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Centre for Policy on Ageing | |
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One size fits all?
— Why we need more sophisticated analytical methods in the explanation of trajectories of cognition in older age and their potential risk factors | | Author(s) | Graciela Muniz Terrera, Carol Brayne, Fiona Matthews |
| Corporate Author | CC75C Study Collaboration Group, UK |
| Journal title | International Psychogeriatrics, vol 22, no 2, March 2010 |
| Pages | pp 291-299 |
| Source | http://www.journals.cambridge.org/ipg doi:10.1017/S1041610209990937 |
| Keywords | Mental health [elderly] ; Mental ageing ; Cognitive processes ; Longitudinal surveys ; Cambridge. |
| Annotation | Cognitive decline in old age varies among individuals. The identification of groups of individuals with similar patterns of cognitive change over time may improve our ability to see whether the effect of risk factors is consistent across groups. Whilst accounting for the missing data, growth mixture models (GMM) were fitted to data from four interview waves of a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study (CC75C; see www.c75c.cam.ac.uk). At all interviews global cognition was assessed using the Mini-mental State Examination (MMSE). Three patterns were identified: a slow decline with age from a baseline of cognitive ability (41% of sample); an accelerating decline from a baseline of cognitive impairment (54% of sample); and a steep constant decline also from a baseline of cognitive impairment (5% of sample). Lower cognitive scores in those with less education were seen at baseline for the first two groups. Only in those with good performance and steady decline was the effect of education strong, with an increased rate of decline associated with poor education. Good mobility was associated with higher initial score in the group with accelerating change but not with rate of decline. Using these analytical methods, it is possible to detect different patterns of cognitive change with age. In this investigation, the effect of education differs with group. To understand the relationship of potential risk factors for cognitive decline, careful attention to dropout and appropriate analytical methods, in addition to long-term detailed studies of the population points, are required. (KJ/RH). |
| Accession Number | CPA-100407208 A |
| Classmark | D: D6: DA: 3J: 8CF |
Data © Centre for Policy on Ageing |
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| ...from the Ageinfo database published by Centre for Policy on Ageing. |
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