The journal of nutrition, health & aging

, Volume 13, Issue 10, pp 881–889 | Cite as

Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force

  • Gabor Abellan Van Kan
  • Y. Rolland
  • S. Andrieu
  • J. Bauer
  • O. Beauchet
  • M. Bonnefoy
  • M. Cesari
  • L.M. Donini
  • S. Gillette-Guyonnet
  • M. Inzitari
  • F. Nourhashemi
  • G. Onder
  • P. Ritz
  • A. Salva
  • M. Visser
  • B. Vellas
Article

Abstract

Introduction

The use of a simple, safe, and easy to perform assessment tool, like gait speed, to evaluate vulnerability to adverse outcomes in community-dwelling older people is appealing, but its predictive capacity is still questioned. The present manuscript summarises the conclusions of an expert panel in the domain of physical performance measures and frailty in older people, who reviewed and discussed the existing literature in a 2-day meeting held in Toulouse, France on March 12–13, 2009. The aim of the IANA Task Force was to state if, in the light of actual scientific evidence, gait speed assessed at usual pace had the capacity to identify community-dwelling older people at risk of adverse outcomes, and if gait speed could be used as a single-item tool instead of more comprehensive but more time-consuming assessment instruments.

Methods

A systematic review of literature was performed prior to the meeting (Medline search and additional pearling of reference lists and key-articles supplied by Task Force members). Manuscripts were retained for the present revision only when a high level of evidence was present following 4 pre-selected criteria: a) gait speed, at usual pace, had to be specifically assessed as a single-item tool, b) gait speed should be measured over a short distance, c) at baseline, participants had to be autonomous, community-dwelling older people, and d) the evaluation of onset of adverse outcomes (i.e. disability, cognitive impairment, institutionalisation, falls, and/or mortality) had to be assessed longitudinally over time. Based on the prior criteria, a final selection of 27 articles was used for the present manuscript.

Results

Gait speed at usual pace was found to be a consistent risk factor for disability, cognitive impairment, institutionalisation, falls, and/or mortality. In predicting these adverse outcomes over time, gait speed was at least as sensible as composite tools.

