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A survey of dementia in the Canberra population: experience with ICD-10 and DSM-III-R criteria

Published online by Cambridge University Press:  09 July 2009

A. S. Henderson ,
A. F. Jorm ,
A. Mackinnon ,
H. Christensen ,
L. R. Scott ,
A. E. Korten  and
C. Doyle
A. S. Henderson*
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
A. F. Jorm
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
A. Mackinnon
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
H. Christensen
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
L. R. Scott
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
A. E. Korten
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
C. Doyle
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT, Australia
*
1 Address for correspondence: Professor A. S. Henderson, National Health and Medical Research Council, Social Psychiatry Research Unit, The Australian National University, GPO Box 4, Canberra, ACT 0200, Australia
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Synopsis

A community survey of 1045 persons aged 70 years and over was conducted to identify cases of dementia in the cities of Canberra and Queanbeyan. Cases were identified using the Canberra Interview for the Elderly, administered by lay interviewers. When diagnostic criteria were rigidly applied, the point prevalence of dementia in the combined sample of community and institutional residents was considerably lower by ICD-10 than by DSM-III-R. Both criteria showed a similar rise in prevalence with age, and no gender difference. Agreement between the two systems had a kappa of only 0·48. ‘Probable’ cases by either criteria were identified solely from respondent-provided information in order to include persons for whom no informant was available. The point prevalence of such ‘probable’ cases was more similar for the two systems, and the kappa coefficient of agreement rose to 0·80. Analysis of the various components required for a diagnosis of dementia showed that the prevalence of all increased with age. Components involving cognitive assessment were correlated with education, but other components were not. The results of the study point to important differences between ICD-10 and DSM-III-R diagnoses of dementia.

Type
Original Articles
Information
Psychological Medicine , Volume 24 , Issue 2 , May 1994 , pp. 473 - 482
Copyright
Copyright © Cambridge University Press 1994

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References

American Psychiatric Association (1987). Diagnostic and Statistical Manual of Mental Disorders (3rd edn revised). DSM-III-R. APA: Washington, DC.Google Scholar
Berkman, L. F. (1986). The association between educational attainment and mental status examinations: of etiologic significance for senile dementias or not? Journal of Chronic Diseases 39, 171–174.CrossRefGoogle ScholarPubMed
Copeland, J. R. M., Dewey, M. E. & Saunders, P. (1991). The epidemiology of dementia. GMS-AGECAT studies of prevalence and incidence, including studies in progress. European Archives of Psychiatry and Clinical Neuroscience, 240, 212–217.CrossRefGoogle ScholarPubMed
Dartigues, J. F., Gagnon, M., Michel, P., Letenneur, L., Commenges, D., Barberger-Gateau, P., Auriacombe, S., Rigal, B., Bedry, R., Alperovitch, A., Orgogozo, J. M., Henry, P., Loiseau, P. & Salamon, R. (1991). Le programme de recherche Paquid sur l'épidémiologie de la démence: méthodes et résultats initiaux. Revue Neurologique 147, 225–230.Google Scholar
Folstein, M. F, Folstein, S. E. & McHugh, P. R. (1975). ‘Mini-Mental State’: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 12, 189–198.CrossRefGoogle Scholar
Folstein, M. F., Bassett, S. S., Anthony, J. C., Romanovski, A. J. & Nestadt, G. R. (1991). Dementia: case ascertainment in a community survey. Journal of Gerontology: Medical Sciences 46, M132–M138.CrossRefGoogle Scholar
Fuhrer, R., Antonucci, T. C., Gagnon, M., Dartigues, J. F., Barberger-Gateau, P. & Alperovitch, A. (1992). Depressive symptomatology and cognitive functioning: an epidemiological survey in an elderly community sample in France. Psychological Medicine 22, 159–172.CrossRefGoogle Scholar
Henderson, A. S. (1994). Dementia. World Mental Health Situation Report. World Health Organization: Geneva.Google Scholar
Henderson, A. S., Jorm, A. F., Mackinnon, A., Christensen, H., Scott, L. R., Korten, A. E. & Doyle, C. (1993). The prevalence of depressive disorders and the distribution of depressive symptoms in later life: a survey using Draft ICD-10 and DSM-III-R. Psychological Medicine 23, 719–729.CrossRefGoogle ScholarPubMed
Hofman, A., Rocca, W. A., Brayne, C., Breteler, M. M. B., Clark, M., Cooper, B. & Copeland, J. R. M. (1991). The prevalence of dementia in Europe: a collaborative study of 1980–1990 findings. International Journal of Epidemiology 20, 736–748.CrossRefGoogle ScholarPubMed
Jorm, A. F. (1990). The Epidemiology of Alzheimer's Disease and Related Disorders. Chapman and Hall: London.Google Scholar
Jorm, A. F., Korten, A. E. & Henderson, A. S. (1987). The prevalence of dementia: a quantitative integration of the literature. Acta Psychiatrica Scandinavica 76, 465–479.CrossRefGoogle ScholarPubMed
Katzman, R. (1993). Education and the prevalence of dementia and Alzheimer's disease. Neurology 43, 13–20.CrossRefGoogle ScholarPubMed
Kittner, S. J., White, L. R., Farmer, M. E., Wolz, M., Kaplan, E., Moes, E., Brody, J. A. & Feinleib, M. (1986). Methodological issues in screening for dementia: the problem of education adjustment. Journal of Chronic Diseases 39, 163–170.CrossRefGoogle ScholarPubMed
Mackinnon, A., Christensen, H., Cullen, J. S., Doyle, C. J., Henderson, A. S., Jorm, A. F., Korten, A. E. & Scott, L. R. (1993). The Canberra Interview for the Elderly: assessment of its validity in the diagnosis of dementia and depression. Acta Psychiatrica Scandinavica 76, 146–151.CrossRefGoogle Scholar
Norušis, M.J./SPSS Inc. (1990). SPSS/PC+ Statistics 4.0. SPSS Inc.: Chicago.Google Scholar
Ritchie, K., Kildea, D. & Robine, J.-M. (1992). The relationship between age and the prevalence of senile dementia: a meta-analysis of recent data. Interntional Journal of Epidemiology 21, 763–769.CrossRefGoogle ScholarPubMed
Social Psychiatry Research Unit (1992). The Canberra Interview for the Elderly: a new field instrument for the diagnosis of dementia and depression by ICD-10 and DSM-III-R. Acta Psychiatrica Scandinavica 85, 105–113.CrossRefGoogle Scholar
World Health Organization (1990). ICD-10 Chapter V. Mental and Behavioural Disorders (including disorders of psychological development). Diagnostic Criteria for Research. 05 1990 Draft for Field Trials, World Health Organization, Division of Mental Health: Geneva.Google Scholar