Authors
Summary
To address the scarcity of small-area datasets focused on economic inclusion, we created a harmonised dataset describing the extent and enablers of economic inclusion in Great Britain. The result, the SIPHER (Systems Science in Public Health and Health Economics Research) Inclusive Economy (Ward Level) dataset, consists of 13 indicators describing economic inclusion at electoral ward level (N = 7,973 of 8,020 wards, 2022 boundaries), for 2019–2021. The dataset was curated based on administrative statistics (mostly open-source) and the SIPHER Synthetic Population, a validated, survey-based, full-scale synthetic population dataset derived from the UK Household Longitudinal Study (UKHLS): Understanding Society, and aggregate-level population statistics. The dataset also includes summary measures of population health – age-standardised Short Form Health Survey (SF-12) mental and physical health component scores – and supplementary demographic indicators describing the population structure. For validation, a range of comparisons against deprivation indices and other data provide strong evidence of the dataset’s added value and utility for applications in research and policy requiring high-quality estimates at a granular spatial resolution.
Volume
Volume: 12:1230
Subjects
Notes
Code: All code used and data generated or analysed during this study are available via a data repository - Rice, H. P., Lomax, N. & Hoehn, A. SIPHER Inclusive Economy (Ward Level). Open Science Framework https://doi.org/10.17605/OSF.IO/S24YE (2024), including a user guide on how to use the dataset and create some visualisations of it using the Python notebook provided.
Open Access
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.