Evidence map›Paper›PMID 37345222›Full record

ArticleEuropean journal of pain (London, England)2023

Where does it hurt? Small area estimates and inequality in the prevalence of chronic pain.

Marty Lynch, George Peat, Kelvin Jordan, Dahai Yu, Ross Wilkie

Abstract read
In one paragraph

Article in European journal of pain (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Who Gets Referred for What? Large Scale Analysis of Clinical, Socioeconomic and Demographic Drivers Within Electronic Optometry Referrals.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marty LynchSchool of Medicine, Keele University, Keele, UK.ORCID 0000-0003-4882-6875
George PeatSchool of Medicine, Keele University, Keele, UK.ORCID 0000-0002-9008-0184
Kelvin JordanSchool of Medicine, Keele University, Keele, UK.ORCID 0000-0003-4748-5335
Dahai YuSchool of Medicine, Keele University, Keele, UK.ORCID 0000-0002-8449-7725
Ross WilkieSchool of Medicine, Keele University, Keele, UK.ORCID 0000-0003-4825-714X

Funding

NIHR Applied Research CollaborationNuffield Foundation and Versus Arthritis for the MIDAS Project OBF/43390Versus Arthritis for the PRELIM Survey 21403
6 · The paper itself

Abstract

backgroundChronic pain affects up to half of UK adults, impacting quality of life and demand on local health services. Whilst local health planning is currently based on subnational prevalence estimates, associations between pain and sociodemographic characteristics suggest that inequalities in the prevalence of chronic and high-impact chronic pain between neighbourhoods within local authorities are likely. We aimed to derive lower super output area (LSOA) estimates of the prevalence of chronic and high-impact chronic pain.

methodsPresence of self-reported chronic and high-impact chronic pain were measured in adults aged 35+ in North Staffordshire and modelled using multilevel regression as a function of demographic and geographic predictors. Multilevel model predictions were post-stratified using the North Staffordshire age-sex population structure and LSOA demographic characteristics to estimate the prevalence of chronic and high-impact chronic pain in 298 LSOAs, corrected for ethnic diversity underrepresented in the data. Confidence intervals were generated for high-impact chronic pain using bootstrapping.

resultsData were analysed from 4162 survey respondents (2358 women, 1804 men). The estimated prevalence of chronic and high-impact chronic pain in North Staffordshire LSOAs ranged from 18.6% to 50.1% and 6.18 [1.71, 16.0]% to 33.09 [13.3, 44.7]%, respectively.

conclusionsPrevalence of chronic and high-impact chronic pain in adults aged 35+ varies substantially between neighbourhoods within local authorities. Further insight into small-area level variation will help target resources to improve the management and prevention of chronic and high-impact chronic pain to reduce the impact on individuals, communities, workplaces, services and the economy. SIGNIFICANCE: Post-stratified multilevel model predictions can produce small-area estimates of pain prevalence and impact. The evidence of substantial variation indicates a need to collect local-level data on pain and its impact to understand health needs and to guide interventions.

Indexed as

Chronic PainAdultFemaleHumansMalePrevalenceQuality of LifeSelf ReportSurveys and QuestionnairesUnited States

Identifiers

PMID37345222
PMCPMC10947147

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.