Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-10T14:08:03.281Z Has data issue: false hasContentIssue false
  • English
  • Français

Positive components of mental health provide significant protection against likelihood of falling in older women over a 13-year period

Published online by Cambridge University Press:  14 March 2012

Richard A. Burns ,
Julie Byles ,
Paul Mitchell  and
Kaarin J. Anstey
Richard A. Burns*
Affiliation:
Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia
Julie Byles
Affiliation:
Research Centre for Gender, Health and Ageing, University of Newcastle, Newcastle, NSW, Australia
Paul Mitchell
Affiliation:
Centre for Vision Research, Westmead Millennium Institute and Department of Ophthalmology, The University of Sydney, Sydney, NSW, Australia
Kaarin J. Anstey
Affiliation:
Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia
*
Correspondence should be addressed to: Richard A. Burns, Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia. Phone: +61 02 6125 3132; Fax: +61 2 6125 0733. Email: Richard.Burns@anu.edu.au.
Get access Rights & Permissions [Opens in a new window]

Abstract

Background: In late life, falls are associated with disability, increased health service utilization and mortality. Physical and psychological risk factors of falls include falls history, grip strength, sedative use, stroke, cognitive impairment, and mental ill-health. Less understood is the role of positive psychological well-being components. This study investigated the protective effect of vitality on the likelihood of falls in comparison to mental and physical health.

Methods: Female participants were drawn from the Dynamic Analyses to Optimise Ageing (DYNOPTA) harmonization project. Participants (n = 11,340) were aged 55–95 years (Mean = 73.68; SD = 4.31) at baseline and observed on up to four occasions for up to 13 years (Mean = 5.30; SD = 2.53).

Results: A series of random intercept logistic regression models consistently identified vitality's protective effects on falls as a stronger effect in the reduction of the likelihood of falls than the effect of mental health. Vitality is a significant predictor of falls likelihood even after adjusting for physical health, although the size of effect is substantially explained by its covariance with mental and physical heath.

Conclusions: Vitality has significant protective effects on the likelihood of falls. In comparison with mental health, vitality reported much stronger protective effects on the likelihood to fall in comparison with the risk associated with poor mental health in a large sample of older female adults. Both physical health and mental health account for much of the variance in vitality, but vitality still reports a protective effect on the likelihood of falls.

Keywords

longitudinal studiesresearch design and methodologydepression
Type
Research Article
Information
International Psychogeriatrics , Volume 24 , Issue 9 , September 2012 , pp. 1419 - 1428
Copyright
Copyright © International Psychogeriatric Association 2012