Conclusions

Although more specific surveys needs to be performed, there is sufficient evidence to state that gait speed identifies autonomous community-dwelling older people at risk of adverse outcomes and can be used as a single-item assessment tool. The assessment at usual pace over 4 meters was the most often used method in literature and might represent a quick, safe, inexpensive and highly reliable instrument to be implemented.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Abellan van Kan G, Rolland Y, Bergman H, Morley JE, Kritchevsky SB and Vellas B. Frailty assessment of older people in clinical practice. Expert opinion of a Geriatric Advisory Panel. J Nutr Health Aging. 2007;12(1):29–37Google Scholar
  2. 2.
    Evans WJ. Functional outcomes for clinical trials in frail older persons. Time to be moving. J Gerontol Med Sci. 2008;63(2):160–164Google Scholar
  3. 3.
    Guralnik JM, Ferrucci L, Pieper CF et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the Short Physical Performance Battery. J Gerontol Med Sci. 2000;55(4):221–231Google Scholar
  4. 4.
    Lexell J. Evidence for nervous system degeneration with advancing age. J Nutr. 1997;127:1011–1013Google Scholar
  5. 5.
    Deshpande N, Ferrucci L, Metter J, et al. Association of lower limb cutaneous sensitivity with gait speed in the elderly: the health ABC study. Am J Phys Med Rehabil. 2008;87(11):921–928CrossRefPubMedGoogle Scholar
  6. 6.
    Lauretani F, Bandinelli S, Bartali B, et al. Axonal degeneration affects muscle density in older men and women. Neurobiol Aging. 2006;27:1145–1154CrossRefPubMedGoogle Scholar
  7. 7.
    Callisaya ML, Blizzard L, Schmidt MD, et al. A population based study of sensorimotor factors affecting gait in older people. Age Ageing. 2009;38(3):290–295CrossRefPubMedGoogle Scholar
  8. 8.
    Schmitz A, Silder A, Heiderscheit B, Mahoney J, Thelen DG. Differences in lowerextremity muscular activation during walking between healthy older and young adults. J Electromyogr Kinesiol. 2008; doi:10.1016/j.jelekin.2008.10.008Google Scholar
  9. 9.
    Rosano C, Aizenstein H, Brach J, et al. Gait measures indicate underlying focal gray matter atrophy in the brain of older adults. J Gerontol A Biol Sci Med Sci. 2008;63(12):1380–1388PubMedGoogle Scholar
  10. 10.
    Rosano C, Brach J, Longstreth Jr WT, Newman AB. Quantitative measures of gait characteristics indicate prevalence of underlying subclinical structural brain abnormalities in high-functioning older adults. Neuroepidemiology. 2006; 26(1):52–60CrossRefPubMedGoogle Scholar
  11. 11.
    Rosano C, Kuller LH, Chung H, et al. Sub clinical brain magnetic resonance imaging abnormalities predict physical functional decline in high-functioning older adults. J Am Geriatr Soc. 2005;53:649–654CrossRefPubMedGoogle Scholar
  12. 12.
    Baezner H, Blahak C, Poggesi A, et al. Association of gait and balance disorders with age-related white matter changes: the LADIS Study. Neurology. 2008; 70(12):935–942CrossRefGoogle Scholar
  13. 13.
    Misic MM, Rosengren KS, Woods JA, Evans EM. Muscle quality, aerobic fitness and fat mass predict lower-extremity physical function in community-dwelling older adults. Gerontology. 2007;53(5):260–266CrossRefPubMedGoogle Scholar
  14. 14.
    Pette D, Staron RS. Myosin isoforms muscle fibre types, and transitions. Microsc Res Tech. 2000;50:500–509CrossRefPubMedGoogle Scholar
  15. 15.
    Clémençon M, Hautier CA, Rahmani A, Cornu C, Bonnefoy M. Potential role of optimal velocity as a qualitative factor of physical functional performance in women aged 72 to 96 years. Arch Phys Med Rehabil. 2008;89(8):1594–1599CrossRefPubMedGoogle Scholar
  16. 16.
    Semba RD, Ferrucci L, Sun K, Walston J, Varadhan R, Guralnik JM, Fried LP. Oxidative stress and severe walking disability among older women. Am J Med. 2007;120(12):1084–1089CrossRefPubMedGoogle Scholar
  17. 17.
    Bassey EJ, Fiatarone MA, O’Neill EF, Kelly M, Evans WJ, Lipsitz LA: Leg extensors power and functional performance in very old men and women. Clin Sci. 1992;82:321–332PubMedGoogle Scholar
  18. 18.
    Von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology [STROBE] statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344–349CrossRefGoogle Scholar
  19. 19.
    Cesari M, Kritchevsky SB, Penninx BWHJ, et al. Pronostic value of usual gait speed in well-functioning older people. Results from the Health, Aging and Body Composition Study. J Am Geriatr Soc. 2005;53:1675–1680CrossRefPubMedGoogle Scholar
  20. 20.
    Cesari M, Kritchevsky SB, Newman AB, et al. Added value of physical performance measures in predicting adverse health-related events: results from the Health, Aging and Body Composition Study. J Am Geriatr Soc. 2009;57:251–259CrossRefPubMedGoogle Scholar
  21. 21.
    Rosano C, Newman AB, Katz R, et al. Association between lower digit symbol substitution test score and slower gait and greater risk of mortality and of developing incident disability in well-functioning older adults. J Am Geriatr Soc. 2008; 56:1618–1625CrossRefPubMedGoogle Scholar
  22. 22.
    Onder G, Penninx BWJ, Ferrucci L, et al. Measures of Physical performance and risk for progressive and catastrophic disability: results from the Women’s Health and Aging Study. J Gerontol Med Sci. 2005;60(1):74–79Google Scholar
  23. 23.
    Ostir GV, Markides KS, Black SA, Goodwin JS. Lower body function as a predictor of subsequent disability among older Mexican Americans. J Gerontol Med Sci. 1998;53(6):491–495Google Scholar
  24. 24.
    Studenski S, Perera S, Wallace D et al. Physical performance measures in the clinical setting. J Am Geriatr Soc. 2003;51:314–322CrossRefPubMedGoogle Scholar
  25. 25.
