10 l/p/d) Less than SPHERE (<15 l/p/d) Less than National Standard (<20 l/p/d) 5. RESULTS OF FOOD SECURITY & LIVELIHOODS DATA 5.1. Livestock ownership and milk production As a primarily pastoralist and agro-pastoralist area, livestock are of critical importance to the livelihoods and food security of many households in Garbatulla. Of the households surveyed, 71% reported owning livestock, as compared to 76% in February However, in February 97% of the overall sample were from pastoralist and agro-pastoralist livelihood zones, compared to 8 in the May 2010 sample (the remaining 2 were from urban areas). This may have had some impact on the figures and their comparative value in this instance, particularly as it is likely that fewer urban households own livestock. The table below provides comparative data on household livestock ownership between February and May Average and median household animal ownership are provided as average figures are frequently distorted upwards by relatively small numbers of households with significantly larger herds. Table 3: Household Livestock Ownership by Type February and May 2010 Compared Livestock % HH Ownership No. Animals per HH - Average No. of Animals per HH - Median Type Cattle 25% 38% Camel 22% 14% Goat 58% 52% Sheep 54% 47% Chicken 32% 31% Donkey 29% 31% Despite the decrease in the number of owning cattle, there was an increasing trend in the average milk production per household. The percentage of households who milked the day before the survey was 25.7% in February increased to 37.7% in May Most households are on average accessing 2.88 liters of milk per day, which is however still significantly below the normal 3-5 liters 9. This could be due to pasture and water availability as expected right after the end of long rain season. 9 Kenya Food Security Update, FEWSNET Report, May 2010 ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

6 5.2. Crop Cultivation Farming is not widely practiced in Garbatulla, the bulk of production is restricted to irrigated lands in the riverine areas (e.g. Kinna, Rapsu). Only 7.7% of the surveyed households reported to have undertaken agricultural activities, compared to 10.8% during the February survey. This decrease may have resulted from the reduction in the percentage of the sample from agropastoralist areas (27% in May as compared to 43% in February). The table below details crop production by type, revealing that maize is by far the most commonly cultivated crop. Vegetable production includes onion, tomato and sukumawiki, with onions being produced in the largest quantities. Fruit production, primarily banana and pawpaw, is also undertaken by a significant minority of local farmers. Table 4: Household Crop Production by Crop Type February & May 2010 Compared Crop Type % Farming HH Av. HH Production KG Median HH Production KG % Farming HH Av. HH Production KG Median HH Production KG Maize 97% % Beans 25% % Sorghum 3% % Tomato 22% Banana 13% % Onion 31% % Pawpaw 3% % Orange 3% % Sukumawiki 9% % Mango 3% % Watermelon % Sources of Food Among four common sources of food (purchase, own production, food aid, gift) in Garbatulla District, purchase of food continued to be the primary source of food for the overwhelming majority of households. The figure below illustrates the primary food sources as reported by households. Figure 4: Household Primary Food Sources - February & May Purchase Own Production Food Aid Gift ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

7 Considering the high dependence of households on markets to access food, the price data monitoring for key food items and livestock over the three months preceding the survey indicates that the price decrease for food items was significant. Moreover, the price of livestock has significantly increased over the three months preceding the survey Income and Expenditure Income sources and expenditure data were collected for the 30 days preceding the survey, with livestock/livestock products sales and small business trade reported as the most significant income sources. There was variation in sources of income between February and May, which may be explained to some extent by the increase in urban dwellers in the sampled population. In terms of total income, a decreasing trend was observed from livestock and livestock sales, while an increasing trend from sources of own business and salary. However, for other income sources, slight variations were observed, but not significant. The average household s monthly income in May was 8172 Ksh, representing a slight increase on an average income of 7999 Ksh in February. However, even with the increase, income per person per day translates to only 45 Ksh (0.75 USD), still well below the poverty threshold of 1.25 USD. 5 45% 35% 3 25% 2 15% 1 5% Figure 5: Household Income Sources Agricultural sales Livestock/products sales Small business Bush products Daily labour % HH Feb 2010 % HH May 2010 % Total Income Feb 2010 % Total Income May 2010 Remittance Loans/credit Salary Other The total expenditure pattern is presented in Figure 6. The overall trend was for an increase in the percentage of households who spent money on different products and services, although Figure 6: Household Expenditure Medical & Health Farm Inputs Food Water Transportation Education Debt Repayment Fuel Duksi/Madrassa Clothing Mira Livestock Medication Others % HH % HH % Total Expenditure - % Total Expenditure - ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

