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What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England
OBJECTIVES: The aim of this study was to identify the most important determinants of accident and emergency (A&E) attendance in disadvantaged areas. DESIGN, SETTING AND PARTICIPANTS: A total of 3510 residents from 20 disadvantaged neighbourhoods in the North West Coast area in England completed...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326270/ https://www.ncbi.nlm.nih.gov/pubmed/30613026 http://dx.doi.org/10.1136/bmjopen-2018-022820 |
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author | Giebel, Clarissa McIntyre, Jason Cameron Daras, Konstantinos Gabbay, Mark Downing, Jennifer Pirmohamed, Munir Walker, Fran Sawicki, Wojciech Alfirevic, Ana Barr, Ben |
author_facet | Giebel, Clarissa McIntyre, Jason Cameron Daras, Konstantinos Gabbay, Mark Downing, Jennifer Pirmohamed, Munir Walker, Fran Sawicki, Wojciech Alfirevic, Ana Barr, Ben |
author_sort | Giebel, Clarissa |
collection | PubMed |
description | OBJECTIVES: The aim of this study was to identify the most important determinants of accident and emergency (A&E) attendance in disadvantaged areas. DESIGN, SETTING AND PARTICIPANTS: A total of 3510 residents from 20 disadvantaged neighbourhoods in the North West Coast area in England completed a comprehensive public health survey. MAIN OUTCOME MEASURES: Participants were asked to complete general background information, as well as information about their physical health, mental health, lifestyle, social issues, housing and environment, work and finances, and healthcare service usage. Only one resident per household could take part in the survey. Poisson regression analysis was employed to assess the predictors of A&E attendance frequency in the previous 12 months. RESULTS: 31.6% of the sample reported having attended A&E in the previous 12 months, ranging from 1 to 95 visits. Controlling for demographic and health factors, not being in employment and living in poor quality housing increased the likelihood of attending an A&E service. Service access was also found to be predictive of A&E attendance insofar as there were an additional 18 fewer A&E attendances per 100 population for each kilometre closer a person lived to a general practitioner (GP) practice, and 3 fewer attendances per 100 population for each kilometre further a person lived from an A&E department. CONCLUSIONS: This is one of the first surveys to explore a comprehensive set of socio-economic factors as well as proximity to both GP and A&E services as predictors of A&E attendance in disadvantaged areas. Findings from this study suggest the need to address both socioeconomic issues, such as employment and housing quality, as well as structural issues, such as public transport and access to primary care, to reduce the current burden on A&E departments. |
format | Online Article Text |
id | pubmed-6326270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-63262702019-01-25 What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England Giebel, Clarissa McIntyre, Jason Cameron Daras, Konstantinos Gabbay, Mark Downing, Jennifer Pirmohamed, Munir Walker, Fran Sawicki, Wojciech Alfirevic, Ana Barr, Ben BMJ Open Public Health OBJECTIVES: The aim of this study was to identify the most important determinants of accident and emergency (A&E) attendance in disadvantaged areas. DESIGN, SETTING AND PARTICIPANTS: A total of 3510 residents from 20 disadvantaged neighbourhoods in the North West Coast area in England completed a comprehensive public health survey. MAIN OUTCOME MEASURES: Participants were asked to complete general background information, as well as information about their physical health, mental health, lifestyle, social issues, housing and environment, work and finances, and healthcare service usage. Only one resident per household could take part in the survey. Poisson regression analysis was employed to assess the predictors of A&E attendance frequency in the previous 12 months. RESULTS: 31.6% of the sample reported having attended A&E in the previous 12 months, ranging from 1 to 95 visits. Controlling for demographic and health factors, not being in employment and living in poor quality housing increased the likelihood of attending an A&E service. Service access was also found to be predictive of A&E attendance insofar as there were an additional 18 fewer A&E attendances per 100 population for each kilometre closer a person lived to a general practitioner (GP) practice, and 3 fewer attendances per 100 population for each kilometre further a person lived from an A&E department. CONCLUSIONS: This is one of the first surveys to explore a comprehensive set of socio-economic factors as well as proximity to both GP and A&E services as predictors of A&E attendance in disadvantaged areas. Findings from this study suggest the need to address both socioeconomic issues, such as employment and housing quality, as well as structural issues, such as public transport and access to primary care, to reduce the current burden on A&E departments. BMJ Publishing Group 2019-01-06 /pmc/articles/PMC6326270/ /pubmed/30613026 http://dx.doi.org/10.1136/bmjopen-2018-022820 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Public Health Giebel, Clarissa McIntyre, Jason Cameron Daras, Konstantinos Gabbay, Mark Downing, Jennifer Pirmohamed, Munir Walker, Fran Sawicki, Wojciech Alfirevic, Ana Barr, Ben What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title | What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title_full | What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title_fullStr | What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title_full_unstemmed | What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title_short | What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England |
title_sort | what are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? results from a cross-sectional household health survey in the north west of england |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326270/ https://www.ncbi.nlm.nih.gov/pubmed/30613026 http://dx.doi.org/10.1136/bmjopen-2018-022820 |
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