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Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions
BACKGROUND: In England, the responsibility to address food insecurity lies with local government, yet the prevalence of this social inequality is unknown in small subnational areas. In 2018 an index of small-area household food insecurity risk was developed and utilised by public and third sector or...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733884/ https://www.ncbi.nlm.nih.gov/pubmed/36490256 http://dx.doi.org/10.1371/journal.pone.0267260 |
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author | Smith, Dianna M. Rixson, Lauren Grove, Grace Ziauddeen, Nida Vassilev, Ivaylo Taheem, Ravita Roderick, Paul Alwan, Nisreen A. |
author_facet | Smith, Dianna M. Rixson, Lauren Grove, Grace Ziauddeen, Nida Vassilev, Ivaylo Taheem, Ravita Roderick, Paul Alwan, Nisreen A. |
author_sort | Smith, Dianna M. |
collection | PubMed |
description | BACKGROUND: In England, the responsibility to address food insecurity lies with local government, yet the prevalence of this social inequality is unknown in small subnational areas. In 2018 an index of small-area household food insecurity risk was developed and utilised by public and third sector organisations to target interventions; this measure needed updating to better support decisions in different settings, such as urban and rural areas where pressures on food security differ. METHODS: We held interviews with stakeholders (n = 14) and completed a scoping review to identify appropriate variables to create an updated risk measure. We then sourced a range of open access secondary data to develop an indices of food insecurity risk in English neighbourhoods. Following a process of data transformation and normalisation, we tested combinations of variables and identified the most appropriate data to reflect household food insecurity risk in urban and rural areas. RESULTS: Eight variables, reflecting both household circumstances and local service availability, were separated into two domains with equal weighting for a new index, the Complex Index, and a subset of these to make up the Simple Index. Within the Complex Index, the Compositional Domain includes population characteristics while the Structural Domain reflects small area access to resources such as grocery stores. The Compositional Domain correlated well with free school meal eligibility (r(s) = 0.705) and prevalence of childhood obesity (r(s) = 0.641). This domain was the preferred measure for use in most areas when shared with stakeholders, and when assessed alongside other configurations of the variables. Areas of highest risk were most often located in the North of England. CONCLUSION: We recommend the use of the Compositional Domain for all areas, with inclusion of the Structural Domain in rural areas where locational disadvantage makes it more difficult to access resources. These measures can aid local policy makers and planners when allocating resources and interventions to support households who may experience food insecurity. |
format | Online Article Text |
id | pubmed-9733884 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-97338842022-12-10 Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions Smith, Dianna M. Rixson, Lauren Grove, Grace Ziauddeen, Nida Vassilev, Ivaylo Taheem, Ravita Roderick, Paul Alwan, Nisreen A. PLoS One Research Article BACKGROUND: In England, the responsibility to address food insecurity lies with local government, yet the prevalence of this social inequality is unknown in small subnational areas. In 2018 an index of small-area household food insecurity risk was developed and utilised by public and third sector organisations to target interventions; this measure needed updating to better support decisions in different settings, such as urban and rural areas where pressures on food security differ. METHODS: We held interviews with stakeholders (n = 14) and completed a scoping review to identify appropriate variables to create an updated risk measure. We then sourced a range of open access secondary data to develop an indices of food insecurity risk in English neighbourhoods. Following a process of data transformation and normalisation, we tested combinations of variables and identified the most appropriate data to reflect household food insecurity risk in urban and rural areas. RESULTS: Eight variables, reflecting both household circumstances and local service availability, were separated into two domains with equal weighting for a new index, the Complex Index, and a subset of these to make up the Simple Index. Within the Complex Index, the Compositional Domain includes population characteristics while the Structural Domain reflects small area access to resources such as grocery stores. The Compositional Domain correlated well with free school meal eligibility (r(s) = 0.705) and prevalence of childhood obesity (r(s) = 0.641). This domain was the preferred measure for use in most areas when shared with stakeholders, and when assessed alongside other configurations of the variables. Areas of highest risk were most often located in the North of England. CONCLUSION: We recommend the use of the Compositional Domain for all areas, with inclusion of the Structural Domain in rural areas where locational disadvantage makes it more difficult to access resources. These measures can aid local policy makers and planners when allocating resources and interventions to support households who may experience food insecurity. Public Library of Science 2022-12-09 /pmc/articles/PMC9733884/ /pubmed/36490256 http://dx.doi.org/10.1371/journal.pone.0267260 Text en © 2022 Smith et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Smith, Dianna M. Rixson, Lauren Grove, Grace Ziauddeen, Nida Vassilev, Ivaylo Taheem, Ravita Roderick, Paul Alwan, Nisreen A. Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title | Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title_full | Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title_fullStr | Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title_full_unstemmed | Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title_short | Household food insecurity risk indices for English neighbourhoods: Measures to support local policy decisions |
title_sort | household food insecurity risk indices for english neighbourhoods: measures to support local policy decisions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733884/ https://www.ncbi.nlm.nih.gov/pubmed/36490256 http://dx.doi.org/10.1371/journal.pone.0267260 |
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