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Onset and Rate of Cognitive Change Before Dementia Diagnosis: Findings From Two Swedish Population-Based Longitudinal Studies

Published online by Cambridge University Press:  17 November 2010

Valgeir Thorvaldsson ,
Stuart W. S. MacDonald ,
Laura Fratiglioni ,
Bengt Winblad ,
Miia Kivipelto ,
Erika Jonsson Laukka ,
Ingmar Skoog ,
Simona Sacuiu ,
Xinxin Guo  and
Svante Östling
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Valgeir Thorvaldsson*
Affiliation:
Department of Psychology, University of Gothenburg, Gothenburg, Sweden
Stuart W. S. MacDonald
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden Department of Psychology, University of Victoria, Victoria, British Colombia, Canada
Laura Fratiglioni
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden
Bengt Winblad
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden
Miia Kivipelto
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden
Erika Jonsson Laukka
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden
Ingmar Skoog
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Simona Sacuiu
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Xinxin Guo
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Svante Östling
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Anne Börjesson-Hanson
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Deborah Gustafson
Affiliation:
Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Boo Johansson
Affiliation:
Department of Psychology, University of Gothenburg, Gothenburg, Sweden
Lars Bäckman
Affiliation:
Aging Research Center, Karolinska Institute, Stockholm, Sweden
*
Correspondence and reprint requests to: Valgeir Thorvaldsson, Department of Psychology, University of Gothenburg, Box 500, SE-405 30, Gothenburg, Sweden. E-mail: [email protected]
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Abstract

We used data from two population-based longitudinal studies to estimate time of onset and rate of accelerated decline across cognitive domains before dementia diagnosis. The H70 includes an age-homogeneous sample (127 cases and 255 non-cases) initially assessed at age 70 with 12 follow-ups over 30 years. The Kungsholmen Project (KP) includes an age-heterogeneous sample (279 cases and 562 non-cases), with an average age of 82 years at initial assessment, and 4 follow-ups spanning 13 years. We fit mixed linear models to the data and determined placement of change points by a profile likelihood method. Results demonstrated onset of accelerated decline for fluid (speed, memory) versus crystallized (verbal, clock reading) abilities occurring approximately 10 and 5 years before diagnosis, respectively. Although decline before change points was greater for fluid abilities, acceleration was more pronounced for crystallized abilities after the change points. This suggests that onset and rate of acceleration vary systematically along the fluid-crystallized ability continuum. There is early onset in fluid abilities, but these changes are difficult to detect due to substantial age-related decline. Onset occurred later and acceleration was greater in crystallized abilities, suggesting that those markers may provide more valid identification of cases in later stages of the prodromal phase. (JINS, 2011, 17, 000–000)

Keywords

Cognitive declinePreclinical dementiaChange pointAccelerated changeFluid abilitiesCrystallized abilities
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 17 , Issue 1 , January 2011 , pp. 154 - 162
Copyright
Copyright © The International Neuropsychological Society 2010

