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Title: The effect of dementia trends and treatments on longevity and disability: a simulation model based on the MRC Cognitive Function and Ageing Study (MRC CFAS).
Authors: Jagger, C
Matthews, R
Lindesay, J
Robinson, T
Croft, P
Brayne, C
First Published: May-2009
Citation: AGE AGEING, 2009, 38 (3), pp. 319-325
Abstract: BACKGROUND: the numbers with dementia are projected to double between 2001 and 2040, in line with continued increases in life expectancy. Projections have failed to account for the impact of changing risk factors on future numbers with dementia or disability. OBJECTIVE: to estimate the size of the disabled population over the next 20 years and explore the impact of treatments that delay onset of cognitive impairment and associated disability. METHODS: a dynamic macro-simulation projection model was used to calculate the numbers of older people with disability to 2026. Transition rates to disability and death conditional on a range of conditions, calculated from the MRC Cognitive Function and Ageing Study, were applied to the 1992 England and Wales population. Scenarios for trends in dementia incidence, risk factors and treatment were devised from a systematic review and applied. Findings: population ageing alone resulted in 39% more older people between 2006 and 2026 and 82% more with disability. A combination of reduced incidence of cognitive impairment and disabling consequences alongside improved survival provided the largest reductions in the disabled population (15,000) and the numbers cognitively impaired (302,000) compared with ageing of the population alone. Interpretation: population ageing alone will increase the disabled older population by over 80% and the numbers cognitively impaired by almost 50% over the next 20 years with serious implications for the provision of care. Research priorities should focus on earlier detection of dementia and its risk factors, thereby allowing earlier and more targeted treatment to alleviate its associated disability.
DOI Link: 10.1093/ageing/afp016
eISSN: 1468-2834
Type: Journal Article
Appears in Collections:Published Articles, Dept. of Health Sciences

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