Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-25T04:58:29.189Z Has data issue: false hasContentIssue false

Longitudinal relationships between subjective fatigue, cognitive function, and everyday functioning in old age

Published online by Cambridge University Press:  19 October 2012

Feng Lin*
Affiliation:
School of Nursing, University of Rochester Medical Center, Rochester, New York, USA
Ding-Geng Chen
Affiliation:
School of Nursing, and Department of Biostatistics and Computational Biology, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York, USA
David E. Vance
Affiliation:
School of Nursing, and Edward R. Roybal Center for Translational Research on Aging and Mobility, University of Alabama at Birmingham, Birmingham, Alabama, USA
Karlene K. Ball
Affiliation:
Department of Psychology, and Edward R. Roybal Center for Translational Research on Aging and Mobility, University of Alabama at Birmingham, Birmingham, Alabama, USA
Mark Mapstone
Affiliation:
Department of Neurology, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York, USA
*
Correspondence should be addressed to: Feng Lin, School of Nursing, University of Rochester Medical Center, Helen Wood Hall, 601 Elmwood Avenue, Rochester, NY 14642. Phone: +585-276-6002; Fax: +585-273-1270. Email: [email protected].
Get access

Abstract

Background: The present study examined the prospective relationships between subjective fatigue, cognitive function, and everyday functioning.

Methods: A cohort study with secondary data analysis was conducted using data from 2,781 community-dwelling older adults without dementia who were enrolled to participate in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) randomized intervention trial. Measures included demographic and health information at baseline, and annual assessments of subjective fatigue, cognitive function (i.e. speed of processing, memory, and reasoning), and everyday functioning (i.e. everyday speed and everyday problem-solving) over five years.

Results: Four distinct classes of subjective fatigue were identified using growth mixture modeling: one group complaining fatigue “some of the time” at baseline but “most of the time” at five-year follow-up (increased fatigue), one complaining fatigue “a good bit of the time” constantly over time (persistent fatigue), one complaining fatigue “most of the time” at baseline but “some of the time” at five-year follow-up (decreased fatigue), and the fourth complaining fatigue “some of the time” constantly over time (persistent energy). All domains of cognitive function and everyday functioning declined significantly over five years; and the decline rates, but not the baseline levels, differed by the latent class of subjective fatigue. Except for the decreased fatigue class, there were different degrees of significant associations between the decline rates of subjective fatigue and all domains of cognitive function and everyday functioning in other classes of subjective fatigue.

Conclusion: Future interventions should address subjective fatigue when managing cognitive and functional abilities in community-dwelling older adults.

