University of Hertfordshire

  • Caitlin Kirby
  • Kathrin Specht
  • Runrid Fox-Kämper
  • Jason Hawes
  • Nevin Cohen
  • Silvio Caputo
  • Rositsa Ilieva
  • Agnès Lelièvre
  • Lidia Poniży
  • Victoria Schoen
  • Chris Blythe
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Original languageEnglish
Article number104110
JournalLandscape and Urban Planning
Volume212
DOIs
Publication statusPublished - Aug 2021

Abstract

Urban agriculture is an increasingly popular approach to addressing negative social and health effects of cities. Social benefits of urban agriculture include improved health and wellbeing, economic opportunities, social cohesion, and education. However, the extent to which urban agriculture participants are motivated by or experience these impacts has rarely been measured quantitatively, especially across the many different types of urban agriculture. We analyzed survey data from 74 urban agriculture sites in France, Germany, Poland, the United Kingdom, and the United States to quantitatively assess the relationships between urban agriculture types, farmers and gardeners’ motivations, and the social impacts of urban agriculture. Through factor analysis, we established valid and reliable measurements of participants’ motivations and impacts. We identified four scales: general wellbeing impacts, nutritional health impacts, economic interests, and socialization motivations. Through multivariate analysis of variance, we document significant differences in motivations and reported impacts across types of urban agriculture. Finally, we conducted a multilevel multivariate analysis to explore the predictors of general wellbeing impacts. Participants with stronger economic interests, stronger socialization motivations, and who are owners or primary operators of their plots would be predicted to report greater general wellbeing impacts of urban agriculture. These results provide data about the impacts of urban agriculture projects that enable urban planners and policymakers to maximize the desired social benefits of urban agriculture.

Notes

Funding Information: This paper is based on FEW-meter project, funded by ESRC, UK , grant number ES/S002170/2 ; by BMBF: Germany , grant number 01LF1801A ; by ANR: France , grant number ANR-17-SUGI-0001-01 ; by NSF: USA, Belmont Forum 18929627; by NCN: Poland, grant no 2017/25/Z/HS4/03048; and by European Union’s Horizon 2020 research and innovation programme (GA No 730254) under the JPI Urban Europe’s call “SUGI - FWE Nexus”. The German-American Fulbright Commission also provided support for this project. Funding Information: This paper is based on FEW-meter project, funded by ESRC, UK, grant number ES/S002170/2; by BMBF: Germany, grant number 01LF1801A; by ANR: France, grant number ANR-17-SUGI-0001-01; by NSF: USA, Belmont Forum 18929627; by NCN: Poland, grant no 2017/25/Z/HS4/03048; and by European Union's Horizon 2020 research and innovation programme (GA No 730254) under the JPI Urban Europe's call ?SUGI - FWE Nexus?. The German-American Fulbright Commission also provided support for this project. Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

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