------------------- GENERAL INFORMATION ------------------- 1. Title of dataset: Nigeria Nutrition Conversion Table (Nigeria_NCT) 2. Contact Co-principal Investigator Contact Information Name: Lara Cockx Institution: European Commission Joint Research Center, Seville, Spain and International Food Policy Research Institute, Lilongwe, Malawi Email: l.cockx@cgiar.org ORCID: https://orcid.org/0000-0002-7708-2791 Co-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 consumption in Nigeria we used information on household food consumption collected as part of the Nigeria Living Standard Survey (NLSS) and General Household Survey (GHS) for 2018/2019. 4. Description of the dataset: it includes the nutrients composition of food items reported in the food composition module of the 2018/2019 NLSS and GHS. 5. Notes 6. Deposit date: June 25 2025 7. Date: June 25 2025 8. Language: English -------------------------- AUTHOR INFORMATION -------------------------- 1. Author Name: Lara Last name: Cockx Institution: European Commission Joint Research Center, Seville, Spain Email: lcockx@gmail.com ORCID: https://orcid.org/0000-0002-7708-2791 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 -------------------------- METHODOLOGY -------------------------- 1. Methodology: We built the Nutrition Conversion table for Nigeria 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 four steps, as described below: Step 1. Revise, identify and harmonize all food items reported in the food consumption module of the 2018/2019 NLSS and Nigeria GHS. A total of 201 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 contacted key informants in Nigeria 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:  Emily Ikhide at the Gender and Inclusivity Unit, National Institute for Legislative and Democratic Studies, National Assemngly, Abuja, Nigeria.  Oluwasola E. Omoju: Department of Economic and Social Research, National Institute for Legislative and Democratic Studies, National Assemngly, Abuja, Nigeria.  Olutayo Adeyemi: Department of Human Nutrition and Dietetics, University of Ibadan, Ibadan, Nigeria 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 Nigeria) 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. Only internationally validated FCT/FDBs were considered for the matching, and we prioritized the FCT/FDB to be searched based on data quality and completion, 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:  West Africa Fooc Composition Table 2019 (145 food items, 72.1% of the total)  USDA Food Database (38 food items, 18.9% of the total)  Nigeria Food Composition Table 2019 (13 items, 6.5%)  Kenya Food Composition Table 2018 (1 food item, 0.5% of the total)  East Asia Food Composition Table (1 food item, 0.5% of the total)  Spanish Food Composition Database (1 food item, 0.5% of the total) Step 3. Select food item in the FCT/FDB and mathing method to be used 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 type of food matching: direct or average 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: autres patisseries) 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 applied to the food items 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. The Yield factor refers to how the weight of a food changes during preparation and cooking, primarily due to moisture loss or gain, thus it adjusts for the change in weight that occurrs during cooking or processing, allowing the quantities reported in the survey (often in cooked form) to be converted in their raw equivalents before matching them with nutrient values in food composition tables. The Retention factor, on the other hand, accounts for the proportion of each nutrient that remains in the food after cooking or processing. Both factors need to be applied when the foods are consumed cooked and reported as such in the survey , but only available in the raw form in the Food Composition Table (FCT) or Food Database (FDB). We used Yield and Retention factors from the Food Composition Table for Western Africa as well as the USDA Table of Yield Factors and Table of Nutrient Retention Factors. 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 3.3 The information available for mixed dishes. For most of these prepared dishes, we found appropriate matches in the FCT/FDB consulted. Only in one case (yellow gari) we used the ingredients in the recipe. Step 4: Impute nutrient values to survey food items based on food matching. Once the food items in the survey have been matched to corresponding food items in the FCT/DB the nutrient values from the FCT/FDB are imputed to the matched food items in the NCT. In ths step, is important to check that expression of the nutrient as well as the units are the same in both the survey and the FCT/FDB. If any nutrients are missing from the FCT being used, we completed these values with similar food items with complete nutrients information from the same FCT/FDB or from other reliable source. We followed these steps to obtain the NCT as recommended by FAO guidelines (2012). 2. Software: Excel. -------------------------- KEYWORDS -------------------------- 1. Keywords: Nutrition Conversion Table, Nigeria, nutrients consumption, Nigeria General Household Survey, -------------------------- SPONSORSHIP INFORMATION AND GRANT IDs -------------------------- 1. Grant Information: This Nutrition Conversion Table was developed within the European Commission Joint Research Centre contract number -------------------------- 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. FAO. (2012). FAO/INFOODS Guidelines for Food Matching. Version 1.2. FAO. 2. Related dataset: Living Standards Survey 2018-2019 https://doi.org/10.48529/8gbe-z155. Available at https://microdata.worldbank.org/index.php/catalog/3827 General Household Survey, Panel 2018-2019. Available at https://microdata.fao.org/index.php/catalog/1374 -------------------------- GEOGRAPHIC INFORMATION -------------------------- 1. Spatial coverage: Nigeria -------------------------- TEMPORAL INFORMATION -------------------------- 1. Time period coverage: 2018/2019 -------------------------- FILES -------------------------- 1. Files: one excel file containing the Nigeria Nutrition Conversion Table. -------------------------- LICENSES AND PRIVACITY -------------------------- 1. Licenses: Open Data Commons Attribution License (ODC-By). -------------------------- OTHERS -------------------------- 1. Data dictionary