Evidence map›Paper›PMID 39748300›Full record

ArticleBMC geriatrics2025

Estimating undiagnosed dementia in England using capture recapture techniques.

Naaheed Mukadam, Louise Marston, Katie Flanagan, Etuini Ma'u, Gary Cheung, Dankmar Böhning

Abstract read
In one paragraph

Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Naaheed MukadamUniversity College London, London, UK. n.mukadam@ucl.ac.uk.
Louise MarstonUniversity College London, London, UK.
Katie FlanaganUniversity College London, London, UK.
Etuini Ma'uUniversity of Auckland, Auckland, New Zealand.
Gary CheungUniversity of Auckland, Auckland, New Zealand.
Dankmar BöhningUniversity of Southampton, Southampton, UK.

Funding

Alzheimer's Society SF-18b-001
6 · The paper itself

Abstract

backgroundTo our knowledge capture-recapture techniques have not been used to estimate dementia prevalence using routinely collected data in England, nor have they been used to estimate changes in undiagnosed dementia over time. In this study we aimed to use routinely collected electronic health records to estimate the number of undiagnosed dementia cases there are in England and how this has changed over time. We also aimed to assess whether proportion of undiagnosed cases differed by age group, ethnicity, socioeconomic deprivation and sex.

methodsWe used routinely collected primary care data linked to hospital episode statistics from 1997 to 2018. We tabulated capture of dementia in each of the two datasets and used the Lincoln-Petersen estimator to estimate numbers of missing dementia diagnoses per year along with the estimated total number of cases and the proportion of cases identified. We calculated age and sex-adjusted prevalence of dementia for each year and used proportion of cases identified to estimate the underlying population prevalence of dementia per year. We conducted beta regression to estimate how sex, age band, deprivation and ethnic group affects the proportion of dementia cases identified, adjusting for year.

resultsProportion of cases out of the estimated total that were identified, rose from 42.4% in 1997 to 84.4% in 2018. Estimated population prevalence of dementia rose from 1997 to a high of 4.4% in 2018 in those aged ≥ 65. Proportion of dementia cases identified did not vary by sex but a lower proportion of those from the South Asian ethnic group were diagnosed compared to the White population (coeff -0.115, 95% CI -0.218 to -0.011). Compared to those aged 65-74, those aged 75-84 and 85 + had higher proportions of dementia diagnosed (75-84 Coeff 0.259, 95% CI 0.153-0.366; 85 + Coeff 0.185, 95% CI 0.079-0.291). Those living in the two most deprived areas had a higher proportion of dementia diagnosed compared to the least deprived area (IMD quintile 4 vs 1 coeff 0.093, 95% CI 0.014 to 0.173, IMD quintile 5 vs 1 coeff 0.162, 95% CI 0.083 to 0.242).

conclusionsProportion of dementia cases identified has increased over time and results indicate that underlying prevalence of dementia may be lower than previously estimated but this needs replication. Greater focus needs to be given to those with dementia onset at younger ages and those from South Asian backgrounds as dementia is relatively under-diagnosed in these groups.

Indexed as

DementiaAgedAged, 80 and overElectronic Health RecordsEnglandFemaleHumansMaleMiddle AgedPrevalenceUndiagnosed DiseasesDementiaEpidemiologyPrevalence

Identifiers

PMID39748300
PMCPMC11694474

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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.