Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-26T06:30:51.650Z Has data issue: false hasContentIssue false
  • English
  • Français

The Sydney Memory and Ageing Study (MAS): methodology and baseline medical and neuropsychiatric characteristics of an elderly epidemiological non-demented cohort of Australians aged 70–90 years

Published online by Cambridge University Press:  19 July 2010

Perminder S. Sachdev ,
Henry Brodaty ,
Simone Reppermund ,
Nicole A. Kochan ,
Julian N. Trollor ,
Brian Draper ,
Melissa J. Slavin ,
John Crawford ,
Kristan Kang  and
G. Anthony Broe
...Show all authors
Perminder S. Sachdev*
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick NSW 2031, Australia Primary Dementia Collaborative Research Centre, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
Henry Brodaty
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Primary Dementia Collaborative Research Centre, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Academic Department for Old Age Psychiatry, Prince of Wales Hospital, Avoca Street, Randwick, NSW, Australia
Simone Reppermund
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
Nicole A. Kochan
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick NSW 2031, Australia
Julian N. Trollor
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Intellectual Disability Mental Health, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
Brian Draper
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Primary Dementia Collaborative Research Centre, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Academic Department for Old Age Psychiatry, Prince of Wales Hospital, Avoca Street, Randwick, NSW, Australia
Melissa J. Slavin
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
John Crawford
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
Kristan Kang
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
G. Anthony Broe
Affiliation:
Primary Dementia Collaborative Research Centre, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Prince of Wales Medical Research Institute, Randwick NSW, Australia Ageing Research Centre, Prince of Wales Hospital, Barker Street, Randwick, NSW, Australia
Karen A. Mather
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick NSW 2031, Australia
Ora Lux
Affiliation:
Brain and Ageing Research Program, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia South Eastern Area Laboratory Service, Prince of Wales Hospital, Randwick, NSW, Australia
*
Correspondence should be addressed to: Professor P. Sachdev, UNSW School of Psychiatry, NPI, Euroa Centre, Prince of Wales Hospital, Barker Street, Randwick NSW 2031, Australia. Phone: +612-9382 3763; Fax: +612-9382 3774. Email: p.sachdev@unsw.edu.au.
Get access

Abstract

Background: The Sydney Memory and Ageing Study (Sydney MAS) was initiated in 2005 to examine the clinical characteristics and prevalence of mild cognitive impairment (MCI) and related syndromes, and to determine the rate of change in cognitive function over time.

Methods: Non-demented community-dwelling individuals (N = 1037) aged 70–90 were recruited from two areas of Sydney, following a random approach to 8914 individuals on the electoral roll. They underwent detailed neuropsychiatric and medical assessments and donated a blood sample for clinical chemistry, proteomics and genomics. A knowledgeable informant was also interviewed. Structural MRI scans were performed on 554 individuals, and subgroups participated in studies of falls and balance, metabolic and inflammatory markers, functional MRI and prospective memory. The cohort is to be followed up with brief telephone reviews annually, and detailed assessments biannually.

Results: This is a generally well-functioning cohort mostly living in private homes and rating their health as being better than average, although vascular risk factors are common. Most (95.5%) participants or their informants identified a cognitive difficulty, and 43.5% had impairment on at least one neuropsychological test. MCI criteria were met by 34.8%; with19.3% qualifying for amnestic MCI, whereas 15.5% had non-amnestic MCI; 1.6% had impairment on neuropsychological test performance but no subjective complaints; and 5.8% could not be classified. The rate of MCI was 30.9% in the youngest (70–75) and 39.1% in the oldest (85–90) age bands. Rates of depression and anxiety were 7.1% and 6.9% respectively.

Conclusions: Cognitive complaints are common in the elderly, and nearly one in three meet criteria for MCI. Longitudinal follow-up of this cohort will delineate the progression of complaints and objective cognitive impairment, and the determinants of such change.

