Local level estimates of food, drink and tobacco expenditure for Great Britain

We present expenditure estimates for 106 product categories across Great Britain for the years 2008-2016. Estimates are at the Local Authority District level (n = 380) and the categories cover all food, drink and tobacco commodities. Reliable, local level expenditure estimates are crucial for unders...

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Bibliographic Details
Published in:Scientific data 2019-05, Vol.6 (1), p.56, Article 56
Main Authors: James, William H M, Lomax, Nik, Birkin, Mark
Format: Article
Language:English
Subjects:
Beverages - economics
Commerce
Computer applications
Computer Simulation
Data Descriptor
Environmental management
Expenditures
Family Characteristics
Food - economics
Geography
Humans
Income
Meat
Meat industry
Public health
Socioeconomic Factors
Tobacco
Tobacco Products - economics
Trends
United Kingdom
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Summary:We present expenditure estimates for 106 product categories across Great Britain for the years 2008-2016. Estimates are at the Local Authority District level (n = 380) and the categories cover all food, drink and tobacco commodities. Reliable, local level expenditure estimates are crucial for understanding broader market trends, assessing economic stability and for projections. This is especially important for commodities such as alcohol, tobacco and unhealthy foods due to their role in the prevalence of non-communicable diseases. There has been relatively little research into local area spatial patterns of expenditure, with existing estimates often of insufficient resolution for informing planning decisions. We use spatial microsimulation to create an archive of expenditure datasets. This was achieved by linking socio-demographic foundations with detailed datasets on individual expenditure. Whilst initially developed to aid investigations into sociodemographic trends in the meat industry, the data have reuse potential in a number of disciplines, including public health, economics, retail geography and environmental management. The framework could be applied to other regions with appropriate data.
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-019-0064-z