CoChat
Sign Up
Cited by 301Dementia and Cognitive Impairment ResearchInsurance, Mortality, Demography, Risk ManagementStatistical Methods in Epidemiology

The DOI matches its Crossref record; 55 of the 56 references it cites were found in a registry or an index.

Temporal trend in dementia incidence since 2002 and projections for prevalence in England and Wales to 2040: modelling study

Open access
Ahmadi-Abhari, Sara, Guzman-Castillo, Maria, Bandosz, Piotr, Shipley, Martin J, Muniz-Terrera, Graciela, Singh-Manoux, Archana, Kivimäki, Mika, Steptoe, Andrew, Capewell, Simon, O’Flaherty, Martin, Brunner, Eric J·2017·BMJ
DOI 10.1136/bmj.j2856PMC PMC5497174
Open this paper in CoChat — free accountOpen PDF

Abstract

Objective To forecast dementia prevalence with a dynamic modelling approach that integrates calendar trends in dementia incidence with those for mortality and cardiovascular disease. Design Modelling study. Setting General adult population of England and Wales. Participants The English Longitudinal Study of Ageing (ELSA) is a representative panel study with six waves of data across 2002-13. Men and women aged 50 or more years, selected randomly, and their cohabiting partners were recruited to the first wave of ELSA (2002-03). 11392 adults participated (response rate 67%). To maintain representativeness, refreshment participants were recruited to the study at subsequent waves. The total analytical sample constituted 17 906 people. Constant objective criteria based on cognitive and functional impairment were used to ascertain dementia cases at each wave. Main outcome measures To estimate calendar trends in dementia incidence, correcting for bias due to loss to follow-up of study participants, a joint model of longitudinal and time-to-event data was fitted to ELSA data. To forecast future dementia prevalence, the probabilistic Markov model IMPACT-BAM (IMPACT-Better Ageing Model) was developed. IMPACT-BAM models transitions of the population aged 35 or more years through states of cardiovascular disease, cognitive and functional impairment, and dementia, to death. It enables prediction of dementia prevalence while accounting for the growing pool of susceptible people as a result of increased life expectancy and the competing effects due to changes in mortality, and incidence of cardiovascular disease. Results In ELSA, dementia incidence was estimated at 14.3 per 1000 person years in men and 17.0/1000 person years in women aged 50 or more in 2010. Dementia incidence declined at a relative rate of 2.7% (95% confidence interval 2.4% to 2.9%) for each year during 2002-13. Using IMPACT-BAM, we estimated there were approximately 767 000 (95% uncertainty interval 735 000 to 797 000) people with dementia in England and Wales in 2016. Despite the decrease in incidence and age specific prevalence, the number of people with dementia is projected to increase to 872 000, 1 092 000, and 1 205 000 in 2020, 2030, and 2040, respectively. A sensitivity analysis without the incidence decline gave a much larger projected growth, of more than 1.9 million people with dementia in 2040. Conclusions Age specific dementia incidence is declining. The number of people with dementia in England and Wales is likely to increase by 57% from 2016 to 2040. This increase is mainly driven by improved life expectancy.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/bmj.j2856

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig 1 IMPACT-Better Ageing Model (IMPACT-BAM). Numbers represent different health states and mortality. Population vector represents the number of men and women reaching age 35 and entering the model at each calendar year. States 6 and 7 represent dementia. States 5, 6, 7, and 8 represent functional impairment or disability
Fig 1 IMPACT-Better Ageing Model (IMPACT-BAM). Numbers represent different health states and mortality. Population vector represents the number of men and women reaching age 35 and entering the model at each calendar year. States 6 and 7 represent dementia. States 5, 6, 7, and 8 represent functional impairment or disabilityCC BY · PubMed Central
Fig 2 Projected number of people with dementia in England and Wales 2011-40. Thinner lines represent 95% uncertainty intervals
Fig 2 Projected number of people with dementia in England and Wales 2011-40. Thinner lines represent 95% uncertainty intervalsCC BY · PubMed Central
Fig 3 Age specific estimated number of cases of dementia 2010-40 in men and women
Fig 3 Age specific estimated number of cases of dementia 2010-40 in men and womenCC BY · PubMed Central
Fig 4 Projected prevalence of dementia in England and Wales, 2011-40. Thinner lines represent 95% uncertainty intervals
Fig 4 Projected prevalence of dementia in England and Wales, 2011-40. Thinner lines represent 95% uncertainty intervalsCC BY · PubMed Central
Fig 5 Projected prevalence of dementia in England and Wales, 2011-40, age standardised to the population of 2015. Thinner lines represent 95% uncertainty intervals
Fig 5 Projected prevalence of dementia in England and Wales, 2011-40, age standardised to the population of 2015. Thinner lines represent 95% uncertainty intervalsCC BY · PubMed Central
Fig 6 Sensitivity analysis for number of cases of dementia under alternative assumptions for calendar trend in incidence of dementia. Thinner lines represent 95% uncertainty intervals
Fig 6 Sensitivity analysis for number of cases of dementia under alternative assumptions for calendar trend in incidence of dementia. Thinner lines represent 95% uncertainty intervalsCC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 56 references

Cited by

Sorted by citations

See all 301

Related

Metadata

Authors
Ahmadi-Abhari, S., Guzman-Castillo, M., Bandosz, P., Shipley, M. J., Muniz-Terrera, G., Singh-Manoux, A., Kivimäki, M., Steptoe, A., Capewell, S., O’Flaherty, M., & Brunner, E. J.
Affiliations
  • University of Liverpool (GB)
  • University College London (GB)
ORCID
Venue
BMJ
Publisher
BMJ
Published
2017-07-05
Volume
358
Pages
j2856
ISSN
  • 1756-1833 (ISSN-L)
  • 0959-8138
DOI
10.1136/bmj.j2856
PMC
PMC5497174
OpenAlex
W2724131311
Cited by
301
References
56
Citations by year
2026: 20 · 2025: 43 · 2024: 43 · 2023: 23 · 2022: 38 · 2021: 27 · 2020: 31 · 2019: 42 · 2018: 28 · 2017: 5
FWCI
23.82
Type
journal article
Language
en
Open access
Licence
Locations
  • BMJ (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (publishedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • British Heart Foundation (RG/16/11/32334, K013351, 32334, PG/11/63/29011, RG/13/2/30098)
  • NordForsk (RG/16/11/32334, K013351)
  • Medical Research Council (MR/K013351/1, K013351, RG/16/11/32334)
  • Economic and Social Research Council (ES/J023299/1)
  • National Institute on Aging (R01AG017644)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
dementia, dementia incidence, dementia prevalence projections, temporal trends, Markov model, cardiovascular disease, cognitive impairment, functional disability, mortality, loss to follow-up, England and Wales, population aging, dementia risk factors, English Longitudinal Study of Ageing
MeSH terms
Aged, Dementia, England, Female, Health Surveys, Humans, Life Expectancy, Longitudinal Studies, Male, Middle Aged, Models, Theoretical, Population Surveillance, Socioeconomic Factors, Time Factors, Wales, Incidence, Prevalence, Sex Distribution

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review