Consumption intensity of leafy African indigenous vegetables: towards enhancing nutritional security in rural and urban dwellers in Kenya

Eric Obedy Gido (), Oscar Ingasia Ayuya, George Owuor and Wolfgang Bokelmann
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Eric Obedy Gido: Humboldt University of Berlin
Oscar Ingasia Ayuya: Egerton University
George Owuor: Egerton University
Wolfgang Bokelmann: Humboldt University of Berlin

Agricultural and Food Economics, 2017, vol. 5, issue 1, 1-16

Abstract: Abstract Estimation of consumption intensity of African indigenous vegetables (AIVs) is important to understand how their utilization can be enhanced at the household level. The study evaluated consumption intensity of leafy AIVs using the zero-inflated negative binomial regression model. A multistage sampling technique was used to select a random sample of 450 rural and urban respondents, and data were collected using a pre-tested semi-structured questionnaire. The findings revealed that consumption intensity of leafy AIVs were higher in rural than in urban dwellers with a mean of four and two times a week, respectively. Age, occupation, household size, diversity of AIV leaves, market distance, awareness of AIV’s medicinal benefits and proportion of income allocated to food purchases significantly influenced consumption intensity of leafy AIVs. Strategies that could promote the transfer of AIVs’ traditional knowledge to uninformed consumer segments such as male and younger decision-makers could increase the consumption intensity of leafy AIVs in rural dwellers. Similarly, the consumption intensity of leafy AIVs in urban dwellers could increase through the promotion of the value addition activities of sorting and plucking vegetable leaves from their stalks before marketing. Finally, in both rural and urban dwellers, promotion of AIV diversity in food systems through diversified production and well-coordinated market supply chains could increase consumption intensity of leafy AIVs.

Keywords: African indigenous vegetables; Consumption intensity; Micronutrients; Negative binomial regression; Rural; Urban; Vegetable leaves (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1186/s40100-017-0082-0

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