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References

REFERENCES

American Psychiatric Association (1987). Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: American Psychiatric Association.Google Scholar
Amieva, H., Jacqmin-Gadda, H., Orgogozo, J.-M., Le Carret, N., Helmer, C., Letennueur, L., Dartigues, J.-F. (2005). The 9 year cognitive decline before dementia of the Alzheimer type: A prospective population-based study. Brain, 128, 1093–1101.CrossRefGoogle ScholarPubMed
Bäckman, L., Forsell, Y. (1994). Episodic memory functioning in a community-based sample of old adults with major depression: Utilization of cognitive support. Journal of Abnormal Psychology, 103, 361–370.CrossRefGoogle Scholar
Bäckman, L., Jones, S., Berger, A.K., Laukka, E.J., Small, B.J. (2005). Cognitive impairment in preclinical Alzheimer’s disease: A meta-analysis. Neuropsychology, 19, 520–531.CrossRefGoogle ScholarPubMed
Bäckman, L., Small, B.J., Fratiglioni, L. (2001). Stability of the preclinical episodic memory deficit in Alzheimer’s disease. Brain, 124, 96–102.CrossRefGoogle ScholarPubMed
Berg, S. (1980). Psychological functioning in 70- and 75-year-old people: A study in an industrialized city. Acta Psychiatrica Scandinavica, Supplementum, 62, 1–47.Google Scholar
Boyle, P.A., Wilson, R.S., Aggarwal, N.T., Tang, Y., Bennett, D.A. (2006). Mild cognitive impairment: Risk of Alzheimer disease and rate of cognitive decline. Neurology, 67, 441–445.CrossRefGoogle ScholarPubMed
Cattell, R.B. (1971). Abilities: Their structure, growth and action. Boston: Houghton-Mifflin.Google Scholar
Driscoll, I., Resnick, S.M., Troncoso, J.C., An, Y., O’Brien, R., Zonderman, A.B. (2006). Impact of Alzheimer’s pathology on cognitive trajectories in nondemented elderly. Annals of Neurology, 60, 688–695.CrossRefGoogle ScholarPubMed
Dureman, I., Kebbon, L., Österberg, E. (1971). Manual till DS-batteriet [Manual for the DS-battery]. Stockholm: Psykologiförlaget AB.Google Scholar
Fratiglioni, L., Grut, M., Forsell, Y., Viitanen, M., Grafström, R.N., Holmen, R.N., Winblad, B. (1991). Prevalence of Alzheimer’s disease and other dementias in an elderly urban population: Relationship with age, sex and education. Neurology, 41, 1886–1892.CrossRefGoogle Scholar
Fratiglioni, L., Viitanen, M., von Strauss, E., Tontodonati, V., Herlitz, A., Winblad, B. (1997). Very old women at highest risk of dementia and Alzheimer’s disease: Incidence data from the Kungsholmen Project, Stockholm. Neurology, 48, 132–138.CrossRefGoogle ScholarPubMed
Grober, E., Hall, C.B., Lipton, R.B., Zonderman, A.B., Resnick, S.M., Kawas, C. (2008). Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer’s disease. Journal of the International Neuropsychological Society, 14, 266–278.CrossRefGoogle ScholarPubMed
Hall, C.B., Lipton, R.B., Sliwinski, M., Stewart, W.F. (2000). A change point model for estimating the onset of cognitive decline in preclinical Alzheimer’s disease. Statistics in Medicine, 19, 1555–1566.3.0.CO;2-3>CrossRefGoogle ScholarPubMed
Hall, C.B., Ying, J., Kuo, L., Sliwinski, M., Buschke, H., Katz, M., Lipton, R.B. (2001). Estimation of bivariate measurements having different change points, with application to cognitive ageing. Statistics in Medicine, 30, 3695–3714.CrossRefGoogle Scholar
Howieson, D.B., Carlson, N.E., Moore, M.M., Wasserman, D., Abendroth, C.D., Payne-Murphy, J., Kaye, J.A. (2008). The trajectory of mild cognitive impairment onset. Journal of the International Neuropsychological Society, 14, 192–198.CrossRefGoogle ScholarPubMed
Hultsch, D.F., Hertzog, C., Dixon, R.A., Small, B.J. (1998). Memory change in the aged. New York: Cambridge University Press.Google Scholar
Jacqmin-Gadda, H., Commenges, D., Dartigues, J.-F. (2006). Random changepoint model for joint modeling of cognitive decline and dementia. Biometrics, 62, 254–260.CrossRefGoogle Scholar
Jones, S., Laukka, E.J., Bäckman, L. (2006). Differential verbal fluency deficits in the preclinical stages of Alzheimer’s disease and vascular dementia. Cortex, 42, 347–355.CrossRefGoogle ScholarPubMed
Jones, S., Laukka, E.J., Small, B.J., Fratiglioni, L., Bäckman, L. (2004). A preclinical phase in vascular dementia: Cognitive impairment three years before diagnosis. Dementia and Geriatric Cognitive Disorders, 18, 233–239.CrossRefGoogle ScholarPubMed
Lezak, M.D. (1995). Neuropsychological assessment (3rd ed.). New York: Oxford University Press.Google Scholar
Little, R.J.A., Rubin, D.B. (1987). Statistical analysis with missing data. New York: Wiley.Google Scholar
Ming, J., Xion, C., Grundman, M. (2003). Hypothesis testing of a change point during cognitive decline among Alzheimer’s disease patients. Journal of Alzheimer’s Disease, 5, 375–382.Google Scholar
Morris, J.C. (2006). Mild cognitive impairment is early-stage Alzheimer disease. Archives of Neurology, 63, 15–16.CrossRefGoogle ScholarPubMed
Petersen, R.C., Jack, C.R. Jr. (2009). Imaging and biomarkers in early Alzheimer’s disease and mild cognitive impairment. Clinical Pharmacology Therapeutics, 86, 438–441.CrossRefGoogle ScholarPubMed
Raudenbush, S.W., Bryk, A.S. (2002). Hierarchical linear models: Application and data analysis methods (2nd ed.). London: Sage Publications.Google Scholar
Rinder, L., Roupe, S., Steen, B., Svanborg, A. (1975). Seventy-year-old people in Gothenburg: A population study in an industrialized Swedish city. Acta Medica Scandinavica, 198, 397–407.CrossRefGoogle Scholar
Sacuiu, S., Gustafson, D., Johansson, B., Thorvaldsson, V., Berg, S., Sjögren, M., Skoog, I. (2009). The pattern of cognitive symptoms predicts time to dementia onset. Alzheimer’s & Dementia, 5, 199–206.CrossRefGoogle ScholarPubMed
Sacuiu, S., Sögren, M., Johansson, B., Skoog, I. (2005). Prodromal cognitive signs of dementia in 85-year-olds using four sources of information. Neurology, 65, 1894–1900.CrossRefGoogle ScholarPubMed
Schaie, K.W. (1996). Intellectual development in adulthood: The Seattle Longitudinal Study. New York: Academic Press.Google Scholar
Skoog, I., Nilsson, L., Palmertz, B., Andreasson, L.A., Svanborg, A. (1993). A population-based study of dementia in 85-year-olds. The New England Journal of Medicine, 328, 153–158.CrossRefGoogle ScholarPubMed
Storandt, M., Grant, E.A., Miller, P., Morris, J.C. (2002). Rates of progression in mild cognitive impairment and early Alzheimer’s disease. Neurology, 59, 1034–1041.CrossRefGoogle ScholarPubMed
Svanborg, A. (1977). Seventy-year-old people in Gothenburg: A population study in an industrialized Swedish city II. General presentation of social and medical conditions. Acta Medica Scandinavica, 611, 5–37.CrossRefGoogle Scholar
Tuokko, H., Hadjistavropoulos, T., Miller, J.A., Beattie, B.L. (1992). The Clock Test: A sensitive measure to differentiate normal elderly from those with Alzheimer Disease. Journal of the American Geriatrics Society, 40, 579–584.CrossRefGoogle ScholarPubMed
Wechsler, D. (1981). Manual for the Wechsler Adult Intelligence Scale-Revised. New York: The Psychological Corporation.Google Scholar
Wilson, R.S., Beckett, L.A., Bennett, D.A., Albert, M.S., Evans, D.A. (1999). Change in cognitive function in old persons from a community population: Relation to age and Alzheimer disease. Archives of Neurology, 56, 1274–1279.CrossRefGoogle Scholar