Poster presented at Tropentag 2014. International Conference on Research on Food Security, Natural Resource Management and Rural Development. "Bridging the Gap between Increasing Knowledge and Decreasing Resources" Prague (Czech Republic) Sep 17-19 2014

Herrmann, J.

Jordan, I.

Keding, G.B.

Krawinkel, M.B.

Waswa, L.M.

English

CGSpace

Household Food Security and Dietary Diversity in Different Agro-ecological Zones in Western KenyaLydiah M. Waswa1, Irmgard Jordan1, Johannes Herrmann1, Michael B. Krawinkel1 and Gudrun B. Keding21Institute of Nutritional Sciences, Justus Liebig University Giessen Germany, 2Nutrition and Marketing Diversity Programme, Bioversity International, Nairobi, KenyaIntroductionHousehold food insecurity is associated with diets that lack diversityand which contribute to poor nutrition and health especially indeveloping countries. This study aimed to assess household foodsecurity and dietary diversity in different agro-ecological zones (AEZs)in Western Kenya.Methodology A cross-sectional baseline survey was conducted in July/August 2012 in 5 AEZs in Teso South and Bondo districts.  The 5 AEZs were grouped into two zones:Humid zone in Teso South district: humid LM1 and sub-humid LM2 AEZs (n=148). Dry zone in Bondo district: semi-humid LM3 , transitional LM4 and semi-arid LM5 AEZs (n=145). Two-stage cluster sampling was applied:  30 villages were selected proportional to population size. Households with children aged 6-23 months and their caregivers were randomly selected from each village. Semi-structured questionnaires were used to assess household socio-demographic characteristics. The household hunger scale was used to assess household food security. 24 hour recalls were conducted to document the household dietary intakes.  Household dietary diversity scores (HDDS) were computed based on 12 food groups1. The household hunger score (HHS)2 with a high score meaning severe hunger, and a household wealth indicator (WI) 3 with a high score meaning high wealth were calculated.Bioversity International is a member of the CGIAR Consortium. CGIAR is a global research partnership for a food secure future.Bioversity HeadquartersVia dei Tre Denari 472/a00057 Maccarese, (Fiumicino)Rome, ItalyTel. (39) 06 61181Fax. (39) 06 61979661Email: bioversity@cgiar.orgwww.bioversityinternational.orgConclusions The study findings revealed that food access and household dietarydiversity were better in the drier than humid zones. This contradictsthe common pattern of low food availability in drier zones. This couldbe attributed to better coping strategies among households in thedrier zones due to differences in districts structures. The study findings also confirmed that less varied diets are usuallyfound in poor and food insecure households. There is need for further investigations taking into considerationother variables to understand whether the AEZs alone or otherdistrict-related factors have an influence on food security andhousehold dietary diversity. Strategies focusing on increasing food and nutrition security andthat promote the utilization of a variety of locally available foods areneeded in rural communities.LED BY IFPRIAcknowledgements: This research was conducted with the financial support of the Federal Ministry for Economic Cooperation and Development, Germany, Deutscher AkademischerAustauschdient (DAAD) and National Council of Science and Technology, Nairobi Kenya. Figure 1: Prevalence of hunger among households in the humid and dry zones in Teso South and Bondo districts, Western Kenya Table 2: Mean household hunger scores and household dietary diversity scores in the humid and dry zones in Teso South and Bondo districts, Western KenyaReferences:1. FAO (2011). Guidelines for measuring household and individual dietary diversity. Rome: Food and Agriculture Organization of the United Nations.2. Ballard T, Coates J, Swindale A and Deitchler M (2011). Household Hunger Scale: Indicator Definition and Measurement Guide. Washington, DC: FANTA-2 Bridge, FHI 360.3. Filmer D, Pritchett LH (2001). Estimating wealth effects without expenditure data- or tears: an application to educational enrollments in states of India. Demography, 38(1):115–32.CharacteristicsHumid zone (LM1+LM2)n=148Dry zone(LM3+LM4+LM5)n=145 P*Household hunger scores 1.45±1.27 0.94±1.14 <0.001Household dietary diversity scores6.38±1.66 7.42±1.42 <0.001*Mann-Whitney testOverall 34.5% and 3.4% of the households in the study areaexperienced moderate and severe hunger, respectively (Figure 1). Households in the dry zones experienced less hunger and had higherHDDS values compared to those in the humid zones (Table 2).There was a significant difference between the humid and dry zones inthe proportion of households that consumed fruits (P=0.017); eggs(P=0.003); fish, pulses, legumes & nuts, and sugar/honey (all Ps<0.001) and spices, condiments and beverages, P=0.001, during thelast 24 hours (Figure 2).There was a significant negative relationship between HHS andHDDS, r=-.35, P<0.001. WI related negatively with HHS, r=-.13,P=0.027, but positively with HDDS, r=0.21, P<0.001 (Table 3).Variable 1 Variable 2 r * PHHS HDDS -.35 <0.001HHS WI -.13 0.027HDDS WI 0.21 <0.001*Spearman’s rho correlationHHS= Household hunger score, HDDS= Household dietary diversity scores and WI= Wealth indexTable 3: Relationship between HHS, HDDS and WI in the humid and dry zones in Teso South and Bondo districts, Western KenyaFigure 2: Proportion of households consuming foods from different food groups during the last 24 hours in the humid and dry zones in Teso South and Bondo districts, Western Kenya3.4 4 2.834.542.626.262.153.47101020304050607080All zones Humid zone(LM1+LM2)Dry zone(LM3+LM4+LM5)Percentage (%)Severe hungerModerate hungerLittle to no hunger****•Chi square testSignificant (P<0.05)0 10 20 30 40 50 60 70 80 90 100Spices, condiments & beveragesSugar/ HoneyOils and fatsMilkPulses, legumes and nutsFishEggsMeat, Poultry, OffalsFruitsVegetablesRoots and tubersCerealsPercentage (%)Dry zoneHumid zone**ResultsCharacteristics of the study participants are presented in Table 1.Table 1: Characteristics of participants in the humid and dry zones in Western KenyaCharacteristics Min Max Mean SDAge of women (years) 16 52 25.8 ±6.4Household size 2 17 6.0 ±2.5Household dietary diversity score 1 11 6.9 ±1.6Household hunger score 0 6 1.2 ±1.2Household wealth Index -6.1 13.1 -.34 ±3.0

Household food security and dietary diversity in different agro-ecological zones in Western Kenya

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Household food security and dietary diversity in different agro-ecological zones in Western Kenya

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