What does ethnic density represent? Spatial co-occurrence networks of a widely used contextual measure using harmonised UK small-area census data
Abstract
Ethnic density is widely used in epidemiology and health geography as a contextual exposure, yet it is rarely examined as a measurement problem in its own right. Equivalent percentage values may represent different neighbourhood contexts across groups and places, particularly where migration, religion, language, household structure and socioeconomic conditions are spatially co-located. Using the harmonised Unified UK Census Data release, I analysed 239,023 small-area census data to examine ethnic density as an exploratory contextual co-occurrence construct. I estimated UK-wide mixed graphical models (MGM) for eight ethnic-density targets using 239,019 complete cases and 32 nodes per target-specific model. England-only spatial analyses then used k-nearest-neighbour Output Area centroids (k = 8) to estimate LISA and spatially adjusted residual networks. Ethnic density did not behave as a single contextual scalar. In the UK-wide MGM, the strongest retained target-neighbour edges differed across groups. Asian density was linked most strongly with Middle East/Asia-born share (0.59), Indian density with Hindu share (0.55), Pakistani density with Muslim share (0.47), Bangladeshi density with Muslim share (0.23), Black density with Africa-born share (0.42), and White density with Middle East/Asia-born share (0.35). England-only ethnic-density measures were strongly spatially autocorrelated, with Global Moran's I ranging from 0.57 for Mixed share to 0.90 for White share. After residualising against English region and local spatial lag, 64.3% to 96.4% of original target-node edges persisted across ethnic-density networks. Equivalent percentage values are not necessarily comparable across ethnic groups. This has implications for estimand definition, adjustment strategies, and the interpretation of ethnic density and other bundled contextual measures in urban health research.
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BibTeX
@misc{lam2026what,
title = {{What does ethnic density represent? Spatial co-occurrence networks of a widely used contextual measure using harmonised UK small-area census data}},
author = {Joseph Lam},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2606.19087},
eprint = {2606.19087},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2606.19087},
note = {CC BY-SA 4.0},
}
RIS
TY - UNPB
TI - What does ethnic density represent? Spatial co-occurrence networks of a widely used contextual measure using harmonised UK small-area census data
AU - Joseph Lam
PY - 2026
DA - 2026/08/27
PB - arXiv
DO - 10.48550/arxiv.2606.19087
UR - https://arxiv.org/abs/2606.19087
AB - Ethnic density is widely used in epidemiology and health geography as a contextual exposure, yet it is rarely examined as a measurement problem in its own right. Equivalent percentage values may represent different neighbourhood contexts across groups and places, particularly where migration, religion, language, household structure and socioeconomic conditions are spatially co-located. Using the harmonised Unified UK Census Data release, I analysed 239,023 small-area census data to examine ethnic density as an exploratory contextual co-occurrence construct. I estimated UK-wide mixed graphical models (MGM) for eight ethnic-density targets using 239,019 complete cases and 32 nodes per target-specific model. England-only spatial analyses then used k-nearest-neighbour Output Area centroids (k = 8) to estimate LISA and spatially adjusted residual networks. Ethnic density did not behave as a single contextual scalar. In the UK-wide MGM, the strongest retained target-neighbour edges differed across groups. Asian density was linked most strongly with Middle East/Asia-born share (0.59), Indian density with Hindu share (0.55), Pakistani density with Muslim share (0.47), Bangladeshi density with Muslim share (0.23), Black density with Africa-born share (0.42), and White density with Middle East/Asia-born share (0.35). England-only ethnic-density measures were strongly spatially autocorrelated, with Global Moran's I ranging from 0.57 for Mixed share to 0.90 for White share. After residualising against English region and local spatial lag, 64.3% to 96.4% of original target-node edges persisted across ethnic-density networks. Equivalent percentage values are not necessarily comparable across ethnic groups. This has implications for estimand definition, adjustment strategies, and the interpretation of ethnic density and other bundled contextual measures in urban health research.
ER -