Evidence map›Paper›PMID 42707877›Full record

ArticleBMJ public health2026

Socioeconomic predictors of diabetic foot ulcers: a systematic review and meta-analysis.

Annel Sinkala, Eustarckio Kazonga, Monde Watae, Julius Mwanza, Richard Mutemwa, Esnart Nguni, John Phiri

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

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Annel SinkalaInternal Medicine, Levy Mwanawasa University Teaching Hospital, Lusaka, Zambia.ORCID https://orcid.org/0009-0003-4463-5614
Eustarckio KazongaSchool of Postgraduate Studies, University of Lusaka, Lusaka, Zambia.
Monde WataeSchool of Postgraduate Studies, University of Lusaka, Lusaka, Zambia.
Julius MwanzaPostgraduate Studies, University of Lusaka, Lusaka, Zambia.
Richard MutemwaSchool of Postgraduate Studies, University of Lusaka, Lusaka, Zambia.
Esnart NguniSchool of Postgraduate Studies, University of Lusaka, Lusaka, Zambia.
John PhiriSchool of Postgraduate Studies, University of Lusaka, Lusaka, Zambia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To evaluate the association between socioeconomic factors and diabetic foot ulcers (DFUs) among adults with diabetes mellitus through systematic review and meta-analysis. Design: Systematic review and meta-analysis of observational studies conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Data sources: PubMed/MEDLINE, Scopus, CINAHL and Google Scholar were systematically searched from database inception to 31 December 2024, with a final updated search performed in February 2025. Eligibility criteria: Cross-sectional and case-control studies evaluating the association between socioeconomic factors and DFUs among adults with diabetes mellitus were included. Data extraction and synthesis: Study selection and data extraction were performed independently by two reviewers. Methodological quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for cross-sectional studies and the Newcastle-Ottawa Scale for case-control studies. Random-effects meta-analysis was used to pool ORs and corresponding 95% CIs. Heterogeneity was assessed using the I² statistic. Results: Eight cross-sectional and case-control studies involving 3488 participants were included. Lower educational attainment was significantly associated with higher odds of DFUs (pooled OR=2.54, 95% CI 1.24 to 5.20; I² = 68.0%). Similarly, lack of formal employment was associated with higher odds of DFUs (pooled OR=1.71, 95% CI 1.05 to 2.77; I² = 21.2%). In contrast, although low income showed increased pooled odds of DFUs, the association did not reach statistical significance under the random-effects model (pooled OR=2.70, 95% CI 0.36 to 20.41; I² = 81.9%). Interpretation of the income analysis was limited by substantial heterogeneity and wide CIs. Sensitivity analyses excluding moderate-to-high risk studies demonstrated similar directions of association for education and occupational status. Conclusions: Lower educational attainment and lack of formal employment were associated with higher odds of DFUs among individuals with diabetes mellitus. These findings suggest that socioeconomic factors should be considered in diabetic foot prevention and management strategies alongside conventional clinical risk factors. Further high-quality prospective studies using standardised socioeconomic measures are needed to strengthen the evidence base in this area.

Indexed as

Confounding Factors, EpidemiologicDiabetes MellitusSocial MedicineSystematic Review

Identifiers

PMID42707877
PMCPMC13548240

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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.