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

Anstey, K. J., Sanden, C. V. and Luszcz, M. A. (2006). An 8-year prospective study of the relationship between cognitive performance and falling in very old adults. Journal of the American Geriatrics Society, 54, 1169–1176.CrossRefGoogle ScholarPubMed
Anstey, K. et al. (2008). Psychological well-being is an independent predictor of falling in an 8-year follow-up of older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 63, 249–257.CrossRefGoogle Scholar
Anstey, K. J. et al. (2010). Cohort profile: the Dynamic Analyses to Optimize Ageing (DYNOPTA) project. International Journal of Epidemiology, 39, 44–51.CrossRefGoogle ScholarPubMed
Australian Bureau of Statistics (1998). Population Projections 1997 to 2051. Cat. No. 3222.0. Canberra, Australia: ABS, Australian Government Publication Services.Google Scholar
Bartsch, L. J., Butterworth, P., Byles, J. E., Mitchell, P., Shaw, J., and Anstey, K. J. (2011). Examining the SF-36 in an older population: analysis of data and presentation of Australian adult reference scores from the Dynamic Analyses to Optimise Ageing (DYNOPTA) project. Quality of Life Research. 20, 1227–1236.CrossRefGoogle Scholar
Begg, S. (2007). The Burden of Disease and Injury in Australia 2003. Canberra, Australia: Australian Institute of Health and Welfare.Google Scholar
Burns, R. A., Anstey, K. J. and Windsor, T. D. (2011). Subjective well-being mediates the effects of resilience and mastery on depression and anxiety in a large community sample of young and middle-aged adults. Australian and New Zealand Journal of Psychiatry, 45, 240–248.CrossRefGoogle Scholar
Covinsky, K. E. et al. (2001). History and mobility exam index to identify community-dwelling elderly persons at risk of falling. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 56, 253–259.CrossRefGoogle ScholarPubMed
Ganz, D. A. et al. (2005). Monitoring falls in cohort studies of community-dwelling older people: effect of the recall interval. Journal of the American Geriatrics Society, 53, 2190–2194.CrossRefGoogle ScholarPubMed
Gill, S. C. et al. (2006). Mental health and the timing of men's retirement. Social Psychiatry and Psychiatric Epidemiology, 41, 515–522.CrossRefGoogle ScholarPubMed
Graafmans, W. C. et al. (1996). Falls in the elderly: a prospective study of risk factors and risk profiles. American Journal of Epidemiology, 143, 1129–1136.CrossRefGoogle ScholarPubMed
Heinrich, S. et al. (2010). Cost of falls in old age: a systematic review. Osteoporosis International, 21, 891–902.CrossRefGoogle ScholarPubMed
Huppert, F. A. and Whittington, J. E. (2003). Evidence for the independence of positive and negative well-being: implications for quality of life assessment. British Journal of Health Psychology, 8, 107–122.CrossRefGoogle ScholarPubMed
Kannus, P. et al. (2006). Preventing falls among elderly people in the hospital environment. Medical Journal of Australia, 184, 372–373.CrossRefGoogle ScholarPubMed
Kron, M. et al. (2003). Risk indicators for falls in institutionalized frail elderly. American Journal of Epidemiology, 158, 645–653.CrossRefGoogle ScholarPubMed
National Health and Medical Research Council (Australia) (2001). Australian Alcohol Guidelines: Health Risks and Benefits. Canberra, Australia: National Health and Medical Research Council.Google Scholar
Nevitt, M. C. et al. (1991). Risk factors for injurious falls: a prospective study. Journal of Gerontology, 46, M164–M170.CrossRefGoogle ScholarPubMed
Noale, M. et al. (2005). Predictors of mortality: an international comparison of socio-demographic and health characteristics from six longitudinal studies on aging: the CLESA project. Experimental Gerontology, 40, 89–99.CrossRefGoogle ScholarPubMed
Pointer, S., Harrison, J. and Bradley, C. (2003). National Injury Prevention Plan Priorities for 2004 and Beyond: Discussion Paper. Canberra, Australia: Australian Institute of Health and Welfare.Google Scholar
Rubenstein, L. Z. (2006). Falls in older people: epidemiology, risk factors and strategies for prevention. Age and Ageing, 35 (Suppl. 2), ii37–ii41.CrossRefGoogle ScholarPubMed
Rumpf, H. J. et al. (2001). Screening for mental health: validity of the MHI-5 using DSM-IV Axis I psychiatric disorders as gold standard. Psychiatry Research, 105, 243–253.CrossRefGoogle ScholarPubMed
Ryan, R. M. and Deci, E. L. (2001). On happiness and human potentials: a review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52, 141–166.CrossRefGoogle ScholarPubMed
Scott, H. (2005). Research shows how we can prevent falls in old age. British Journal of Nursing, 14, 245.CrossRefGoogle ScholarPubMed
Shumway-Cook, A. et al. (2009). Falls in the medicare population: incidence, associated factors, and impact on health care. Physical Therapy, 89, 324–332.CrossRefGoogle ScholarPubMed
Skapinakis, P. et al. (2005). Mental health inequalities in Wales, UK: multi-level investigation of the effect of area deprivation. British Journal of Psychiatry, 186, 417–422.CrossRefGoogle ScholarPubMed
Stevens, J. A. et al. (2006). The costs of fatal and non-fatal falls among older adults. Injury Prevention, 12, 290–295.CrossRefGoogle ScholarPubMed
Stevens, J. A. et al. (2008). Self-reported falls and fall-related injuries among persons aged ≫ 65 years–United States, 2006. Journal of Safety Research, 39, 345–349.CrossRefGoogle Scholar
Studenski, S. et al. (1994). Predicting falls: the role of mobility and nonphysical factors. Journal of the American Geriatrics Society, 42, 297–302.CrossRefGoogle ScholarPubMed
Tinetti, M. E. et al. (1988). Risk factors for falls among elderly persons living in the community. New England Journal of Medicine, 319, 1701–1707.CrossRefGoogle ScholarPubMed
Ware, J. E. Jr. and Gandek, B. (1998). Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. Journal of Clinical Epidemiology, 51, 903–912.CrossRefGoogle ScholarPubMed
Ware, J. E. Jr. et al. (1998). The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51, 1159–1165.CrossRefGoogle ScholarPubMed
Windsor, T. D. et al. (2006). Measuring physical and mental health using the SF-12: implications for community surveys of mental health. Australian and New Zealand Journal of Psychiatry, 40, 797–803.CrossRefGoogle ScholarPubMed
World Health Organization, Ageing and Life Course Unit (2008). WHO Global Report on Falls Prevention in Older Age. #9789241563536. Geneva: World Health Organization.Google Scholar
Yamazaki, S., Shunchi, F. and Green, J. (2005). Usefulness of five-item and three-item mental health inventories to screen for depressive symptoms in the general population of Japan. Health and Quality of Life Outcomes, 3, 48.CrossRefGoogle ScholarPubMed