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Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?

BACKGROUND: Emergency diagnosis of cancer is associated with poorer short-term survival and may reflect delayed help-seeking. Optimal targeting of interventions to raise awareness of cancer symptoms is therefore needed. METHODS: We examined the risk of emergency presentation of lung and colorectal c...

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Autores principales: Bright, C J, Gildea, C, Lai, J, Elliss-Brookes, L, Lyratzopoulos, G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677448/
https://www.ncbi.nlm.nih.gov/pubmed/32785586
http://dx.doi.org/10.1093/pubmed/fdaa111
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author Bright, C J
Gildea, C
Lai, J
Elliss-Brookes, L
Lyratzopoulos, G
author_facet Bright, C J
Gildea, C
Lai, J
Elliss-Brookes, L
Lyratzopoulos, G
author_sort Bright, C J
collection PubMed
description BACKGROUND: Emergency diagnosis of cancer is associated with poorer short-term survival and may reflect delayed help-seeking. Optimal targeting of interventions to raise awareness of cancer symptoms is therefore needed. METHODS: We examined the risk of emergency presentation of lung and colorectal cancer (diagnosed in 2016 in England). By cancer site, we used logistic regression (outcome emergency/non-emergency presentation) adjusting for patient-level variables (age, sex, deprivation and ethnicity) with/without adjustment for geodemographic segmentation (Mosaic) group. RESULTS: Analysis included 36 194 and 32 984 patients with lung and colorectal cancer. Greater levels of deprivation were strongly associated with greater odds of emergency presentation, even after adjustment for Mosaic group, which nonetheless attenuated associations (odds ratio [OR] most/least deprived group = 1.67 adjusted [model excluding Mosaic], 1.28 adjusted [model including Mosaic], P < 0.001 for both, for colorectal; respective OR values of 1.42 and 1.18 for lung, P < 0.001 for both). Similar findings were observed for increasing age. There was large variation in risk of emergency presentation between Mosaic groups (crude OR for highest/lowest risk group = 2.30, adjusted OR = 1.89, for colorectal; respective values of 1.59 and1.66 for lung). CONCLUSION: Variation in risk of emergency presentation in cancer patients can be explained by geodemography, additional to deprivation group and age. The findings support proof of concept for public health interventions targeting all the examined attributes, including geodemography.
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spelling pubmed-86774482021-12-17 Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables? Bright, C J Gildea, C Lai, J Elliss-Brookes, L Lyratzopoulos, G J Public Health (Oxf) Original Article BACKGROUND: Emergency diagnosis of cancer is associated with poorer short-term survival and may reflect delayed help-seeking. Optimal targeting of interventions to raise awareness of cancer symptoms is therefore needed. METHODS: We examined the risk of emergency presentation of lung and colorectal cancer (diagnosed in 2016 in England). By cancer site, we used logistic regression (outcome emergency/non-emergency presentation) adjusting for patient-level variables (age, sex, deprivation and ethnicity) with/without adjustment for geodemographic segmentation (Mosaic) group. RESULTS: Analysis included 36 194 and 32 984 patients with lung and colorectal cancer. Greater levels of deprivation were strongly associated with greater odds of emergency presentation, even after adjustment for Mosaic group, which nonetheless attenuated associations (odds ratio [OR] most/least deprived group = 1.67 adjusted [model excluding Mosaic], 1.28 adjusted [model including Mosaic], P < 0.001 for both, for colorectal; respective OR values of 1.42 and 1.18 for lung, P < 0.001 for both). Similar findings were observed for increasing age. There was large variation in risk of emergency presentation between Mosaic groups (crude OR for highest/lowest risk group = 2.30, adjusted OR = 1.89, for colorectal; respective values of 1.59 and1.66 for lung). CONCLUSION: Variation in risk of emergency presentation in cancer patients can be explained by geodemography, additional to deprivation group and age. The findings support proof of concept for public health interventions targeting all the examined attributes, including geodemography. Oxford University Press 2020-08-12 /pmc/articles/PMC8677448/ /pubmed/32785586 http://dx.doi.org/10.1093/pubmed/fdaa111 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Bright, C J
Gildea, C
Lai, J
Elliss-Brookes, L
Lyratzopoulos, G
Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title_full Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title_fullStr Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title_full_unstemmed Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title_short Does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
title_sort does geodemographic segmentation explain differences in route of cancer diagnosis above and beyond person-level sociodemographic variables?
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677448/
https://www.ncbi.nlm.nih.gov/pubmed/32785586
http://dx.doi.org/10.1093/pubmed/fdaa111
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