Mobility and cognition are associated with wellbeing and health related quality of life among older adults: a cross-sectional analysis of the Vancouver Falls Prevention Cohort

BMC Geriatrics

Teresa Liu-Ambrose³  Kelly A. Vertes²  Caitlin Gomez²  Chun Liang Hsu³  John R. Best³  Linda C. Li⁴  Stirling Bryan¹  Jennifer C. Davis¹ 

[1] University of British Columbia, Vancouver V6T 2B5, BC, Canada;Aging, Mobility, and Cognitive Neuroscience Lab, 2211 Wesbrook Mall, Vancouver, Canada;Center for Hip Health and Mobility, 311-2647 Willow Street, Vancouver V5Z 1 M9, BC, Canada;Arthritis Research Centre of Canada, 5591 No. 3 Road, Richmond V6X 2C7, BC, Canada

关键词: Wellbeing;    Quality of life;    Cognition;    Mobility;   

Others  :  1218274
DOI  :  10.1186/s12877-015-0076-2

 received in 2014-09-23, accepted in 2015-06-23,  发布年份 2015

【 摘 要 】

Background

Ascertaining individuals’ quality of life and wellbeing is essential in public health and clinical research. The impact of these two pressing geriatric syndromes – impaired mobility and cognitive function -- on wellbeing and quality of life is not well examined. Hence, our objective was to identify key clinically relevant outcome measures of mobility and cognitive function that explain variation in wellbeing and health related quality of life (HRQoL) among community dwelling older adults.

Methods

We conducted a cross-sectional analysis of 229 participants presenting to the Vancouver Falls Prevention Clinic from June 2010 through October 2013. The linear regression models included two dependent variables: the ICECAP-O assessing wellbeing and the EQ-5D-3L assessing HRQoL. Key independent variables included the Short Performance Physical Battery (SPPB) and the Montreal Cognitive Assessment (MoCA). Covariates included Functional Comorbidity Index (FCI), sex and age. In the two multiple linear regression models, age was statistically controlled. Other covariates (i.e., sex and FCI) were included based on statistical significance (i.e., p < 0.05).

Results

The SPPB was significantly associated with HRQoL and with wellbeing after adjusting for known covariates (p < 0.05, Unstandardized ß (Standard Error) 0.023 (0.006) for HRQoL and 0.016 (0.003) for wellbeing). The MoCA was significantly associated with wellbeing after adjusting for known covariates (p = 0.006), Unstandardized ß (Standard Error) 0.005 (0.002) but not with health related quality of life (p > 0.05).

Conclusion

We found that a measure of mobility and balance was associated with HRQoL and wellbeing. However, cognitive function was associated with wellbeing only. This study highlights the potential importance of considering wellbeing as an outcome measure if interventions are intended to have a broader impact than health alone.

