Estimating undiagnosed dementia in England using capture recapture techniques
2025

Estimating Undiagnosed Dementia in England

publication Evidence: moderate

Author Information

Author(s): Naaheed Mukadam, Marston Louise, Flanagan Katie, Ma’u Etuini, Cheung Gary, Böhning Dankmar

Primary Institution: University College London

Hypothesis

Can capture-recapture techniques be used to estimate the number of undiagnosed dementia cases in England and how this has changed over time?

Conclusion

The proportion of dementia cases identified has increased over time, suggesting that the underlying prevalence of dementia may be lower than previously estimated.

Supporting Evidence

  • The proportion of identified dementia cases rose from 42.4% in 1997 to 84.4% in 2018.
  • Estimated population prevalence of dementia rose to a high of 4.4% in 2018 for those aged 65 and older.
  • Lower proportions of dementia cases were diagnosed in the South Asian ethnic group compared to the White population.
  • Older age groups (75-84 and 85+) had higher proportions of dementia diagnosed compared to those aged 65-74.
  • Individuals in the most deprived areas had a higher proportion of dementia diagnosed compared to the least deprived.

Takeaway

This study looked at how many people with dementia in England are not diagnosed and found that more people are being diagnosed now than in the past.

Methodology

The study used routinely collected primary care data linked to hospital episode statistics from 1997 to 2018 and applied capture-recapture techniques to estimate undiagnosed dementia cases.

Potential Biases

The capture-recapture method assumes independence of data sources and a closed population, which may not hold true.

Limitations

Estimates depend on the accuracy of dementia diagnoses in healthcare records, which may be under-captured, especially in earlier years.

Participant Demographics

The study focused on individuals aged 65 and older in England, with analyses stratified by age, sex, ethnicity, and socioeconomic deprivation.

Statistical Information

Confidence Interval

95% CI -0.218 to -0.011

Digital Object Identifier (DOI)

10.1186/s12877-024-05591-0

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