Geodemographic Patterns of Meat Expenditure in Great Britain.

Diet Environment Expenditure patterns Geodemographic classification Health

Journal

Applied spatial analysis and policy
ISSN: 1874-463X
Titre abrégé: Appl Spat Anal Policy
Pays: Netherlands
ID NLM: 101631768

Informations de publication

Date de publication:
2021
Historique:
received: 03 12 2019
accepted: 12 05 2020
entrez: 1 11 2021
pubmed: 2 11 2021
medline: 2 11 2021
Statut: ppublish

Résumé

The future of the meat industry will require the management of important trade-offs between economic, environmental and health aspects of both humans and animals. Understanding the patterns and trends of meat expenditure and consumption is crucial for assessing the current resilience of the system and for economic, planning, health and environmental applications. Here, we show how the technique of geodemographic classification, combined with fine scale expenditure estimates can be used to explore temporal and spatial patterns of meat expenditure in Great Britain between 2008 and 2017. Whilst the expenditure patterns of some food categories such as sausages remained relatively consistent, others such as lamb show a trend towards a reduced proportion of expenditure and increased inequality of purchases. Short term changes in expenditure patterns also occurred, potentially due to product specific price variability, price elasticities or zoonotic disease scare. Environmental attitudes, financial constraints and the prominence of communities who do not eat meat for religious or cultural reasons are likely to be driving the differences between geodemographic groups. The methodology and results could be a valuable tool for policy makers in the meat industry and beyond.

Identifiants

pubmed: 34721723
doi: 10.1007/s12061-020-09344-5
pii: 9344
pmc: PMC8550722
doi:

Types de publication

Journal Article

Langues

eng

Pagination

563-590

Informations de copyright

© The Author(s) 2020.

Déclaration de conflit d'intérêts

Conflict of InterestThe authors declare that they have no conflict of interest.

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Auteurs

William H M James (WHM)

School of Geography and Leeds Institute for Data Analytics, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire LS2 9JT UK.

Nik Lomax (N)

School of Geography and Leeds Institute for Data Analytics, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire LS2 9JT UK.

Mark Birkin (M)

School of Geography and Leeds Institute for Data Analytics, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire LS2 9JT UK.

Lisa M Collins (LM)

Faculty of Biological Sciences, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire LS2 9JT UK.

Classifications MeSH