8 there was very little change in the pattern of total expenditure. This indicates that there may have been some diversification in household expenditure, but with slightly reduced amounts being spent. Average household expenditure for the month in May was 7350 Ksh, representing a drop from expenditure of 7850 Ksh in February. This could potentially be explained to some extent by decreasing food prices, particularly for staple maize flour Dietary Diversity Dietary diversity was measured using the Household Dietary Diversity Score (HDDS), which measures the 12 main food groups consumed in the 24 hours prior to the survey. Results showed that the average HDDS for Garbatulla District was 4.6 in February and 6.5 in May 2010, which constitutes a marked improvement. % of HH Figure 7: Household Dietary Diversity by Food Group Cereals Roots & Tubers Vegetables Fruits Eggs Meat Fish Legumes Dairy Fats Sugars Condiments The table below shows the distribution of the households according to HDDS category, revealing that the majority fell within the higher dietary diversity group (6 or more food groups consumed), indicating improvements in terms of food availability and household food access. At the same time nutritionally significant food groups such as vegetables, fruits, eggs, meat and fish continue to be consumed by a minority of the households. Table 5: HDDS by Category HDDS Category % of HH in Feb 2010 % of HH In May 2010 Low Dietary Diversity (<=3 Food Groups) 32.7% 7.7% Moderate Dietary Diversity (4-5 Food Groups) 32.3% 16.3% High Dietary Diversity (6 + Food Groups) Coping Strategies Households were asked to report the coping strategies they had utilized during the previous thirty days. Overall, the results revealed reductions of most coping strategies, indicating an improvement in household food security from February to May. However, there was an increase in food purchases on credit which may point towards problems with ready access to adequate cash income amongst the households. Equally there was a slight increase in sales of productive assets, indicating that some households lack a sustainable livelihoods base and face challenges maintaining existing assets. Thus, asset building and livelihoods diversifcation which protects against asset depletion of households need to be promoted in Garbatulla sentinel site. ACF Kenya Sentinel Surveillance Report Mandera & Garissa June

9 % o HH Figure 8: Household Utilisation of Coping Strategies Skip meals Reduce meal size Eat less preferred foods Purchase food on credit Borrow from relatives Send children to eat with relatives Sell off productive assets Ot her 6. CONCLUSION AND RECOMMENDATIONS The second round of Small Scale Sentinel Surveillance of anthropometrics data analysis based on 85% probability thresholds in Garbatulla district was 12%, which is below the WHO 15% GAM threshold and became normal. The probable contributing factor for such improvement in GAM rate was due to water and pasture availability which ultimately leads to high milk production. Overall improvements in household food security were in evidence as compared to the first survey period, as indicated by increased household dietary diversity and income, along with a reduction in reliance on food aid. Generally decreasing staple food prices and increasing livestock sale prices would also contribute to improved household food security. However, on average households still remain well below the poverty line in terms of income. Despite the slight improvement in food security at household level observed during the reporting period, addressing malnutrition through the following short- to medium-term complementary interventions is required for the subsequent period to help sustain the improvements observed: The started outpatient therapeutic feeding program with appropriate screening (passive and active) together with relevant partners and communities needa to be scaled up. Refocus and/or expand activities for nutrition and food security to beneficiaries living in Garbatulla sentinel sites. Improved access to safe water in all Garbatulla site is a major critical and priority intervention. Support income-generating activities as a way to diversify pastoralist and agro-pastoralist livelihood income and food sources, as well as protect against asset depletion at household level. Support pastoralists to become more strategic and market-oriented to create and receive the full value of their animals and animal products throughout the different seasons. Integrate Disaster Risk Management and Drought Management aspects in all program activities, especially WASH and food security and livelihoods. ACF Kenya Sentinel Surveillance Report Mandera & Garissa June