Keywords

mild cognitive impairmentcognitive functiondementiacognitive declinemagnetic resonance imaging (MRI)fMRImetabolic syndromeinflammatory markersbalancefallsdepressionanxietygeneticsproteomics
Type
Research Article
Information
International Psychogeriatrics , Volume 22 , Special Issue 8: Focus on prevention in psychogeriatrics , December 2010 , pp. 1248 - 1264
Copyright
Copyright © International Psychogeriatric Association 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

ABS (1998). Mental Health and Wellbeing: Profile of Adults, Australia, 1997. Canberra: Australian Bureau of Statistics.Google Scholar
ABS (1999). Older People, Australia: A Social Report. Cat. No. 4109.0. Canberra: Australian Bureau of Statistics.Google Scholar
ABS (2003). Ageing in Australia: Census of Population and Housing 2001. Canberra: Australian Bureau of Statistics.Google Scholar
ABS (2006). Census of Population and Housing. Cat. No. 2914.0. Canberra: Australian Bureau of Statistics.Google Scholar
Access Economics (2006). Dementia in the Asia Pacific Region: The Epidemic is Here. Canberra: Alzheimer's Australia.Google Scholar
AIHW (2008). Australia's Health 2008. Canberra: Australian Institute of Health and Welfare. Available at www.aihw.gov.au/publications/index.cfm/title/10585.Google Scholar
Anderson, T. M., Sachdev, P. S., Brodaty, H., Trollor, J. N. and Andrews, G. (2007). Effects of sociodemographic and health variables on Mini-mental State Exam scores in older Australians. American Journal of Geriatric Psychiatry, 15, 467–476.CrossRefGoogle ScholarPubMed
Bennett, D. A. et al. (2002). Natural history of mild cognitive impairment in older persons. Neurology, 59, 198–205.CrossRefGoogle ScholarPubMed
Benton, A. L. (1967). Problems of test construction in the field of aphasia. Cortex, 3, 32–58.CrossRefGoogle Scholar
Benton, A. L., Sivan, A. B. and Spreen, O. (1966). Der Benton Test (7th edn). Bern: Huber.Google Scholar
Blossom, C. et al. (2007). Early cognitive change in the general population: how do different definitions work? Journal of the American Geriatrics Society, 55, 1534–1540.Google Scholar
Brandt, J., Spencer, M. and Folstein, M. (1988). The telephone interview for cognitive status. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 1, 111–117.Google Scholar
Briganti, E. M. et al. (2003). Untreated hypertension among Australian adults: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Medical Journal of Australia, 179, 135–139.CrossRefGoogle ScholarPubMed
Costa, P. T. and McCrae, R. R. (1992). NEO PI-R Professional Manual. Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI). Odessa: Psychological Assessment Resources Inc.Google Scholar
Crawford, J. R., Stewart, L. E., Cochrane, R. H. B., Foulds, J. A., Besson, J. A. O. and Parker, D. M. (1989). Estimating premorbid IQ from demographic variables: regression equations derived from a U.K. sample. British Journal of Clinical Psychology, 28, 275–278.CrossRefGoogle Scholar
Crook, T. H., Feher, E. P. and Larrabee, G. J. (1992). Assessment of memory complaint in age-associated memory impairment: the MAC-Q. International Psychogeriatrics, 4, 165–175.CrossRefGoogle ScholarPubMed
Cummings, J. L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D. A. and Gornbein, J. (1994). The Neuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia. Neurology, 44, 2308–2314.CrossRefGoogle ScholarPubMed
de Jager, C. A., Budge, M. M. and Clarke, R. (2003). Utility of TICS-M for the assessment of cognitive function in older adults. International Journal of Geriatric Psychiatry, 18, 318–324.CrossRefGoogle ScholarPubMed
Diener, E., Emmons, R. A., Larsen, R. J. and Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49, 71–75.CrossRefGoogle ScholarPubMed
Doty, R. L., Marcus, A. and Lee, W. W. (1996). Development of the 12-item cross-cultural Smell Identification Test™. Laryngoscope, 106, 353–356.CrossRefGoogle ScholarPubMed
