Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009
This is a baseline survey data that was collected within the project ‘Managing agricultural biodiversity for better nutrition and health, improved livelihoods and more sustainable production systems in sub-Saharan Africa’ implemented by Bioversity International. The survey was conducted in Kitui Dis...
| Autores principales: | , , , , |
|---|---|
| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
| Publicado: |
Bioversity International and the International Center for Tropical Agriculture
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/109504 |
| _version_ | 1855525801723691008 |
|---|---|
| author | Morimoto, Yasuyuki Maundu, Patrick Imbumi, Maryam Kariuki, Lucy Tumbo, Dominic |
| author_browse | Imbumi, Maryam Kariuki, Lucy Maundu, Patrick Morimoto, Yasuyuki Tumbo, Dominic |
| author_facet | Morimoto, Yasuyuki Maundu, Patrick Imbumi, Maryam Kariuki, Lucy Tumbo, Dominic |
| author_sort | Morimoto, Yasuyuki |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This is a baseline survey data that was collected within the project ‘Managing agricultural biodiversity for better nutrition and health, improved livelihoods and more sustainable production systems in sub-Saharan Africa’ implemented by Bioversity International. The survey was conducted in Kitui District in Eastern Province of Kenya between 14 July and 5 August 2009. The area was chosen for best testing the research hypothesis: In rural farming communities there exists a relationship between access to local agrobiodiversity (domesticated, weedy and immediate wild) and dietary diversity which in turn has some link to nutritional and health status. Factors considered while choosing the area included: i) differential access to agrobiodiverisity among different communities living in close proximity, ii) easy access to the site, iii) high diversity of traditional foods and iv) richness in local knowledge. A structured questionnaire was formulated with following 13 sections , A) Demographic, B) Farm charactaeristics, C) Crop/Fruits diversity, D) Farming systems and activities, E) Personal preferences, nutrition knowledge, F) Labour profile, G) Livestock production, H) Asset holding, I) Cost of hired implements/machines, J) Housing, K) Income, L) Marketing constraints, and M) Institutional variables. Through individual interview at the household visit, the questionnaire was administered to 295 households at 14-15 homesteads per village. The average survey time per household was 1 hour and 15 munitus. Five (5) local enumerators were recruited from the 20 villages with the help of local leaders and provided for the training. These 295 households representing in total of 20 villages, 148 households in 10 villages in intervention (treatment) area, 147 households in the other 10 villages in none-intervention (control) area, were selected from a group of 60 villages which had been subjected to a clustering process based on soils, vegetation, agroecology, altitude and number of crop growing days per year, forming 6 clusters. From each of the 6 cluster groups (A-F), 1 or 2 target villages were selected randomly such that for each treatment village, there was a corresponding control village with similar characteristics (File 13: Project Area). Each village had 150-200 households. The households are defined as members of a family served from the same pot. The selected households have children under the age of 5 years and above 6 months which were randomly selected for study in each village. In order to establish a cause and effect relationship between the Agrobiodiversity, dietary diversity and nutrition/health, the research design combines two methods: 1) A“cross-sectional research design’ that surveys status only once and 2) a control group design where there is a control and treatment group (File 14: Research design). |
| format | Conjunto de datos |
| id | CGSpace109504 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Bioversity International and the International Center for Tropical Agriculture |
| publisherStr | Bioversity International and the International Center for Tropical Agriculture |
| record_format | dspace |
| spelling | CGSpace1095042025-12-08T10:29:22Z Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 Morimoto, Yasuyuki Maundu, Patrick Imbumi, Maryam Kariuki, Lucy Tumbo, Dominic agricultural development desarrollo agricola agricultural extension extension agricola agricultural landscape paisaje agricola agricultural research investigacion agraria agrobiodiversity agrobiodiversidad biodiversity biodiversidad biodiversity conservation conservacion de la diversidad biologica body measurements medicion del cuerpo community development desarrollo de la comunidad data datos databases bases de datos development projects proyectos de desarrollo diet dieta evaluation evaluacion farm equipment equipo de la explotacion agraria farm size tamano de la finca food security seguridad alimentaría human nutrition nutricion humana nutrition nutricion social indicators indicadores sociales social sciences ciencias sociales sociocultural systems sistemas socioculturales This is a baseline survey data that was collected within the project ‘Managing agricultural biodiversity for better nutrition and health, improved livelihoods and more sustainable production systems in sub-Saharan Africa’ implemented by Bioversity International. The survey was conducted in Kitui District in Eastern Province of Kenya between 14 July and 5 August 2009. The area was chosen for best