    Simonsick EM, Newman AB, Visser M, et al. Mobility limitations in self-described well-functioning older adults: importance of endurance walk test. J Gerontol Med Sci. 2008;63(8):841–847Google Scholar
  26. 26.
    Shinkai S, Watanabe S, Kumagai S et al. Walking speed as a good predictor for the onset of functional dependence in a Japanese rural community population. Age Ageing. 2000;29:441–446CrossRefPubMedGoogle Scholar
  27. 27.
    Woo J, Ho SC, Yu ALM. Walking speed and stride length predicts 36 months dependency, mortality, and hospitalisation in Chinese aged 70 and older. J Am Geriatr Soc. 1999;47:1257–1260PubMedGoogle Scholar
  28. 28.
    Ho SC, Woo J, Yuen YK, Chan SG. Predictors of mobility decline: the Hong-Kong Old Study. J Gerontol Med Sci. 1997;52(6):356–362Google Scholar
  29. 29.
    Alfaro-Acha A, Al Snih S, Raji MA et al. Does 8-foot walk time predict cognitive decline in older Mexicans Americans? J Am Geriatr Soc. 2007;55(2):245–251CrossRefPubMedGoogle Scholar
  30. 30.
    Inzitari M, Newman AB, Yaffe K, et al. Gait speed predicts decline in attention and psychomotor speed in older adults: The Health Aging and Body Composition Study. Neuroepidemiology. 2007;29:156–162CrossRefPubMedGoogle Scholar
  31. 31.
    Wang L, Larson EB, Bowen JD, van Belle G. Performance-based physical function and future dementia in older people. Arch Intern Med. 2006;166(10):1115–1120CrossRefPubMedGoogle Scholar
  32. 32.
    Waite LM, Grayson DA, Piguet O et al. Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study. J Neurol Sci. 2005;15:89–93CrossRefGoogle Scholar
  33. 33.
    Atkinson HH, Cesari M, Kritchevsky SB et al. Predictors of combined cognitive and physical decline. J Am Geriatr Soc. 2005;53:1197–1202CrossRefPubMedGoogle Scholar
  34. 34.
    Marquis S, Moore MM, Howieson DB et al. Independent predictors of cognitive decline in healthy elderly persons. Arch Neurol. 2002;59:601–606CrossRefPubMedGoogle Scholar
  35. 35.
    Camicioli R, Howieson D, Oken B, Sexton G, Kaye J. Motor slowing precedes cognitive impairment in the oldest old. Neurology. 1998;50:1496–1498PubMedGoogle Scholar
  36. 36.
    Ostir GV, Kuo YF, Berges IM, Markides KS, Ottenbacher KJ. Measures of lower body function and risk of mortality over 7 years of follow-up. Am J Epidemiol. 2007;166:599–605CrossRefPubMedGoogle Scholar
  37. 37.
    Cesari M, Onder G, Zamboni V et al. Physical function and self-rated status as predictors of mortality: results from longitudinal analysis in the ilSIRENTE study. BMC Geriatrics. 2008;8:34CrossRefPubMedGoogle Scholar
  38. 38.
    Rolland Y, Lauwers-Cances V, Cesari M, Vellas B, Pahor M, Grandjean H. Physical performance measures as predictors of mortality in a cohort of community-dwelling older French Women. Eur J Epid. 2006;21:113–122CrossRefGoogle Scholar
  39. 39.
    Markides KS, Black SA, Ostir GV, et al. Lower body function and mortality in Mexican American elderly people. J Gerontol Biol Sci Med Sci. 2001;56:243–247Google Scholar
  40. 40.
    Chamberlin ME, Fulwider BD, Sanders SL, and Medeiros JM. Does fear of falling influence spatial and temporal gait parameters in elderly persons beyond changes associated with normal aging? J Gerontol Biol Sci Med Sci. 2005;60(9):1163–1167Google Scholar
  41. 41.
    Balash Y, Hadar-Frumer M, Herman T, et al. The effects of reducing fear of falling on locomotion in older adults with a higher level gait disorder. J Neural Trasm. 2007;114:1309–1314CrossRefGoogle Scholar
  42. 42.
    Dargent-Molina P, Favier F, Grandjean H, et al. Fall-related factors and risk of hip fracture: the EPIDOS prospective study. Lancet. 1996:348:145–149CrossRefPubMedGoogle Scholar
  43. 43.
    Montero-Odasso M, Schapira M, Soriano ER, et al. Gait velocity as a single predictor of adverse events in healthy senior aged 75 years and older. J Gerontol Med Sci. 2005;60(10):1304–1309Google Scholar
  44. 44.
    Chu LW, Chi I, and Chiu AYY. Incidence and predictors of falls in the Chinese elderly. Ann Acad Med Singapore. 2005;34:60–72PubMedGoogle Scholar
  45. 45.
    Biderman A, Cwikel J, Fried AV, and Galisnky D. Depression and falls among community dwelling elderly people: a search for common risk factors. J Epidemiol Community Health. 2002;56:631–636CrossRefPubMedGoogle Scholar
  46. 46.
    Hardy SE, Perera S, Roumani YF, Chandler JM, Studenski SA. Improvement in usual gait speed predicts better survival in older adults. J Am Geriatr Soc. 2007;55:1727–1734CrossRefPubMedGoogle Scholar
  47. 47.
    Perera S, Studenski S, Chandler JM et al. Magnitude and patterns of decline in health and function in 1 year affect subsequent 5-year survival. J Gerontol A Biol Sci Med Sci. 2005;60:894–900PubMedGoogle Scholar
  48. 48.
    Guralnik JM, Ferrucci L, Simonsick EM et al. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med. 1995;332:556–561CrossRefPubMedGoogle Scholar
  49. 49.
    Rolland Y, Cesari M, Miller ME, Penninx BW, Atkinson HH and Pahor M. Reliability of the 400-m usual pace walk test as an assessment of mobility limitation in older adults. J Am Geriatr Soc. 2004;52:972–976CrossRefPubMedGoogle Scholar
  50. 50.
    Friedman PJ, Richmond DE, Baskett JJ. A prospective trial of serial gait speed as a measure of rehabilitation in the elderly. Age Ageing. 1988;17:227–235CrossRefPubMedGoogle Scholar
  51. 51.
    Rantanen T, Guralnik JM, Ferrucci L et al. Co-impairments as predictors of severe walking disability in older women. J Am Geriatr Soc. 2001;49:21–27CrossRefPubMedGoogle Scholar
  52. 52.
    Bohannon RW. Comfortable and maximum walking speed of adults aged 20–79 years: reference values and determinants. Age Ageing. 1997;26:15–19CrossRefPubMedGoogle Scholar

