Demographic, health, cognitive, and sensory variables as predictors of mortality in very old adults.

Anstey, Kaarin J., Luszcz, Mary A., Giles, Lynne C., Andrews, Gary R.·2001·Psychology and Aging

Abstract

Cognitive and sensorimotor predictors of mortality were examined in the Australian Longitudinal Study of Ageing, controlling for demographic and health variables. A stratified random sample of 1,947 males and females aged 70 and older were interviewed, and 1,500 were assessed on measures of health, memory. verbal ability, processing speed, vision, hearing, and grip strength in 1992 and 1994. Analyses of incident rate ratios for mortality over 4- and 6-year periods were conducted using Cox hierarchical regression analyses. Results showed that poor performance on nearly all cognitive variables was associated with mortality, but many of these effects were explained by measures of self-rated health and disease. Significant decline in hearing and cognitive performance also predicted mortality as did incomplete data at Wave 1. Results suggest that poor cognitive performance and cognitive decline in very old adults reflect both biological aging and disease processes.

Cites (5)

  1. Self-rated health and mortality: a review of twenty-seven community studies.
    Idler, Ellen L., Benyamini, Yael · 1997 · Journal of Health and Social Behavior
  2. Sensory functioning and intelligence in old age: A strong connection.
    Lindenberger, Ulman, Baltes, Paul B. · 1994 · Psychology and Aging
  3. The Role of <EMPH TYPE="ITAL">APOE</EMPH> ∊4 in Modulating Effects of Other Risk Factors for Cognitive Decline in Elderly Persons
    Haan, Mary N. · 1999 · JAMA
  4. Psychological predictors of mortality in old age
    Maier, H., Smith, J. · 1999 · The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
  5. Health, cognitive, and psychosocial factors as predictors of mortality in an elderly community sample.
    Korten, A E, Jorm, A F, Jiao, Z, Letenneur, L, Jacomb, P A, Henderson, A S, Christensen, H, Rodgers, B · 1999 · Journal of Epidemiology and Community Health

Show all 5 references

Cited by (15)

  1. Objectively measured physical capability levels and mortality: systematic review and meta-analysis
    Cooper, R., Kuh, D., Hardy, R., Mortality Review Group, on behalf of the FALCon and HALCyon study teams · 2010 · BMJ
  2. Muscular Strength as A Predictor of All-Cause Mortality in an Apparently Healthy Population: A Systematic Review and Meta-Analysis of Data From Approximately 2 Million Men and Women
    García-Hermoso, Antonio, Cavero-Redondo, Iván, Ramírez-Vélez, Robinson, Ruiz, Jonatan R., Ortega, Francisco B., Lee, Duck-Chul, Martínez-Vizcaíno, Vicente · 2018 · Archives of Physical Medicine and Rehabilitation
  3. Prognostic value of handgrip strength in people aged 60 years and older: A systematic review and meta-analysis
    Rijk, Joke M, Roos, Paul RKM, Deckx, Laura, van den Akker, Marjan, Buntinx, Frank · 2016 · Geriatrics & Gerontology International
  4. Effect of social networks on 10 year survival in very old Australians: the Australian longitudinal study of aging
    Giles, Lynne C, Glonek, Gary F V, Luszcz, Mary A, Andrews, Gary R · 2005 · Journal of Epidemiology and Community Health
  5. What cognitive changes can be expected with normal ageing?
    Christensen, Helen · 2001 · Australian & New Zealand Journal of Psychiatry

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Demographic, health, cognitive, and sensory variables as predictors of mortality in very old adults. https://app.cochat.ai/papers/10.1037//0882-7974.16.1.3
The paper
Anstey, K. J., Luszcz, M. A., Giles, L. C., & Andrews, G. R. (2001). Demographic, health, cognitive, and sensory variables as predictors of mortality in very old adults. Psychology and Aging. https://doi.org/10.1037//0882-7974.16.1.3

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.