Evidence map›Paper›PMID 42559038›Full record

ArticlePublic health challenges2026

Gendered Patterns of Engagement With NHS Health Checks in a Super-Diverse City: Community Perspectives and Implications for Equity.

Muhammad Hossain

Abstract read
In one paragraph

Article in Public health challenges, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Muhammad HossainPublic Health, Department of Life and Sports Sciences, School of Life and Health Sciences Birmingham City University City South Campus Birmingham UK.ORCID https://orcid.org/0000-0002-4939-1597

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: NHS Health Checks are a national preventive programme in England designed to reduce cardiovascular disease and related long-term conditions, yet uptake remains uneven. Gender differences persist, with men, particularly from racially marginalised and socioeconomically deprived communities, engaging less with preventive services, potentially reinforcing health inequalities. Methods: A qualitative community-based participatory study was conducted in Birmingham using focus groups across 10 community organisations, alongside discussions with NHS Health Check professionals. Data were analysed using framework analysis, with attention to gendered and intersectional influences on engagement. Results: Women generally reported higher participation than men, although patterns varied across communities. Men's lower engagement was commonly attributed to inflexible employment, perceived low relevance of preventive care and limited trust in services. Women's engagement was shaped by childcare responsibilities, gender concordance of staff and cultural acceptability. Across genders, participants highlighted communication gaps, limited follow-up and structural barriers within service delivery. Conclusion: Gendered inequalities in NHS Health Check engagement reflect intersecting social, cultural and systemic factors. Addressing these requires gender-responsive, culturally competent delivery models, flexible access arrangements and strengthened community partnerships to promote equitable uptake of preventive care. These findings inform policy, commissioning and practice aimed at reducing gendered inequalities in prevention services.

Indexed as

community engagementethnic minority communitiesgender differenceshealth inequalitiesNHS Health Checkspreventive healthcare

Identifiers

PMID42559038
PMCPMC13439508

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.