Urban–rural and socioeconomic status: Impact on multimorbidity prevalence in hospitalized patients

Lynn Robertson; Dolapo Ayansina; Marjorie Johnston; Angharad Marks; Corri Black

doi:10.1177/2235042X19893470

Urban–rural and socioeconomic status: Impact on multimorbidity prevalence in hospitalized patients

Lynn Robertson^* (Corresponding Author), Dolapo Ayansina, Marjorie Johnston, Angharad Marks, Corri Black

^*Corresponding author for this work

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Abstract

Objective:The aim of this study was to describe multimorbidity prevalence in hospitalized adults, by urban?rural area of residence and socioeconomic status (SES).Methods:Linked hospital episode data were used. Adults (≥18 years) admitted to hospital as an inpatient during 2014 in Grampian, Scotland, were included. Conditions were identified from admissions during the 5 years prior to the first admission in 2014. Multimorbidity was defined as ≥2 conditions and measured using Tonelli et al. based on International Classification of Diseases-10 coding (preselected list of 30 conditions). We used proportions and 95% confidence intervals (CIs) to summarize the prevalence of multimorbidity by age group, sex, urban?rural category and deprivation. The association between multimorbidity and patient characteristics was assessed using the ? 2 test.Results:Forty one thousand five hundred and forty-five patients were included (median age 62, 52.6% female). Overall, 27.4% (95% CI 27.0, 27.8) of patients were multimorbid. Multimorbidity prevalence was 28.8% (95% CI 28.1, 29.5) in large urban versus 22.0% (95% CI 20.9, 23.3) in remote rural areas and 28.7% (95% CI 27.2, 30.3) in the most deprived versus 26.0% (95% CI 25.2, 26.9) in the least deprived areas. This effect was consistent in all age groups, but not statistically significant in the age group 18?29 years. Multimorbidity increased with age but was similar for males and females.Conclusion:Given the scarcity of research into the effect of urban?rural area and SES on multimorbidity prevalence among hospitalized patients, these findings should inform future research into new models of care, including the consideration of urban?rural area and SES.

Original language	English
Pages (from-to)	1-11
Number of pages	11
Journal	Journal of Comorbidity
Volume	10
Early online date	20 Apr 2020
DOIs	https://doi.org/10.1177/2235042X19893470
Publication status	Published - 2020

Bibliographical note

The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: This
work was funded by NHS Grampian, Public Health Directorate.
This work was also supported by Health Data Research UK which
receives its funding from HDR UK Ltd (HDR-5012) funded by
the UK Medical Research Council, Engineering and Physical
Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care
Directorates, Health and Social Care Research and Development
Division (Welsh Government), Public Health Agency (Northern
Ireland), British Heart Foundation (BHF) and the Wellcome
Trust.

Data accessibility statement
De-identified data used for this study are held by Grampian Data
Safe Haven. These data are available provided the necessary permissions have been obtained. Further information is available at
http://www.abdn.ac.uk/iahs/facilities/grampian-data-safe-haven.
php and requests for data may be made to Professor Corri Black
on behalf of Grampian Data Safe Haven, corri.black@abdn.ac.uk.

Keywords

hospitalization
multimorbidity
prevalance
socioeconomic status
urban–rural
electronic health records

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Cite this

@article{7757ef96c1f94cafa49318ba14d62cc1,

title = "Urban–rural and socioeconomic status: Impact on multimorbidity prevalence in hospitalized patients",

abstract = "Objective:The aim of this study was to describe multimorbidity prevalence in hospitalized adults, by urban?rural area of residence and socioeconomic status (SES).Methods:Linked hospital episode data were used. Adults (≥18 years) admitted to hospital as an inpatient during 2014 in Grampian, Scotland, were included. Conditions were identified from admissions during the 5 years prior to the first admission in 2014. Multimorbidity was defined as ≥2 conditions and measured using Tonelli et al. based on International Classification of Diseases-10 coding (preselected list of 30 conditions). We used proportions and 95% confidence intervals (CIs) to summarize the prevalence of multimorbidity by age group, sex, urban?rural category and deprivation. The association between multimorbidity and patient characteristics was assessed using the ? 2 test.Results:Forty one thousand five hundred and forty-five patients were included (median age 62, 52.6% female). Overall, 27.4% (95% CI 27.0, 27.8) of patients were multimorbid. Multimorbidity prevalence was 28.8% (95% CI 28.1, 29.5) in large urban versus 22.0% (95% CI 20.9, 23.3) in remote rural areas and 28.7% (95% CI 27.2, 30.3) in the most deprived versus 26.0% (95% CI 25.2, 26.9) in the least deprived areas. This effect was consistent in all age groups, but not statistically significant in the age group 18?29 years. Multimorbidity increased with age but was similar for males and females.Conclusion:Given the scarcity of research into the effect of urban?rural area and SES on multimorbidity prevalence among hospitalized patients, these findings should inform future research into new models of care, including the consideration of urban?rural area and SES.",

keywords = "hospitalization, multimorbidity, prevalance, socioeconomic status, urban–rural, electronic health records",

author = "Lynn Robertson and Dolapo Ayansina and Marjorie Johnston and Angharad Marks and Corri Black",

