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European Journal of Ageing

Erschienen in:

01.03.2013 | Original Investigation

Depressive symptoms as predictor of dementia versus continuous cognitive decline: a 3-year prospective study

verfasst von: Andreas B. Neubauer, Hans-Werner Wahl, Horst Bickel

Erschienen in: European Journal of Ageing | Ausgabe 1/2013

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Abstract

Previous research including meta-analytic efforts supports the assumption that depression is able to predict dementia. The mechanisms of this association still remain to be revealed. Some possible explanations as, for example, the glucocorticoid cascade hypothesis assumes that there are underlying changes at the cortical level that drive the association. Therefore, gradual levels of depressive symptoms may also predict gradual change (decline) in cognitive performance. However, testing both of these predictions (depressive symptoms lead to dementia, and depressive symptoms lead to cognitive decline, respectively) with the same data has to our knowledge not been done in the previous literature. A sample of 562 participants aged 65 or older was examined four times over a period of 3 years. Study participants completed established measures of depression and cognitive functioning. Results based on Cox regression analysis showed that depressive symptoms were not able to predict the conversion to dementia during the following 3 years. Additionally, structural equation models as well as latent change score models did not support the assumption that depressive symptoms predict cognitive decline, measured as a continuous variable. We discuss several possibilities to explain these findings including the potential and possible limits of the glucocorticoid cascade hypothesis.

In the year 1995 Germany introduced a statutory long-term care insurance. People who are persistently dependent on the assistance of caregivers are eligible for benefits from this insurance. These participants were excluded from this study as people in need for nursing are often diagnosed with dementia and have lower life expectancies. Because this study was planned as a longitudinal study to investigate the precursors of and risk factors for dementia (see Bickel et al. 2006), this exclusion criterion seemed justifiable.

We used CDR > .5 as cut-off because we did not expect many participants to develop moderate to severe dementia (CDR > 1) within this short measurement interval. Nevertheless, we repeated the analyses using a more strict criterion (classifying only participants with a CDR score of 2 or 3 as demented). The results obtained in this analysis did not change, the regression coefficient for the GDS score remained insignificant.

Please note that the regression weights of MMSE scores and GDS scores have already been fixed to be one in the configural invariance model.

Please note that this model was built under the assumption of strict factorial invariance for the latent depressive symptoms factor. Here, too, the level of factorial invariance across time was determined using the approach described above. Assessing factorial invariance for the cognition change factors was not appropriate given the different approach with which they were modeled. Therefore, factorial invariance was only determined for the latent depressive symptoms factor. The results of this analysis mirror the results for the SEM approach with one exception: the model under the assumption of strict factorial invariance did not fit significantly worse than the model under the assumption of strong factorial invariance, χ_diff ²(6) = 8.58, p = .199. Therefore, the model used for the LCM approach was tested under the assumption of strict factorial invariance for the latent depressive symptoms factor.

We thank an anonymous reviewer for this important observation.

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Titel: Depressive symptoms as predictor of dementia versus continuous cognitive decline: a 3-year prospective study
verfasst von: Andreas B. Neubauer
Hans-Werner Wahl
Horst Bickel
Publikationsdatum: 01.03.2013
Verlag: Springer Netherlands
Erschienen in: European Journal of Ageing / Ausgabe 1/2013
Print ISSN: 1613-9372
Elektronische ISSN: 1613-9380
DOI: https://doi.org/10.1007/s10433-012-0246-4

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