Type
Research Article
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

Alexander, N. B.et al. (2011). Bedside-to-Bench conference: research agenda for idiopathic fatigue and aging. Journal of the American Geriatrics Society, 58, 967975.CrossRefGoogle Scholar
American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th edn, Text Revision (DSM-IV-TR). Washington, DC: American Psychiatric Association.Google Scholar
Andreasen, A. K., Spliid, P. E., Andersen, H. and Jakobsen, J. (2011). Fatigue and processing speed are related in multiple sclerosis. European Journal of Neurology, 17, 212218.CrossRefGoogle Scholar
Avlund, K. (2010). Fatigue in older adults: an early indicator of the aging process? Aging Clinical and Experimental Research, 22, 100115.CrossRefGoogle ScholarPubMed
Ball, K., Beard, B., Roenker, D., Miller, R. and Griggs, D. (2000). Increasing mobility and reducing accidents of older drivers. In Schaie, K. and Pietrucha, M. (eds.), Mobility and Transportation in the Elderly (pp. 213251). New York: Springer.Google Scholar
Ball, K.et al. (2002). Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA, 288, 22712281.CrossRefGoogle ScholarPubMed
Bauer, D. J. and Curran, P. J. (2003). Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. Psychological Methods, 8, 338363.CrossRefGoogle ScholarPubMed
Bower, J. E.et al. (2012). Yoga for persistent fatigue in breast cancer survivors: a randomized controlled trial. Cancer, 118, 37663775.CrossRefGoogle ScholarPubMed
Boyle, P. A., Buchman, A. S., Wilson, R. S., Leurgans, S. E. and Bennett, D. A. (2011). Physical frailty is associated with incident mild cognitive impairment in community-based older persons. Journal of the American Geriatrics Society, 58, 248255.CrossRefGoogle Scholar
Brandt, J. (1991). The Hopkins Verbal Learning Test: development of a new memory test with six equivalent forms. Clinical Neuropsychologist, 5, 125142.CrossRefGoogle Scholar
Chaudhuri, A. and Behan, P. O. (2004). Fatigue in neurological disorders. Lancet, 363, 978988.CrossRefGoogle ScholarPubMed
Diehl, M., Willis, S. L. and Schaie, K. W. (1995). Everyday problem solving in older adults: observational assessment and cognitive correlates. Psychology and Aging, 10, 478491.CrossRefGoogle ScholarPubMed
Ekstrom, R., French, J., Harman, H. and Derman, D. (1976). Kit of Factor Referenced Cognitive Tests, Rev. edn, Princeton, NJ: Educational Testing Service.Google Scholar
Eldadah, B. A. (2011). Fatigue and fatigability in older adults. PM&R, 2, 406413.Google Scholar
Fotuhi, M., Hachinski, V. and Whitehouse, P. J. (2009). Changing perspectives regarding late-life dementia. Nature Reviews: Neurology, 5, 649658.Google ScholarPubMed
Gonda, J. and Schaie, K. (1985). Schaie-Thurstone Mental Abilities Test: Word Series Test. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Hagenaars, J. A. and McCutcheon, A. L. (2002). Applied Latent Class Analysis. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Holtzer, R. and Foley, F. (2009). The relationship between subjective reports of fatigue and executive control in multiple sclerosis. Journal of the Neurological Sciences, 281, 4650.CrossRefGoogle ScholarPubMed
Holtzer, R., Shuman, M., Mahoney, J. R., Lipton, R. and Verghese, J. (2011). Cognitive fatigue defined in the context of attention networks. Neuropsychology, Development, and Cognition, Section B: Aging, Neuropsychology and Cognition, 18, 108128.CrossRefGoogle ScholarPubMed
Huang, C. Q., Wang, Z. R., Li, Y. H., Xie, Y. Z. and Liu, Q. X. (2011). Cognitive function and risk for depression in old age: a meta-analysis of published literature. International Psychogeriatrics, 23, 516525.CrossRefGoogle ScholarPubMed
Jobe, J. B.et al. (2001). ACTIVE: a cognitive intervention trial to promote independence in older adults. Controlled Clinical Trials, 22, 453479.CrossRefGoogle ScholarPubMed
Jung, T. and Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2, 302317.CrossRefGoogle Scholar
Kaltsas, G., Vgontzas, A. and Chrousos, G. (2011). Fatigue, endocrinopathies and metabolic disorders. PM&R, 2, 393398.Google Scholar
Kelley, K. W.et al. (2003). Cytokine-induced sickness behavior. Brain, Behavior, and Immunity, 17, S112S118.CrossRefGoogle ScholarPubMed
Laditka, S. B.et al. (2009). Attitudes about aging well among a diverse group of older Americans: implications for promoting cognitive health. Gerontologist, 49, S30S39.CrossRefGoogle ScholarPubMed
Lin, F., Friedman, E., Quinn, J., Chen, D. and Mapstone, M. (2012). Effect of leisure activities on inflammation and cognitive function in an aging sample. Archives of Gerontology and Geriatrics, 54, 398404.CrossRefGoogle Scholar
