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Despite the magnitude of the problem, little is known about the duration of dementia. Survival and risk factors of mortality with dementia and the impact of dementia on the risk of death were investigated using the Personnes Agées Quid (PAQUID) prospective population-based cohort study between 1988 and 1998. Statistical models dealing with interval censoring were performed. Among 3,675 participants aged 65 years or older and initially nondemented, 2,923 have been followed up for 8 years. Of these, 281 persons with incident dementia were actively diagnosed. The mean age of onset of dementia was 82.3 years. In the total population, the relative risk of dying after developing dementia was estimated to be 1.82 (95% confidence interval (CI): 1.77, 2.68) when adjusted for sociodemographic variables and comorbidity. Deaths from cerebrovascular diseases and respiratory diseases were particularly increased among persons with dementia, compared with those without. The median survival time of the persons with dementia was estimated to be 4.5 years. Women with dementia had a longer survival than did men with dementia, particularly for Alzheimer-type dementia (relative risk = 0.47, 95% CI: 0.27, 0.83). Educational level was not significantly associated with survival in persons with dementia. These results provide further evidence of the malignancy of dementia, which will be a challenge for the 21st century.

We consider the problem of estimating the intensity functions for a continuous time 'illness-death' model with intermittently observed data. In such a case, it may happen that a subject becomes diseased between two visits and dies without being observed. Consequently, there is an uncertainty about the precise number of transitions. Estimating the intensity of transition from health to illness by survival analysis (treating death as censoring) is biased downwards. Furthermore, the dates of transitions between states are not known exactly. We propose to estimate the intensity functions by maximizing a penalized likelihood. The method yields smooth estimates without parametric assumptions. This is illustrated using data from a large cohort study on cerebral ageing. The age-specific incidence of dementia is estimated using an illness-death approach and a survival approach.

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Our study provides further support for a decrease in dementia incidence in women using algorithmic diagnosis. Changes in diagnostic boundaries mask this reduction.