------------------- GENERAL INFORMATION ------------------- 1. Title of dataset: Kenya Nutrition Conversion Table (Kenya_NCT) 2. Contact Principal Investigator Contact Information Name: Estefanía Custodio Institution: National Centre for Tropical Diseases (CNMT), Carlos III Health Institute (ISCIII), Madrid, 28029 CIBER Infectious diseases, Carlos III Health Institute (ISCIII); Madrid, 28029 Email:ecustodio@isciii.es ORCID:http://orcid.org/0000-0002-5514-3151 3. Description of the project: In order to estimate the nutrients intake from the food consumption module of the 2015/2016 Kenya Integrated Household Budget Survey (KIHBS), each of the food items reported in that module is matched with a food item in the Food Composition Table (FCT) or Food Database (FDB) of choice, and nutrients composition are then compiled in what is called the nutrition conversion table (NCT). 4. Description of the dataset: it includes the nutrients composition of food items reported in the food composition module of the 2015/2016 KIHBS. 5. Notes 6. Deposit date: September 18th 2024 7. Date: Junes 2022 8. Language: English -------------------------- AUTHOR INFORMATION -------------------------- 1. Author Name: Estefanía Last name: Custodio Institution:National Centre for Tropical Diseases (CNMT), Carlos III Health Institute (ISCIII), Madrid, 28029 CIBER Infectious diseases, Carlos III Health Institute (ISCIII); Madrid, 28029 Email:ecustodio@isciii.es ORCID:http://orcid.org/0000-0002-5514-3151 Name: Sofía Last name: Jiménez Institution: School of Business and Economics, University of Zaragoza, Spain Email: sjimenez@unizar.es ORCID: https://orcid.org/0000-0001-8215-3227 Name: María Priscila Last name: Ramos Institution: Departamento de Economía, Facultad de Ciencias Económicas, Universidad de Buenos Aires, e Instituto Interdisciplinario de Economía Política de Buenos Aires, CONICET–Universidad de Buenos Aires, Buenos Aires, Argentina. Email: mpramos@economicas.uba.ar ORCID: https://orcid.org/0000-0002-0552-9486 -------------------------- METHODOLOGY -------------------------- 1. Methodology: We built the Nutrition Conversion table (NCT) for Kenya following a food matching method of food items as consumed. That is, taking into account the cooking method applied to food items before their consumption. We followed three steps, as described below: Step 1. Revise and identify all food items reported in the food consumption module of the Kenya Integrated Household Budget Survey (KIHBS) 2015/2016. A total of 210 items were considered, and we used different sources to clearly identify them, as well as its main way of consumption (cooking method) in order to apply the correct matching in the following steps. Sources consulted were: 1.1 Consultation with key informants We consulted the methodology and process of the NCT elaboration with key experts in the field: - Ana Moltedo,from the Statistics Division,Food and Agriculture Organization of the United Nations (FAO) - Cristina Alvarez, from the Child Nutrition and Development Section, UNICEF We contacted key informants in Kenya to translate some terms reported in local languages, to convert food quantities in standardized units, to obtain scientific names (when available) of edible plants local species, and to learn main way of consumption of certain food items. Key informants consulted:  Statician at the KNBS: Kenya National Bureau of Statistics  Nutrition officer: UNICEF, Kenya  Economy officer: FAO, Kenya 1.2 Consultation of specialized literature In order to identify the best suitable item in the FCT/FDBs used for the matching we consulted bibliographic resources specialized in Africa (and Kenya) fauna and flora, as well as gastronomy and culinary practices. Step 2. Select the food composition tables/databases (FCT/FDB) to be used for the matching. We used the Kenya 2018 Food Composition Table for the majority of the food matchings (71.8% of food items), but the remaining were not available in the Kenya FCT and we had to search in other FCT/FCBs. Only internationally validated FCT/FDBs were considered for the matching, and we prioritized the FCT/FDB to be searched based on geographical location as well as language and cultural linkages. The FCT/FDBs used by number of food items and percentage from the total are describe below:  Kenya Food Composition Table (145 food items, 71.8% of the total)  USDA Food Database (33 food items, 16.3% of the total)  Tanzania Food Composition Table (12 items, 5.9%)  West African Food Composition Table (10 food items, 5.0% of the total)  Indian Food Composition Table (1 food item, 0.5% of the total)  Frida Food Database (1 food item, 0.5% of the total) Step 3. Identify the most appropriate food matching method for each food item We performed the food matching with the food item as consumed, that is taking into account the cooking method applied to the food item before being consumed. Thus, for the food matching we took into account: 3.1 The definition of the food item and the identification of a suitable food item in any of the FCTs consulted. If the food item is well defined and concrete in the survey it is possible to find a corresponding match in the FCT of choice and make a direct matching. However, if the food items refer to a group of foods (ex: Other pulses) it is necessary to do the matching with several food items in the FCT and do the average of the nutrients content. 3.2 The cooking method used for the food item before consumption The cooking method applied to a food item before being consumed has an impact in the micronutrient content (see Moltedo A, et al 2020), and thus it is important to apply the corresponding conversion factors such a Yield or Retention factors to obtain more accurate information on the micronutrients consumption. Individual food consumption surveys usually collect the cooking method of the foods being consumed. However, in household consumption surveys the cooking method is usually omitted, thus it is important to consult resources on culinary practices and local gastronomy, as reported in Step 1. When there was no information on the main cooking method used for a particular food item we calculated the average of the food item cooked by different methods 2. Software: Excel. -------------------------- KEYWORDS -------------------------- 1. Keywords: Nutrition Conversion Table, Kenya, nutrients consumption, food security, Household Consumption Survey -------------------------- SPONSORSHIP INFORMATION AND GRANT IDs -------------------------- 1. Grant Information: This Nutrition Conversion Table was developed within the European Commission Joint Research Centre administrative arrangement JRC N° 35676-2019-NFP -------------------------- RELATED PUBLICATIONS -------------------------- 1. Related publication: Moltedo A, Jiménez S, Álvarez-Sánchez C, Manyani T, Ramos MP, Custodio E. Raw versus cooked food matching: Nutrient intake using the 2015/16 Kenya Integrated Household Budget Survey. J Food Compost Anal. 2021 Sep;102:103879. doi: 10.1016/j.jfca.2021.103879. PMID: 34483479; PMCID: PMC8356072. Ramos MP, Custodio E, Jiménez S, Mainar-Causapé AJ, Boulanger P, Ferrari E. Do agri-food market incentives improve food security and nutrition indicators? a microsimulation evaluation for Kenya. Food Secur. 2022;14(1):209-227. doi: 10.1007/s12571-021-01215-2. Epub 2021 Sep 30. PMID: 34611466; PMCID: PMC8483734. 2. Related dataset: KIHBS 2015/2016, which is available upon request from the Kenya National Bureau of Statistics (KNBS), at KNBS's website https://www.knbs.or.ke -------------------------- GEOGRAPHIC INFORMATION -------------------------- 1. Spatial coverage: Kenya -------------------------- TEMPORAL INFORMATION -------------------------- 1. Time period coverage: 2015/2016 -------------------------- FILES -------------------------- 1. Files: one excel file containing the Kenya Nutrition Conversion Table. -------------------------- LICENSES AND PRIVACITY -------------------------- 1. Licenses: Open Data Commons Attribution License (ODC-By). -------------------------- OTHERS -------------------------- 1. Data dictionary