Ellis, K. A. et al. (2009). The Australian Imaging, Biomarkers and Lifestyle (AIB) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease. International Psychogeriatrics, 21, 672–687.CrossRefGoogle Scholar
Epping-Jordan, J. E. and Üstün, T. B. (2000). The WHODAS II: leveling the playing field for all disorders. WHO Mental Health Bulletin, 6, 5–6.Google Scholar
Farrer, L. A. et al. (1997). Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease: a meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA, 278, 1349–1356.CrossRefGoogle ScholarPubMed
Fastenau, P. S., Denburg, N. L. and Mauer, B. A. (1998). Parallel short forms for the Boston Naming Test: psychometric properties and norms for older adults. Journal of Clinical and Experimental Neuropsychology, 20, 828–834.CrossRefGoogle ScholarPubMed
Flicker, C., Ferris, S. H. and Reisberg, B. (1991). Mild cognitive impairment in the elderly: predictors of dementia. Neurology, 41, 1006–1009.CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E. and 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 ScholarPubMed
Goldberg, D., Bridges, K., Duncan-Jones, P. and Grayson, D. (1988). Detecting anxiety and depression in general medical settings. BMJ, 297, 897–899.CrossRefGoogle ScholarPubMed
Graham, J. E. et al. (1997) Prevalence and severity of cognitive impairment with and without dementia in an elderly population. Lancet, 349, 1793–1796.CrossRefGoogle Scholar
Grundman, M. et al. (2004). Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials. Archives of Neurology, 61, 59–66.CrossRefGoogle ScholarPubMed
Harris, M. E., Ivnik, R. J. and Smith, G. E. (2002). Mayo's Older Americans Normative Studies: expanded AVLT Recognition Trial norms for ages 57 to 98. Journal of Clinical and Experimental Neuropsychology, 24, 214–220CrossRefGoogle ScholarPubMed
Henderson, A. S. et al. (1995). Apolipoprotein E allele ɛ4, dementia, and cognitive decline in a population sample. Lancet, 346, 1387–1390.CrossRefGoogle Scholar
Hindmarch, I., Lehfeld, H., de Jongh, P. and Erzigkeit, H. (1998). The Bayer Activities of Daily Living Scale (B-ADL). Dementia and Geriatric Cognitive Disorders, 9, 20–26.CrossRefGoogle ScholarPubMed
Hixson, J. E. and Vernier, D. T. (1990). Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with Hha1. Journal of Lipid Research, 31, 545–548.CrossRefGoogle Scholar
Hodge, A., Patterson, A. J., Brown, W. J., Ireland, P. and Giles, G. (2000). The Anti Cancer Council of Victoria FFQ: relative validity of nutrient intakes compared with weighed food records in young to middle-aged women in a study of iron supplementation. Australian and New Zealand Journal of Public Health, 24, 576–583.CrossRefGoogle Scholar
Ivnik, R. J., Malec, J. F., Tangalos, E. G., Petersen, R. C., Kokmen, E. and Kurland, L. T. (1990). The Auditory-Verbal Learning Test (AVLT): norms for ages 55 years and older. Psychological Assessment, 2, 304–312.CrossRefGoogle Scholar
Ivnik, R. J. et al. (1992a). Mayo's Older Americans Normative Studies: updated AVLT norms for ages 56 to 97. Clinical Neuropsychology, 6, S83–S104.CrossRefGoogle Scholar
Ivnik, R. J. et al. (1992b). Mayo's Older Americans Normative Studies: WAIS-R norms for ages 56 to 97. Clinical Neuropsychology, 6, S1–S30.CrossRefGoogle Scholar
Jorm, A. F. (1994). A short form of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): development and cross-validation. Psychological Medicine, 24, 145–153.CrossRefGoogle Scholar
Jorm, A. F. et al. (2004). Memory complaints in a community sample aged 60–64 years: associations with cognitive functioning, psychiatric symptoms, medical conditions, APOE genotype, hippocampus and amygdala volumes, and white matter hyperintensities. Psychological Medicine, 34, 1495–1506.CrossRefGoogle Scholar
Jorm, A. F., Mather, K. A., Butterworth, P., Anstey, K. J., Christensen, H. and Easteal, S. (2007). APOE genotype and cognitive functioning in a large age-stratified population sample. Neuropsychology, 21, 1–8.CrossRefGoogle Scholar
