Evidence map›Paper›PMID 41179531›Full record

ArticleJournal of public health research2025

Measuring the population attributable fraction and the potential impact fraction of dementia risk factors in Malta: A population based secondary data analysis.

Anthony Scerri, Charles Scerri

Abstract read
In one paragraph

Article in Journal of public health research, 2025. 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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0citing papers in PubMed
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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

2 authors.

Anthony ScerriDepartment of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta.ORCID https://orcid.org/0000-0002-7231-9710
Charles ScerriDepartment of Pathology, Faculty of Medicine and Surgery, University of Malta, Msida, Malta.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The 2024 Lancet Commission report estimated that up to 45% of global dementia cases could be prevented by addressing modifiable risk factors. However, these estimates are based on international data and may not reflect national differences in risk factor prevalence or intervention feasibility. This study uses a population-based secondary data analysis to estimate both the population attributable fraction (PAF) and the potential impact fraction (PIF) for 14 dementia risk factors specific to the Maltese population. Design and methods: Secondary data were used to estimate the prevalence of each risk factor from Maltese peer-reviewed studies or reputable international datasets where national data were unavailable. Unweighted PAFs were calculated using Levin's formula and adjusted for overlap between risk factors. PIFs were derived by applying evidence-based relative risk reductions from published intervention studies for each weighted PAF, representing more realistic outcomes of targeted interventions. Results: The weighted PAF for Malta was 40.47%, indicating the theoretical maximum proportion of preventable dementia cases if all risk factors were eliminated. The total PIF was 33.82%, reflecting the estimated reduction in dementia incidence if feasible interventions were implemented. The risk factors contributing most to preventable cases were high LDL cholesterol (6.15%), loneliness (4.29%), and untreated vision loss (4.25%). Conclusions: Up to one-third of dementia cases in Malta could be reduced through population-level strategies targeting modifiable risk factors. These PIF estimates provide realistic, evidence-informed guidance for national dementia prevention planning and prioritisation.

Indexed as

dementiaMaltapopulation attributable fractionpotential impact fractionrisk factors

Identifiers

PMID41179531
PMCPMC12576114

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.