【 授权许可】

   
2015 Davis et al.

【 参考文献 】

• [1]Atkinson HH, Rosano C, Simonsick EM, Williamson JD, Davis C, Ambrosius WT, et al.: Cognitive function, gait speed decline, and comorbidities: the health, aging and body composition study. J Gerontol A Biol Sci Med Sci 2007, 62(8):844-850.
• [2]Brookmeyer R, Johnson E, Ziegler-Graham K, Arrighi H: Forecasting the global burden of Alzheimer's disease. Alzheimers Dement 2007, 3:186-191.
• [3]Buracchio T, Dodge HH, Howieson D, Wasserman D, Kaye J: The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol. 2010;67:980-86.
• [4]Burgess PW, Alderman N, Evans J, Emslie H, Wilson BA: The ecological validity of tests of executive function. J Int Neuropsychol Soc 1998, 4(6):547-558.
• [5]Coast J, Flynn TN, Natarajan L, Sproston K, Lewis J, Louviere JJ, et al.: Valuing the ICECAP capability index for older people. Soc Sci Med 2008, 67(5):874-882.
• [6]Coast J, Peters TJ, Natarajan L, Sproston K, Flynn T: An assessment of the construct validity of the descriptive system for the ICECAP capability measure for older people. Qual life res int j qual life asp treat care rehab 2008, 17(7):967-976.
• [7]Cotman CW, Berchtold NC, Christie LA: Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci 2007, 30(9):464-472.
• [8]Couzner L, Crotty M, Norman R, Ratcliffe J: A comparison of the EQ-5D-3L and ICECAP-O in an older post-acute patient population relative to the general population. Appl Health Econ Health Policy 2013, 11(4):415-425.
• [9]Couzner L, Ratcliffe J, Lester L, Flynn T, Crotty M: Measuring and valuing quality of life for public health research: application of the ICECAP-O capability index in the Australian general population. Int J Public Health 2013, 58(3):367-376.
• [10]Delbaere K, Close JC, Brodaty H, Sachdev P, Lord SR: Determinants of disparities between perceived and physiological risk of falling among elderly people: cohort study. BMJ. 2010;341:c4165.
• [11]Dolan P: Modeling valuations for EuroQol health states. Med Care 1997, 35(11):1095-1108.
• [12]Folstein MF, Folstein SE, McHugh PR: "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975, 12(3):189-198.
• [13]Giovannini S, Onder G, Liperoti R, Russo A, Carter C, Capoluongo E, Pahor M, Bernabei R, Landi F: Interleukin-6, C-reactive protein, and tumor necrosis factor-alpha as predictors of mortality in frail, community-living elderly individuals. J Am Geriatr Soc, 2011;59(9):1679–1685.
• [14]Groll DL, To T, Bombardier C, Wright JG: The development of a comorbidity index with physical function as the outcome. J Clin Epidemiol 2005, 58(6):595-602.
• [15]Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB: Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med 1995, 332(9):556-561.
• [16]Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB: Lower-Extremity Function in Persons over the Age of 70 Years as a Predictor of Subsequent Disability 10.1056/NEJM199503023320902. N Engl J Med 1995, 332(9):556-562.
• [17]ICECAP capability measures.. http://www.birmingham.ac.uk/research/activity/mds/projects/HaPS/HE/ICECAP/index.aspx webcite
• [18]Krabbe PF, Stouthard ME, Essink-Bot ML, Bonsel GJ: The effect of adding a cognitive dimension to the EuroQol multiattribute health-status classification system. J Clin Epidemiol 1999, 52(4):293-301.
• [19]Kuo H-K, Lipsitz LA: Cerebral White Matter Changes and Geriatric Syndromes: Is There a Link? J Gerontol A Biol Sci Med Sci 2004, 59(8):M818-M826.
• [20]Lord S, Clark R, Webster I: Physiological factors associated with falls in an elderly population. J Am Geriatr Soc 1991, 39:1194-1200.
• [21]Lord S, Sherrington C, Menz H: A physiological profile approach for falls prevention. In Falls in older people Risk factors and strategies for prevention. Cambridge University Press, Cambridge; 2001:221-238.
• [22]Lord S, Ward J, Williams P, Anstey K: Physiological factors associated with falls in older community-dwelling women. J Am Geriatr Soc 1994, 42:1110-1117.
• [23]Lorgelly PK, Lawson KD, Fenwick EA, Briggs AH: Outcome measurement in economic evaluations of public health interventions: a role for the capability approach? Int J Environ Res Public Health 2010, 7(5):2274-2289.
• [24]Marra CA, Esdaile JM, Guh D, Kopec JA, Brazier JE, Koehler BE, et al.: A comparison of four indirect methods of assessing utility values in rheumatoid arthritis. Med Care 2004, 42(11):1125-1131.
• [25]Morita M, Takamura N, Kusano Y, Abe Y, Moji K, Takemoto T, et al.: Relationship between falls and physical performance measures among community-dwelling elderly women in Japan. Aging Clin Exp Res 2005, 17(3):211-216.
• [26]Murray C, Lopez A: Global and regional descriptive epidemiology of disability: incidence, prevalence, health expectancies, and years lived with disability. In: The Global Burden of Disease and Risk Factors. Edited by Lopez AD, Mathers CD Ezzati M, Jamison DT, Murray CJL. Boston: The Harvard School of Public Health. 1996:201–246.
• [27]Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, et al.: The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 2005, 53(4):695-699.
• [28]Oh B, Cho B, Choi HC, Son KY, Park SM, Chun S, et al.: The influence of lower-extremity function in elderly individuals' quality of life (QOL): an analysis of the correlation between SPPB and EQ-5D. Arch Gerontol Geriatr 2014, 58(2):278-282.
• [29]Ravens-Sieberer U: Measuring and monitoring quality-of-life in population surveys: still a challenge for public health research. Soz Praventivmed 2002, 47(4):203-204.
• [30]Rosano C, Newman AB, Katz R, Hirsch CH, Kuller LH: 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(9):1618-1625.
• [31]Rowen D, Brazier J, Tsuchiya A, Alava MH: Valuing states from multiple measures on the same visual analogue sale: a feasibility study. Health Econ. 2012;21(6):715–29. doi:10.1002/hec.1740. Epub 2011 May 27.
• [32]Sen A: Commodities and capbilities. New Delhi; Commodities and Capabilities. 1987:1–46.
• [33]Sen A, Nussbaum M: Capability and well-being. Oxford University Press, Oxford; 1993.
• [34]Stuss DT, Alexander MP: Executive functions and the frontal lobes: a conceptual view. Psychol Res 2000, 63(3–4):289-298.
• [35]West RL: An application of prefrontal cortex function theory to cognitive aging. Psychol Bull 1996, 120(2):272-292.
• [36]Whitney JC, Lord SR, Close JC: Streamlining assessment and intervention in a falls clinic using the Timed Up and Go Test and Physiological Profile Assessments. Age Ageing 2005, 34(6):567-571.