note = "The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by NHS Grampian, Public Health Directorate. This work was also supported by Health Data Research UK which receives its funding from HDR UK Ltd (HDR-5012) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. Data accessibility statement De-identified data used for this study are held by Grampian Data Safe Haven. These data are available provided the necessary permissions have been obtained. Further information is available at http://www.abdn.ac.uk/iahs/facilities/grampian-data-safe-haven. php and requests for data may be made to Professor Corri Black on behalf of Grampian Data Safe Haven, corri.black@abdn.ac.uk.",

year = "2020",

doi = "10.1177/2235042X19893470",

language = "English",

volume = "10",

pages = "1--11",

journal = "Journal of Comorbidity",

}

TY - JOUR

T1 - Urban–rural and socioeconomic status

T2 - Impact on multimorbidity prevalence in hospitalized patients

AU - Robertson, Lynn

AU - Ayansina, Dolapo

AU - Johnston, Marjorie

AU - Marks, Angharad

AU - Black, Corri

N1 - The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by NHS Grampian, Public Health Directorate. This work was also supported by Health Data Research UK which receives its funding from HDR UK Ltd (HDR-5012) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. Data accessibility statement De-identified data used for this study are held by Grampian Data Safe Haven. These data are available provided the necessary permissions have been obtained. Further information is available at http://www.abdn.ac.uk/iahs/facilities/grampian-data-safe-haven. php and requests for data may be made to Professor Corri Black on behalf of Grampian Data Safe Haven, corri.black@abdn.ac.uk.

PY - 2020

Y1 - 2020

N2 - Objective:The aim of this study was to describe multimorbidity prevalence in hospitalized adults, by urban?rural area of residence and socioeconomic status (SES).Methods:Linked hospital episode data were used. Adults (≥18 years) admitted to hospital as an inpatient during 2014 in Grampian, Scotland, were included. Conditions were identified from admissions during the 5 years prior to the first admission in 2014. Multimorbidity was defined as ≥2 conditions and measured using Tonelli et al. based on International Classification of Diseases-10 coding (preselected list of 30 conditions). We used proportions and 95% confidence intervals (CIs) to summarize the prevalence of multimorbidity by age group, sex, urban?rural category and deprivation. The association between multimorbidity and patient characteristics was assessed using the ? 2 test.Results:Forty one thousand five hundred and forty-five patients were included (median age 62, 52.6% female). Overall, 27.4% (95% CI 27.0, 27.8) of patients were multimorbid. Multimorbidity prevalence was 28.8% (95% CI 28.1, 29.5) in large urban versus 22.0% (95% CI 20.9, 23.3) in remote rural areas and 28.7% (95% CI 27.2, 30.3) in the most deprived versus 26.0% (95% CI 25.2, 26.9) in the least deprived areas. This effect was consistent in all age groups, but not statistically significant in the age group 18?29 years. Multimorbidity increased with age but was similar for males and females.Conclusion:Given the scarcity of research into the effect of urban?rural area and SES on multimorbidity prevalence among hospitalized patients, these findings should inform future research into new models of care, including the consideration of urban?rural area and SES.

AB - Objective:The aim of this study was to describe multimorbidity prevalence in hospitalized adults, by urban?rural area of residence and socioeconomic status (SES).Methods:Linked hospital episode data were used. Adults (≥18 years) admitted to hospital as an inpatient during 2014 in Grampian, Scotland, were included. Conditions were identified from admissions during the 5 years prior to the first admission in 2014. Multimorbidity was defined as ≥2 conditions and measured using Tonelli et al. based on International Classification of Diseases-10 coding (preselected list of 30 conditions). We used proportions and 95% confidence intervals (CIs) to summarize the prevalence of multimorbidity by age group, sex, urban?rural category and deprivation. The association between multimorbidity and patient characteristics was assessed using the ? 2 test.Results:Forty one thousand five hundred and forty-five patients were included (median age 62, 52.6% female). Overall, 27.4% (95% CI 27.0, 27.8) of patients were multimorbid. Multimorbidity prevalence was 28.8% (95% CI 28.1, 29.5) in large urban versus 22.0% (95% CI 20.9, 23.3) in remote rural areas and 28.7% (95% CI 27.2, 30.3) in the most deprived versus 26.0% (95% CI 25.2, 26.9) in the least deprived areas. This effect was consistent in all age groups, but not statistically significant in the age group 18?29 years. Multimorbidity increased with age but was similar for males and females.Conclusion:Given the scarcity of research into the effect of urban?rural area and SES on multimorbidity prevalence among hospitalized patients, these findings should inform future research into new models of care, including the consideration of urban?rural area and SES.

KW - hospitalization

KW - multimorbidity

KW - prevalance

KW - socioeconomic status

KW - urban–rural

KW - electronic health records

U2 - 10.1177/2235042X19893470

DO - 10.1177/2235042X19893470

M3 - Article

C2 - 32341912

VL - 10

SP - 1

EP - 11

JO - Journal of Comorbidity

JF - Journal of Comorbidity

ER -

Urban–rural and socioeconomic status: Impact on multimorbidity prevalence in hospitalized patients

Abstract

Bibliographical note

Keywords

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