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Estimating undiagnosed dementia in England using capture recapture techniques

Estimating undiagnosed dementia in England using capture recapture techniques
Estimating undiagnosed dementia in England using capture recapture techniques
Background: to 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.

Methods: we 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.

Results: proportion 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).

Conclusions: proportion 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.
Dementia, Epidemiology, Prevalence
1471-2318
Mukadam, Naaheed
62748481-67e0-4b68-b423-62b7fc304344
Marston, Louise
8b23801d-4646-4f80-a944-2dfb3edeaeca
Flanagan, Katie
e78e8eef-b6d9-4cf6-93aa-22aa2c9e1cdb
Ma'u, Etuini
64f6c578-dfaa-4542-a65b-c679caf41d81
Cheung, Gary
8b3ea2be-d710-4fce-a903-2a5ac0f74d5d
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Mukadam, Naaheed
62748481-67e0-4b68-b423-62b7fc304344
Marston, Louise
8b23801d-4646-4f80-a944-2dfb3edeaeca
Flanagan, Katie
e78e8eef-b6d9-4cf6-93aa-22aa2c9e1cdb
Ma'u, Etuini
64f6c578-dfaa-4542-a65b-c679caf41d81
Cheung, Gary
8b3ea2be-d710-4fce-a903-2a5ac0f74d5d
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1

Mukadam, Naaheed, Marston, Louise, Flanagan, Katie, Ma'u, Etuini, Cheung, Gary and Böhning, Dankmar (2025) Estimating undiagnosed dementia in England using capture recapture techniques. BMC Geriatrics, 25 (1), [1]. (doi:10.1186/s12877-024-05591-0).

Record type: Article

Abstract

Background: to 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.

Methods: we 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.

Results: proportion 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).

Conclusions: proportion 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.

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Accepted/In Press date: 27 November 2024
e-pub ahead of print date: 2 January 2025
Published date: 2 January 2025
Keywords: Dementia, Epidemiology, Prevalence

Identifiers

Local EPrints ID: 496661
URI: http://eprints.soton.ac.uk/id/eprint/496661
ISSN: 1471-2318
PURE UUID: b5f07887-9a49-40d1-9925-d58fb706d18f
ORCID for Dankmar Böhning: ORCID iD orcid.org/0000-0003-0638-7106

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Date deposited: 07 Jan 2025 18:56
Last modified: 27 Aug 2025 01:46

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Contributors

Author: Naaheed Mukadam
Author: Louise Marston
Author: Katie Flanagan
Author: Etuini Ma'u
Author: Gary Cheung

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