Evidence map›Paper›PMID 32888980›Full record

ArticleThe Journal of infection2020

Neighbourhood unemployment and other socio-demographic predictors of emergency hospitalisation for infectious intestinal disease in England: A longitudinal ecological study.

Tanith C Rose, Natalie L Adams, Margaret Whitehead, Sophie Wickham, Sarah J O'Brien, Jeremy Hawker, David C Taylor-Robinson, Mara Violato, Benjamin Barr

Open access · hybridAbstract read
In one paragraph

Article in The Journal of infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Tanith C RoseDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK. Electronic address: Tanith.Rose@liverpool.ac.uk.
Natalie L AdamsDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK.
Margaret WhiteheadDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK.
Sophie WickhamDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK.
Sarah J O'BrienSchool of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK.
Jeremy HawkerNational Infection Service, Public Health England, Birmingham, UK.
David C Taylor-RobinsonDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK.
Mara ViolatoHealth Economics Research Centre, University of Oxford, Oxford, UK.
Benjamin BarrDepartment of Public Health, Policy and Systems, University of Liverpool, Waterhouse Building 2nd Floor Block F, Liverpool, UK.
University of Liverpool · GBNewcastle University · GBPublic Health England · GBUniversity of Oxford · GB

Funding

Department of Health NIHR130258Medical Research Council G0802448Medical Research Council MC_U122785837Medical Research Council MR/P008577/1Wellcome Trust 200,335/Z/15/Z
6 · The paper itself

Abstract

backgroundPrevious studies have observed that infectious intestinal disease (IID) related hospital admissions are higher in more deprived neighbourhoods. These studies have mainly focused on paediatric populations and are cross-sectional in nature. This study examines recent trends in emergency IID admission rates, and uses longitudinal methods to investigate the effects of unemployment (as a time varying measure of neighbourhood deprivation) and other socio-demographic characteristics on IID admissions for adults and children in England.

methodsA longitudinal ecological analysis was performed using Hospital Episode Statistics on emergency hospitalisations for IID, collected over the time period 2012-17 across England. Analysis was conducted at the neighbourhood (Lower-layer Super Output Area) level for three age groups (0-14; 15-64; 65+ years). Mixed-effect Poisson regression models were used to assess the relationship between trends in neighbourhood unemployment and emergency IID admission rates, whilst controlling for measures of primary and secondary care access, underlying morbidity and the ethnic composition of each neighbourhood.

resultsFrom 2012-17, declining trends in emergency IID admission rates were observed for children and older adults overall, while rates increased for some sub-groups in the population. Each 1 percentage point increase in unemployment was associated with a 6.3, 2.4 and 4% increase in the rate of IID admissions per year for children [IRR=1.06, 95%CI 1.06-1.07], adults [IRR=1.02, 95%CI 1.02-1.03] and older adults [IRR=1.04, 95%CI 1.036-1.043], respectively. Increases in poor primary care access, the percentage of people from a Pakistani ethnic background, and the prevalence of long-term health problems, in a neighbourhood, were also associated with increases in IID admission rates.

conclusionsIncreasing trends in neighbourhood deprivation, as measured by unemployment, were associated with increases in emergency IID admission rates for children and adults in England, despite controlling for measures of healthcare access, underlying morbidity and ethnicity. Research is needed to improve understanding of the mechanisms that explain these inequalities, so that effective policies can be developed to reduce the higher emergency IID admission rates experienced by more disadvantaged communities.

Indexed as

Intestinal DiseasesUnemploymentAgedChildCross-Sectional StudiesEnglandHospitalizationHumansDiarrhoeaEmploymentSocial classSocioeconomic factors

Identifiers

PMID32888980
PMCPMC7649336
OpenAlexW3082900757

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.