Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda

This paper presents data collected in July 2016 to assess the consumption patterns and dietary quality among vulnerable urban consumers at the Base of Pyramid (BoP). The data was collected within the project ‘Making Value Chains Work for Food and Nutrition Security of Vulnerable Populations in East...

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Autores principales: Onyango, Kevin Omondi, Chege, Christine Gacheri Kiria, Jager, Matthias, Karanja, David, Nkalubo, Stanley T.
Formato: Conjunto de datos
Publicado: 2023
Materias:
Acceso en línea:https://hdl.handle.net/10568/130050
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author Onyango, Kevin Omondi
Chege, Christine Gacheri Kiria
Jager, Matthias
Karanja, David
Nkalubo, Stanley T.
author_browse Chege, Christine Gacheri Kiria
Jager, Matthias
Karanja, David
Nkalubo, Stanley T.
Onyango, Kevin Omondi
author_facet Onyango, Kevin Omondi
Chege, Christine Gacheri Kiria
Jager, Matthias
Karanja, David
Nkalubo, Stanley T.
author_sort Onyango, Kevin Omondi
collection Repository of Agricultural Research Outputs (CGSpace)
description This paper presents data collected in July 2016 to assess the consumption patterns and dietary quality among vulnerable urban consumers at the Base of Pyramid (BoP). The data was collected within the project ‘Making Value Chains Work for Food and Nutrition Security of Vulnerable Populations in East Africa’ which was funded by the German Federal Ministry for Economic Cooperation and Development (BMZ). The project was led by the Alliance of Bioversity and CIAT and implemented in partnership with KALRO, NARO, Goettingen University and UHOH. The project was under the CGIAR flagship program “Food Systems for Healthier Diets” under the Research Program on Agriculture for Nutrition and Health (A4NH). A cross-sectional survey was conducted to collect data with the goal of assessing critical and sensible ways in which market systems work to improve the consumption of more diverse, safe and nutrient-dense foods. The questionnaire had five sections. Section A captured the geographical location of the households and interview day details. Section B captured household demographic details. Section C focused on household nutritious porridge consumption and preferences. In Section D, household access to nutrition information was captured while Section E details household assets and their nominal values. The anonymized data is arranged into six files; 01Identifier16 file contains all the data from section A. Similarly, household demographic information is in file 02Demography16. 03Consumption16, 04Flourattributes16, 05Assets16 and 06Text16 contain household nutritious porridge consumption and sources of the flour, important porridge flour quality attributes, household assets and their values, and crosscutting general household level data respectively.
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spelling CGSpace1300502024-04-25T06:01:31Z Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda Onyango, Kevin Omondi Chege, Christine Gacheri Kiria Jager, Matthias Karanja, David Nkalubo, Stanley T. market access value chain analysis urban poor This paper presents data collected in July 2016 to assess the consumption patterns and dietary quality among vulnerable urban consumers at the Base of Pyramid (BoP). The data was collected within the project ‘Making Value Chains Work for Food and Nutrition Security of Vulnerable Populations in East Africa’ which was funded by the German Federal Ministry for Economic Cooperation and Development (BMZ). The project was led by the Alliance of Bioversity and CIAT and implemented in partnership with KALRO, NARO, Goettingen University and UHOH. The project was under the CGIAR flagship program “Food Systems for Healthier Diets” under the Research Program on Agriculture for Nutrition and Health (A4NH). A cross-sectional survey was conducted to collect data with the goal of assessing critical and sensible ways in which market systems work to improve the consumption of more diverse, safe and nutrient-dense foods. The questionnaire had five sections. Section A captured the geographical location of the households and interview day details. Section B captured household demographic details. Section C focused on household nutritious porridge consumption and preferences. In Section D, household access to nutrition information was captured while Section E details household assets and their nominal values. The anonymized data is arranged into six files; 01Identifier16 file contains all the data from section A. Similarly, household demographic information is in file 02Demography16. 03Consumption16, 04Flourattributes16, 05Assets16 and 06Text16 contain household nutritious porridge consumption and sources of the flour, important porridge flour quality attributes, household assets and their values, and crosscutting general household level data respectively. 2023-04 2023-04-19T15:54:14Z 2023-04-19T15:54:14Z Dataset https://hdl.handle.net/10568/130050 Open Access Onyango, Kevin Omondi; Chege, Christine Gacheri Kiria; Jager, Matthias; David Karanja; Nkalubo, Stanley, 2023, "Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda", https://doi.org/10.7910/DVN/LHVTNA, Harvard Dataverse, V1
spellingShingle market access
value chain analysis
urban poor
Onyango, Kevin Omondi
Chege, Christine Gacheri Kiria
Jager, Matthias
Karanja, David
Nkalubo, Stanley T.
Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title_full Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title_fullStr Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title_full_unstemmed Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title_short Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda
title_sort food and nutrition security in urban slums consumer survey data for kenya and uganda
topic market access
value chain analysis
urban poor
url https://hdl.handle.net/10568/130050
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