testing the research hypothesis: In rural farming communities there exists a relationship between access to local agrobiodiversity (domesticated, weedy and immediate wild) and dietary diversity which in turn has some link to nutritional and health status. Factors considered while choosing the area included: i) differential access to agrobiodiverisity among different communities living in close proximity, ii) easy access to the site, iii) high diversity of traditional foods and iv) richness in local knowledge. A structured questionnaire was formulated with following 13 sections , A) Demographic, B) Farm charactaeristics, C) Crop/Fruits diversity, D) Farming systems and activities, E) Personal preferences, nutrition knowledge, F) Labour profile, G) Livestock production, H) Asset holding, I) Cost of hired implements/machines, J) Housing, K) Income, L) Marketing constraints, and M) Institutional variables. Through individual interview at the household visit, the questionnaire was administered to 295 households at 14-15 homesteads per village. The average survey time per household was 1 hour and 15 munitus. Five (5) local enumerators were recruited from the 20 villages with the help of local leaders and provided for the training. These 295 households representing in total of 20 villages, 148 households in 10 villages in intervention (treatment) area, 147 households in the other 10 villages in none-intervention (control) area, were selected from a group of 60 villages which had been subjected to a clustering process based on soils, vegetation, agroecology, altitude and number of crop growing days per year, forming 6 clusters. From each of the 6 cluster groups (A-F), 1 or 2 target villages were selected randomly such that for each treatment village, there was a corresponding control village with similar characteristics (File 13: Project Area). Each village had 150-200 households. The households are defined as members of a family served from the same pot. The selected households have children under the age of 5 years and above 6 months which were randomly selected for study in each village. In order to establish a cause and effect relationship between the Agrobiodiversity, dietary diversity and nutrition/health, the research design combines two methods: 1) A“cross-sectional research design’ that surveys status only once and 2) a control group design where there is a control and treatment group (File 14: Research design). 2020-09-08 2020-09-15T16:15:02Z 2020-09-15T16:15:02Z Dataset https://hdl.handle.net/10568/109504 en Open Access Bioversity International and the International Center for Tropical Agriculture Morimoto, Y.; Maundu, P.; Imbumi, M.; Kariuki, L.; Tumbo, D. (2020) Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009, https://doi.org/10.7910/DVN/94JTZY, Harvard Dataverse, V1, UNF:6:bmFpvdhQRk3dLgjG0/zM2A== [fileUNF] |
| spellingShingle | agricultural development desarrollo agricola agricultural extension extension agricola agricultural landscape paisaje agricola agricultural research investigacion agraria agrobiodiversity agrobiodiversidad biodiversity biodiversidad biodiversity conservation conservacion de la diversidad biologica body measurements medicion del cuerpo community development desarrollo de la comunidad data datos databases bases de datos development projects proyectos de desarrollo diet dieta evaluation evaluacion farm equipment equipo de la explotacion agraria farm size tamano de la finca food security seguridad alimentaría human nutrition nutricion humana nutrition nutricion social indicators indicadores sociales social sciences ciencias sociales sociocultural systems sistemas socioculturales Morimoto, Yasuyuki Maundu, Patrick Imbumi, Maryam Kariuki, Lucy Tumbo, Dominic Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title | Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title_full | Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title_fullStr | Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title_full_unstemmed | Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title_short | Socio-economic baseline survey data of 20 villages in Kitui district, Kenya in 2009 |
| title_sort | socio economic baseline survey data of 20 villages in kitui district kenya in 2009 |
| topic | agricultural development desarrollo agricola agricultural extension extension agricola agricultural landscape paisaje agricola agricultural research investigacion agraria agrobiodiversity agrobiodiversidad biodiversity biodiversidad biodiversity conservation conservacion de la diversidad biologica body measurements medicion del cuerpo community development desarrollo de la comunidad data datos databases bases de datos development projects proyectos de desarrollo diet dieta evaluation evaluacion farm equipment equipo de la explotacion agraria farm size tamano de la finca food security seguridad alimentaría human nutrition nutricion humana nutrition nutricion social indicators indicadores sociales social sciences ciencias sociales sociocultural systems sistemas socioculturales |
| url | https://hdl.handle.net/10568/109504 |
| work_keys_str_mv | AT morimotoyasuyuki socioeconomicbaselinesurveydataof20villagesinkituidistrictkenyain2009 AT maundupatrick socioeconomicbaselinesurveydataof20villagesinkituidistrictkenyain2009 AT imbumimaryam socioeconomicbaselinesurveydataof20villagesinkituidistrictkenyain2009 AT kariukilucy socioeconomicbaselinesurveydataof20villagesinkituidistrictkenyain2009 AT tumbodominic socioeconomicbaselinesurveydataof20villagesinkituidistrictkenyain2009 |