Evidence map›Paper›PMID 40646315›Full record

ArticleJournal of public health policy2025

Assessing hearing health inequalities using routine health information systems.

Dialechti Tsimpida, Roberta Piroddi, Konstantinos Daras, Gabriella Melis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of public health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Dialechti TsimpidaCentre for Research On Ageing, University of Southampton, Murray Building (58), Highfield Campus, Southampton, SO17 1BJ, UK. d.tsimpida@soton.ac.uk.ORCID http://orcid.org/0000-0002-3709-5651
Roberta PiroddiDepartment of Health Data Science, University of Liverpool, Liverpool, UK.
Konstantinos DarasDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Gabriella MelisNational Disease Registration Service (NDRS), NHS England, UK.

Funding

National Institute for Health and Care Research MHF106National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care North West Coast NIHR200182Research England 177946
6 · The paper itself

Abstract

Hearing loss is a significant public health challenge, with prevalence estimates based on projected age demographics rather than actual public health needs. This study aimed to quantify hearing loss using real-world data from primary care and explore local patterns and trends from 2013 to 2022 in Cheshire and Merseyside counties of Northwest England. Annual hearing loss prevalence was measured using an ecological space-time analysis of 2.7 million primary care records from Cheshire and Merseyside Integrated Care System. We applied cluster and outlier analysis with geographically weighted regression to examine local deprivation effects. We detected spatial clusters of high prevalence of hearing loss in Cheshire and an increasing trend in hearing loss prevalence in Halton. Deprivation accounted for up to 35% of hearing loss variance in 2020. Monitoring spatial patterns of hearing loss is crucial for addressing health inequalities and guiding targeted prevention and intervention strategies.

Indexed as

Health Information SystemsHealth Status DisparitiesHearing LossAdolescentAdultAgedChildEnglandFemaleHumansMaleMiddle AgedPrevalencePrimary Health CareSocioeconomic FactorsYoung AdultHealth policyHearing healthInequalitiesPublic healthSpatial statistics

Identifiers

PMID40646315
PMCPMC12328234

What OpenQuestion holds

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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.