The influence of urban spatial characteristics on food insecurity among the low-income households: The case of Naivasha town, Kenya

Simon. N. Mwangi; Charity Irungu; Daniel M. Nzengya

doi:10.51867/ajernet.6.3.39

Authors

Simon. N. Mwangi St. Paul’s University, Kenya
Charity Irungu St. Paul’s University, Kenya https://orcid.org/0000-0002-2727-0970
Daniel M. Nzengya St. Paul’s University, Kenya https://orcid.org/0000-0001-6588-364X

DOI:

https://doi.org/10.51867/ajernet.6.3.39

Keywords:

Food Insecurity, Households, Naivasha Town, Spatial Characteristics, Urban

Abstract

Food insecurity (FI) exists when people do not have secure access to enough amounts of food that is safe and nutritious to enhance normal growth and development and an active and healthy life. Globally, FI prevalence of 25.5% is experienced in towns. FI is prevalent in Kenyan towns too. For example, food insecurity prevalence of up to 86% has been reported in Thika town. The measurement of FI in urban areas is done using rural-oriented approaches thus overlooking critical urban challenges and systemic drivers. One major challenge of the current food insecurity metrics is to overlook spatial variations within urban areas. The influence of spatial characteristics on FI is therefore poorly understood and is unavailable in Naivasha town. The purpose of this study was to examine how urban spatial characteristics influence food insecurity in Naivasha town, Kenya. The research was anchored in the sector theory of urban growth. A quantitative cross-sectional survey design was employed, targeting low-income households from six residential locations in Naivasha town. Using a multistage sampling technique, a total of 390 households were selected from the target population of 117,633. Data was collected through a pretested structured questionnaire and analysed using Kruskal-Wallis H test and multivariable logistic regression with SPSS version 26. Kruskal-Wallis H test results showed that perceived food utilization was significantly (p=0.00) different among the residential areas studied but that was not the case with household food insecurity access score. Regression analysis revealed unavailability of open markets significantly predicted household food insecurity access prevalence (p=0.04), while supermarket unavailability (p=0.039) and time to the food sources (p=0.049) significantly predicted perceived food utilization. These findings indicate that FI in Naivasha is influenced by the spatial characteristics of the town. Recommendations include improving access to open markets which are a significant source of food.

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