Related Experiment Video
Updated: Aug 26, 2025

Assessment of Social Transmission of Food Preferences Behaviors
Published on: January 25, 2018
Food Vendors and the Obesogenic Food Environment of an Informal Settlement in Nairobi, Kenya: a Descriptive and
Kyle R Busse1,2, Rasheca Logendran3, Mercy Owuor4
1Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC, 27599, USA. kybusse@live.unc.edu.
Abstract:
Food environments of urban informal settlements are likely drivers of dietary intake among residents of such settlements. Yet, few attempts have been made to describe them. The objective of this study was to characterize the food environment of a densely-populated informal settlement in Nairobi, Kenya according to the obesogenic properties and spatial distribution of its food vendors. In July-August 2019, we identified food vendors in the settlement and classified them into obesogenic risk categories based on the types of food that they sold. We calculated descriptive statistics and assessed clustering according to obesogenic risk using Ripley's K function. Foods most commonly sold among the 456 vendors in the analytic sample were sweets/confectionary (29% of vendors), raw vegetables (28%), fried starches (23%), and fruits (21%). Forty-four percent of vendors were classified as low-risk, protective; 34% as high-risk, non-protective; 16% as low-risk, non-protective; and 6% as high-risk, protective. The mean distance (95% confidence interval) to the nearest vendor of the same obesogenic risk category was 26 m (21, 31) for vendors in the low-risk, protective group; 29 m (25, 33) in the high-risk, non-protective group; 114 m (88, 139) in the high-risk, protective group; and 43 m (30, 56) in the low-risk, non-protective group. Clustering was significant for all obesogenic risk groups except for the high-risk, protective. Our findings indicate a duality of obesogenic and anti-obesogenic foods in this environment. Clustering of obesogenic foods highlights the need for local officials to take action to increase access to health-promoting foods throughout informal settlements.
Related Concept Videos
Dietary Connections
Analysis of Population Pharmacokinetic Data
Obesity
Regulation of Food Intake
Assessment of the Gastrointestinal System II: Health Perception Pattern
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...