Kaplan, E., Goodglass, H. and Weintraub, S. (2001). The Boston Naming Test. Baltimore: Lippincott, Williams & Wilkins.Google Scholar
Kessler, R. and Mroczek, D. (1994). Final version of our Non-specific Psychological Distress Scale. Unpublished memo. Ann Arbor, MI: Survey Research Center of the Institute for Social Research, University of Michigan.Google Scholar
Klove, H. (1963). Clinical neuropsychology. InForster, F. M. (ed.), The Medical Clinics of North America (pp. 1647–1658). New York: Saunders.Google Scholar
Kochan, N. A. et al. (2010). Effect of different impairment criteria on prevalence of “objective” mild cognitive impairment in a community sample. American Journal of Geriatric Psychiatry. Epublished ahead of print, doi: 10.1097/JGP.0b013e3181d6b6a9CrossRefGoogle Scholar
Kumar, R. et al. (2005). Prevalence of Mild Cognitive Impairment in 60- to 64-year-old community-dwelling individuals: the Personality and Total Health Through Life 60+ study. Dementia and Geriatric Cognitive Disorders, 19, 67–74.CrossRefGoogle ScholarPubMed
Larrieu, S. et al. (2002). Incidence and outcome of mild cognitive impairment in a population-based prospective cohort. Neurology, 59, 1594–1599.CrossRefGoogle Scholar
Lawton, M. P. and Brody, E. M. (1969). Assessment of older people: self maintaining and instrumental activities of daily living. Gerontologist, 9, 179–186.CrossRefGoogle ScholarPubMed
Lechevallier-Michel, N., Fabrigoule, C., Lafont, S., Letenneur, L. and Dartigues, J. (2004). Normes pour le MMSE, le test de rétention visuelle de Benton, le set test d'Isaacs (15s. et 60s), le sous-test des codes de la WAIS et le test barrage de Zazzo, enfunction de l'âge, du sese et du niveau d'études, chez des sujets âgés de 70 ans et plus: données de la chorte PAQUID. Revue Neurologique, 160, 1059–1070.CrossRefGoogle Scholar
Liu, T. et al. (2010). The effects of age and sex on cortical sulci in the elderly. Neuroimage, 51, 19–27.CrossRefGoogle ScholarPubMed
Lopez, O. L. et al. (2003). Prevalence and classification of mild cognitive impairment in the Cardiovascular Health Study Cognition Study: Part 1. Archives of Neurology, 60, 1385–1389.CrossRefGoogle ScholarPubMed
Lord, S. R., Rogers, M. W., Howland, A. and Fitzpatrick, R. (1999). Lateral stability, sensimotor function and falls in older people. Journal of the American Geriatrics Society, 47, 1077–1081.CrossRefGoogle Scholar
Lord, S. R., Murray, S. M., Chapman, K., Munro, B. and Tiedemann, A. (2002). Sit-to-stand performance depends on sensation, speed, balance, and psychological status in addition to strength in older people. Journals of Gerontology: Medical Sciences, 57, M539–M543.Google ScholarPubMed
Mathers, C., Vos, T. and Stevenson, C. (1999). The Burden of Disease and Injury in Australia. Canberra: Australian Institute of Health and Welfare.Google Scholar
McLennan, W. (1997). ASCO: Australian Standard Classification of Occupations (2nd edn). Canberra: Australian Bureau of Statistics.Google Scholar
Mitchell, T., Woodward, M. and Hirose, Y. (2008). A survey of attitudes of clinicians towards the diagnosis and treatment of mild cognitive impairment in Australia and New Zealand. International Psychogeriatrics, 20, 77–85.CrossRefGoogle ScholarPubMed
Morris, J. C. (1993). The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology, 43, 2412–2414.CrossRefGoogle ScholarPubMed
Nelson, H. E. and Willison, J. (1991). National Adult Reading Test (NART): Test Manual (2nd edn). Windsor: NFER Nelson.Google Scholar
Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194.CrossRefGoogle ScholarPubMed
Petersen, R. C. et al. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58, 1985–1002.CrossRefGoogle ScholarPubMed
Petersen, R. C. et al. (2009) Mild cognitive impairment: ten years later. Archives of Neurology, 66, 1447–1455.CrossRefGoogle ScholarPubMed
Posiadlo, D. and Richardson, S. (1991). The timed “up and go”: a test of basic functional mobility for frail elderly persons. Journal of the American Geriatrics Society, 39, 142–148.CrossRefGoogle Scholar