Copyright information

© Serdi and Springer Verlag France 2009

Authors and Affiliations

  • Gabor Abellan Van Kan
    • 1
    • 13
  • Y. Rolland
    • 1
    • 2
  • S. Andrieu
    • 2
    • 3
  • J. Bauer
    • 4
  • O. Beauchet
    • 5
  • M. Bonnefoy
    • 6
  • M. Cesari
    • 7
  • L.M. Donini
    • 8
  • S. Gillette-Guyonnet
    • 1
    • 2
  • M. Inzitari
    • 9
  • F. Nourhashemi
    • 1
    • 2
  • G. Onder
    • 10
  • P. Ritz
    • 11
  • A. Salva
    • 9
  • M. Visser
    • 12
  • B. Vellas
    • 1
    • 2
  1. 1.Gérontopôle, Department of Geriatric MedicineToulouse University HospitalToulouseFrance
  2. 2.INSERM U-558University Toulouse-IIIToulouseFrance
  3. 3.Department of Epidemiology and Public HealthUniversity Toulouse-IIIToulouseFrance
  4. 4.Department of Geriatric MedicineUniversity of Erlangen-NurembergNurnbergGermany
  5. 5.Department of Geriatric MedicineAngers University HospitalAngersFrance
  6. 6.Department of Geriatric MedicineCentre Hospitalier Lyon SudPierre-BeniteFrance
  7. 7.Department of Aging and Geriatric Reseach, Institute on AgingUniversity of FloridaGainesvilleUSA
  8. 8.Department of Medical Physiopathology“Sapienza” University of RomeRomeItaly
  9. 9.Institut Catala de l’EnvellimentUniversity Autonoma de BarcelonaBarcelonaSpain
  10. 10.Department of Geriatric MedicineCatholic University of Sacred HeartRomeItaly
  11. 11.Pole Cardiologie et Métabolique, Service d’EndocrinologieRangueil University HospitalToulouseFrance
  12. 12.Department of Health Sciences, Faculty of Earth and Life SciencesVrije Universiteit, and the EMGO Institute, VU University Medical CenterAmsterdamThe Netherlands
  13. 13.Gérontopôle, Department of Geriatric MedicineToulouse University HospitalToulouse, cedex 9France

Personalised recommendations