Lou, J. S. (2009). Physical and mental fatigue in Parkinson's disease: epidemiology, pathophysiology and treatment. Drugs and Aging, 26, 195208.CrossRefGoogle ScholarPubMed
Marrie, R. A., Fisher, E., Miller, D. M., Lee, J.-C. and Rudick, R. A. (2005). Association of fatigue and brain atrophy in multiple sclerosis. Journal of the Neurological Sciences, 228, 161166.CrossRefGoogle ScholarPubMed
Melamed, S., Shirom, A., Toker, S., Berliner, S. and Shapira, I. (2006). Burnout and risk of cardiovascular disease: evidence, possible causal paths, and promising research directions. Psychological Bulletin, 132, 327353.CrossRefGoogle ScholarPubMed
Nylund, K. L., Asparouhov, T. and Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14, 535569.CrossRefGoogle Scholar
O'Connor, P. J. (2004). Evaluation of four highly cited energy and fatigue mood measures. Journal of Psychosomatic Research, 57, 435441.CrossRefGoogle ScholarPubMed
Ohno, Y.et al. (2011). The diagnostic value of endothelial function as a potential sensor of fatigue in health. Vascular Health and Risk Management, 6, 135144.Google Scholar
Owsley, C., Ball, K., Sloane, M. E., Roenker, D. L. and Bruni, J. R. (1991). Visual/cognitive correlates of vehicle accidents in older drivers. Psychology and Aging, 6, 403415.CrossRefGoogle ScholarPubMed
Owsley, C., Sloane, M., McGwinG., Jr. G., Jr. and Ball, K. (2002). Timed instrumental activities of daily living tasks: relationship to cognitive function and everyday performance assessments in older adults. Gerontology, 48, 254265.CrossRefGoogle ScholarPubMed
Panza, F.et al. (2011). Metabolic syndrome and cognitive impairment: current epidemiology and possible underlying mechanisms. Journal of Alzheimer's Disease, 21, 691724.CrossRefGoogle Scholar
Radloff, L. S. (1977). The CES-D Scale: a self-report depression scale for research in the general. Applied Psychological Measurement, 1, 385401.CrossRefGoogle Scholar
Rey, A. (1941). L'examen psychologique dans les cas d'encéphalopathie traumatique. Archives de Psychologie, 28, 215285.Google Scholar
Reyes-Gibby, C. C., Mendoza, T. R., Wang, S., Anderson, K. O. and Cleeland, C. S. (2003). Pain and fatigue in community-dwelling adults. Pain Medicine, 4, 231237.CrossRefGoogle ScholarPubMed
Thies, W. and Bleiler, L. (2011). Alzheimer's disease facts and figures. Alzheimers Dement, 7, 208244.Google Scholar
Thurstone, L. and Thurstone, T. (1949). Examiner Manual for the SRA Primary Mental Abilities Test (Form 1014). Chicago, IL: Science Research Associates.Google Scholar
Verdelho, A., Henon, H., Lebert, F., Pasquier, F. and Leys, D. (2004). Depressive symptoms after stroke and relationship with dementia: a three-year follow-up study. Neurology, 62, 905911.CrossRefGoogle ScholarPubMed
Vestergaard, S.et al. (2009). Fatigue in a representative population of older persons and its association with functional impairment, functional limitation, and disability. Journal of Gerontology, Series A: Biological Sciences and Medical Sciences, 64, 7682.CrossRefGoogle Scholar
Walker, E. A., Katon, W. J. and Jemelka, R. P. (1993). Psychiatric disorders and medical care utilization among people in the general population who report fatigue. Journal of General Internal Medicine, 8, 436440.CrossRefGoogle ScholarPubMed
Walston, J.et al. (2006). Research agenda for frailty in older adults: toward a better understanding of physiology and etiology: summary from the American Geriatrics Society/National Institute on Aging Research Conference on Frailty in Older Adults. Journal of the American Geriatrics Society, 54, 9911001.CrossRefGoogle Scholar
Ware, J. (2000). SF-36 Health Survey Manual and Interpretation Guide. Lincoln, NE: QualityMetric.Google Scholar
Ware, J. E. Jr and Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Medical Care, 30, 473483.CrossRefGoogle ScholarPubMed
West, B. T., Welch, K. B. and Galecki, A. T. (2007). Linear Mixed Models: A Practical Guide Using Statistical Software. Boca Raton, FL: CRC Press.Google Scholar
Wijeratne, C., Hickie, I. and Brodaty, H. (2007). The characteristics of fatigue in an older primary care sample. Journal of Psychosomatic Research, 62, 153158.CrossRefGoogle Scholar
Willis, S. and Marsiske, M. (1993). Manual for the Everyday Problems Test. University Park, PA: Pennsylvania State University.Google Scholar
Willis, S. L.et al. (2006). Long-term effects of cognitive training on everyday functional outcomes in older adults. JAMA, 296, 28052814.CrossRefGoogle ScholarPubMed
Wilson, B., Cockbum, J. and Baddeley, A. (1985). The River-Mead Behavioral Memory Test. Reading, UK: Thames Valley Test.Google Scholar
Yu, D. S., Lee, D. T. and Man, N. W. (2010). Fatigue among older people: a review of the research literature. International Journal of Nursing Studies, 47, 216228.CrossRefGoogle ScholarPubMed