DOI: 10.7910/dvn/lhvtna
title: Food and Nutrition Security in Urban Slums: Consumer Survey data for Kenya and Uganda

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 Bioversity International and the International Center for Tropical Agriculture 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.&lt;br&gt;&lt;br&gt; Metodology:Data collection site
The data was collected in Nairobi, Kenya and Kampala, Uganda. Nairobi is Kenya’s capital city. Projections by the Kenya Bureau of Statistics (KNBS) indicate that the county’s population will rise from 3.14 million recorded in the 2009 census to 5.96 million by 2022 with an inter-censual growth rate of 3.8 per cent (County Government of Nairobi, 2018). The city has the largest slum in East and Central Africa; Kibera slum, and others such as Kawangware, Mathare, Kangemi, Korogocho, Majengo, Kitui village and Kiambiu. Poverty levels are high in the city with the most affected groups being the unemployed youth, women, persons with disabilities, female and child-headed households, slum dwellers and the aged (County Government of Nairobi, 2018). Poor access to basic infrastructure is also a common characteristic of the many slums in Nairobi. On the other hand, Kampala is Uganda's administrative and commercial capital city with a population of approximately 1.2 million inhabitants (Robinah et al., 2013). Kampala is also a rapidly growing city and is home to Slums such as Bwaise, Katwe, Kisenyi, Kibuli, Katanga, Nabulabye, Naguru2 and Nsambya (Association of Physicians of Uganda, 2018). In Nairobi, Kibera, Embakasi, Mathare and Dagoreti slums were selected as the study site while Bwaise, Kawempe, Kamwokya and Kasubi parishes were the study areas in KampalaA multi-stage sampling strategy was used to select respondents. First, we used the national statistics (Emwanu et al., 2004; KNBS, 2015) and information from the administrative offices to identify four urban BoP locations with the highest poverty levels in each of the two cities. In Nairobi, the selected locations were Kibera, Embakasi, Mathare and Dagoreti while in Kampala data collection was done in Bwaise, Kawempe, Kamwokya and Kasubi parishes. Second, households from these locations were randomly selected, using a systematic random sampling technique. We interviewed a total of 600 households, 300 from Kenya and 300 from Uganda. Survey preparation involved several activities. First, survey tool development, design and programming into SurveyCTO. Second, enumerator recruitment and training. We selected enumerators from a pool of recent graduate applicants with sufficient experience in carrying out household surveys and a good knowledge of the two cities (Nairobi and Kampala). The selected enumerators were then intensively trained for 3 days (11th – 13th July 2016). The training covered each question in the questionnaire, the purpose of each question and a suitable means of handling each question. Enumerators were additionally trained on Computer Aided Personal Interview (CAPI) tools and using tablets in data collection. Prior to the actual fieldwork, the teams held a pretest of the survey in non-sampled villages in Nairobi and Kampala. Actual data collection took 15 days (16th – 30th July 2016) under the guidance of team leaders in collaboration with local authorities and village elders. During the survey, a research associate from the Bioversity International and the International Center for Tropical Agriculture checked for inconsistencies, patterns and outliers in the data on a daily basis and provided detailed feedback to data collection teams as a strategy for quality assurance. After the survey, we downloaded the raw data as Comma Separated Values (CSV) files. We later imported the CSV files into STATA for cleaning.