Jennifer C Davis1,2,3,4,5, Chun Liang Hsu6,7,8,9,10, Cheyenne Ghag6,7,8, Samantha Y Starkey6,7,8,11, Patrizio Jacova6,7,8, Larry Dian11, Naaz Parmar12, Kenneth Madden12, Teresa Liu-Ambrose6,7,8. 1. Applied Health Economic Laboratory, Faculty of Management, University of British Columbia, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada. jennifer.davis@ubc.ca. 2. Aging, Mobility, and Cognitive Neuroscience Laboratory, Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada. jennifer.davis@ubc.ca. 3. Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada. jennifer.davis@ubc.ca. 4. Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada. jennifer.davis@ubc.ca. 5. Social & Economic Change Laboratory, Faculty of Management, University of British Columbia, Kelowna, BC, Canada. jennifer.davis@ubc.ca. 6. Aging, Mobility, and Cognitive Neuroscience Laboratory, Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada. 7. Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada. 8. Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada. 9. Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA, USA. 10. Harvard Medical School, Harvard University, Boston, MA, USA. 11. Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. 12. Department of Medicine, Division of Geriatric Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
Abstract
PURPOSE: Among older adults, health-related quality of life (HRQoL) and falls are associated. Generic patient-reported outcomes measures (PROMs) assess individual's HRQoL. The role for PROMs, a potential tool for predicting subsequent falls, remains under-explored. Our primary aim was to determine whether a baseline PROMs assessment of HRQoL may be a useful tool for predicting future falls. METHODS: A secondary analysis of a 12-month randomized clinical trial (RCT) of a home-based exercise program among 344 adults (67% female), aged ≥ 70 years, with ≥ 1 falls in the prior year who were randomized (1:1) to either a home-based exercise program (n = 172) or usual care (n = 172). A negative binomial regression model with total falls count as the dependent variable evaluated the main effect of the independent variable-baseline HRQoL (measured by the Short-Form-6D)-controlling for total exposure time and experiment group (i.e., exercise or usual care) for the total sample. For the usual care group alone, the model controlled for total exposure time. RESULTS: For the total sample, the rate of subsequent total falls was significantly predicted by baseline HRQoL (IRR = 0.044; 95% CI [0.005-0.037]; p = .004). For the usual care group, findings were confirmed with wider confidence intervals and the rate of prospective total falls was significantly predicted by baseline HRQoL (IRR = 0.025; 95% CI [0.001-0.909]; p = .044). CONCLUSION: These findings suggest the ShortForm-6D should be considered as part of falls prevention screening strategies within a Falls Prevention Clinic setting. Trial Registrations ClinicalTrials.gov Protocol Registration System. Identifier: NCT01029171; URL: https://clinicaltrials.gov/ct2/show/NCT01029171 . Identifier: NCT00323596; URL: https://clinicaltrials.gov/ct2/show/NCT00323596 .
PURPOSE: Among older adults, health-related quality of life (HRQoL) and falls are associated. Generic patient-reported outcomes measures (PROMs) assess individual's HRQoL. The role for PROMs, a potential tool for predicting subsequent falls, remains under-explored. Our primary aim was to determine whether a baseline PROMs assessment of HRQoL may be a useful tool for predicting future falls. METHODS: A secondary analysis of a 12-month randomized clinical trial (RCT) of a home-based exercise program among 344 adults (67% female), aged ≥ 70 years, with ≥ 1 falls in the prior year who were randomized (1:1) to either a home-based exercise program (n = 172) or usual care (n = 172). A negative binomial regression model with total falls count as the dependent variable evaluated the main effect of the independent variable-baseline HRQoL (measured by the Short-Form-6D)-controlling for total exposure time and experiment group (i.e., exercise or usual care) for the total sample. For the usual care group alone, the model controlled for total exposure time. RESULTS: For the total sample, the rate of subsequent total falls was significantly predicted by baseline HRQoL (IRR = 0.044; 95% CI [0.005-0.037]; p = .004). For the usual care group, findings were confirmed with wider confidence intervals and the rate of prospective total falls was significantly predicted by baseline HRQoL (IRR = 0.025; 95% CI [0.001-0.909]; p = .044). CONCLUSION: These findings suggest the ShortForm-6D should be considered as part of falls prevention screening strategies within a Falls Prevention Clinic setting. Trial Registrations ClinicalTrials.gov Protocol Registration System. Identifier: NCT01029171; URL: https://clinicaltrials.gov/ct2/show/NCT01029171 . Identifier: NCT00323596; URL: https://clinicaltrials.gov/ct2/show/NCT00323596 .
Authors: Jacqueline C T Close; Stephen R Lord; Evgeniya Jenya Antonova; Monique Martin; Benedikte Lensberg; Morag Taylor; Jamie Hallen; Ann Kelly Journal: Emerg Med J Date: 2011-10-01 Impact factor: 2.740
Authors: Wilma M Hopman; Claudie Berger; Lawrence Joseph; Tanveer Towheed; Elizabeth VandenKerkhof; Tassos Anastassiades; Jonathan D Adachi; George Ioannidis; Jacques P Brown; David A Hanley; Emmanuel A Papadimitropoulos Journal: Qual Life Res Date: 2006-04 Impact factor: 4.147