Reitan, R. M. and Wolfson, D. (1993). The Halstead-Reitan Neuropsychological Test Battery: Theory and Clinical Interpretation (2nd edn). Tucson, AZ: Neuropsychology Press.Google Scholar
Rey, A. (1964). L'Examen Clinique en Psychologie. Paris: Presses Universitaires de France.Google Scholar
Richardson, J., Day, N., Peacock, S. and Iezzi, A. (2004). Measurement of the quality of life for economic evaluation and the Assessment of Quality of Life (AQoL) Mark 2 instrument. Australian Economic Review, 37, 62–88.CrossRefGoogle Scholar
Ritchie, K. and Lovestone, S. (2002). The dementias. Lancet, 360, 1759–1766.CrossRefGoogle ScholarPubMed
Ritchie, K. and Touchon, J. (2000). Mild cognitive impairment: conceptual basis and current nosological status. Lancet, 355, 225–228.CrossRefGoogle ScholarPubMed
Ritchie, K., Artero, S. and Touchon, J. (2001). Classification criteria for mild cognitive impairment: a population-based validation study. Neurology, 56, 37–42.CrossRefGoogle ScholarPubMed
Roberts, R. O. et al. (2008). The Mayo Clinic Study of Aging: design and sampling, participation, baseline measures and sample characteristics. Neuroepidemiology, 30, 58–68.CrossRefGoogle Scholar
Slavin, M. J. et al. (2010). Prevalence and predictors of subjective cognitive complaints in the Sydney Memory and Ageing Study. Americal Journal of Geriatric Psychiatry. Epublished ahead of print, doi: 10.1097/JGP.0b013e3181df49fbCrossRefGoogle Scholar
Spreen, O. and Benton, A. L. (1969). Neurosensory Centre Comprehensive Examination for Aphasia Manual (NCCEA). Victoria: University of Victoria.Google Scholar
Tombaugh, T. N. (2004). Trail making test A and B: Normative data stratified by age and education. Archives of Clinical Neuropsychology 19, 203–214.CrossRefGoogle Scholar
Tombaugh, T. N., Kozak, J. and Rees, L. (1999). Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Archives of Clinical Neuropsychology, 14, 167–177.Google ScholarPubMed
Trollor, J., Anderson, T., Sachdev, P., Brodaty, H. and Andrews, G. (2007). Prevalence of mental disorders in the elderly: the Australian National Mental and Well-being Survey. American Journal of Geriatric Psychiatry, 15, 455–466.CrossRefGoogle ScholarPubMed
Unverzagt, F. W. et al. (2001). Prevalence of cognitive impairment: data from the Indianapolis Study of Health and Aging. Neurology, 57, 1655–1662.CrossRefGoogle ScholarPubMed
Waite, L. M., Broe, G. A., Garyson, D. A. and Creasey, H. (2001). Preclinical syndromes predict dementia: the Sydney older persons study. Journal of Neurology, Neurosurgery and Psychiatry, 71, 296–302.CrossRefGoogle ScholarPubMed
Watson, D., Clark, L. A. and Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS Scales. Journal of Personality and Social Psychology, 54, 1063–1070.CrossRefGoogle ScholarPubMed
Wechsler, D. (1981). WAIS-R Manual. Ner York: The Psychological Corporation.Google Scholar
Wechsler, D. (1997a). Wechsler Adult Intelligence Scale-III. San Antonio: The Psychological Corporation.Google Scholar
Wechsler, D. (1997b). Wechsler Adult Intelligence Scale- 3rd Edition (WAIS-3®). San Antonio: Harcourt Assessment.Google Scholar
Winblad, B. et al. (2004). Mild cognitive impairment – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246.CrossRefGoogle Scholar
Wen, W. and Sachdev, P. S. (2004). Extent and distribution of white matter hyperintensities in stroke patients: the Sydney Stroke Study. Stroke, 35, 2813–2819.CrossRefGoogle Scholar
Wen, W., Sachdev, P. S., Li, J. J., Chen, X. and Anstey, K. J. (2009). White matter hyperintensities in the forties: their prevalence and topography in an epidemiological sample aged 44–48. Human Brain Mapping, 30, 1155–1167.CrossRefGoogle Scholar
Yesavage, J. A. et al. (1983). Development and validation of a geriatric depression rating scale: a preliminary report. Journal of Psychatric Research, 17, 37–49.CrossRefGoogle Scholar