Literature DB >> 36222974

Food Vendors and the Obesogenic Food Environment of an Informal Settlement in Nairobi, Kenya: a Descriptive and Spatial Analysis.

Kyle R Busse1,2, Rasheca Logendran3, Mercy Owuor4, Hillary Omala4, Erick Nandoya4, Alice S Ammerman3,5, Stephanie L Martin3,6.   

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.
© 2022. The New York Academy of Medicine.

Entities:  

Keywords:  GIS; Nutrition transition; Slums; Ultra-processed food

Year:  2022        PMID: 36222974     DOI: 10.1007/s11524-022-00687-7

Source DB:  PubMed          Journal:  J Urban Health        ISSN: 1099-3460            Impact factor:   5.801


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