Applying the International Classification of Functioning, Disability and Health framework to determine the predictors of falls and fractures in people with osteoarthritis or at high risk of developing osteoarthritis: data from the Osteoarthritis Initiative
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Soh, Sze-Ee
[1
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Barker, Anna L.
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Monash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, Australia
Medibank Private Ltd, 720 Bourke St, Melbourne, Vic 3008, AustraliaMonash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, Australia
Barker, Anna L.
[1
,3
]
Morello, Renata T.
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Monash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, AustraliaMonash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, Australia
Morello, Renata T.
[1
]
Ackerman, Ilana N.
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Monash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, AustraliaMonash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, Australia
Ackerman, Ilana N.
[1
]
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[1] Monash Univ, Dept Epidemiol & Prevent Med, 553 St Kilda Rd, Melbourne, Vic 3004, Australia
Background Falls are a major cause of injury and death among older people. Evidence suggests that people with osteoarthritis (OA) are at a higher risk of falls and fall-related injuries including fractures. While studies demonstrate a link between OA and falls, little is known about the pathways that link falls with demographic factors, OA impairments, activity limitations and participation restrictions. The aim of this study was to identify risk factors for falls and fractures among people with OA or at high risk of developing OA using the International Classification of Functioning, Disability and Health (ICF) framework. Methods A longitudinal analysis of data from the Osteoarthritis Initiative (OAI) dataset was undertaken. Participants were considered to have OA if they reported they had been diagnosed with knee or hip OA by a medical practitioner. Outcomes were self-reported falls and fractures. Potential predictors were classified using the ICF framework. Poisson regression models were used to determine the risk factors for falls and fractures. Results Of the 4796 participants, 2270 (47%) were diagnosed with knee and/or hip OA. A higher proportion of participants with OA reported having had falls (72% vs 63%; p < 0.0001) and fractures (17% vs 14%; p = 0.012) than those without OA. Personal factors were found to be stronger predictors of falls and fractures compared to OA impairments, activity limitations and participation restrictions in this sample of participants. After adjusting for potential covariates, self-reported history of falls was a significant predictor of both increased falls (incidence rate ratio [IRR] 1.50; 95% confidence interval [CI] 1.40, 4.60) and fracture risk (IRR 1.38; 95% CI 1.13, 1.69). Conclusions By applying the ICF framework, we have shown that personal factors were more likely to predict falls and fractures rather than OA impairments, environmental factors, activity limitations and participation restrictions in people with OA or at high risk of developing OA. This highlights the importance of questioning patients about their previous falls and past medical history, and using this information to focus our assessment and clinical decision-making processes.
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Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Ludwig Boltzmann Inst Arthrit & Rehabil, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Stefanac, Sinisa
Oppenauer, Claudia
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Karl Landsteiner Private Univ Hlth Sci, Krems, Lower Austria, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Oppenauer, Claudia
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Zauner, Michael
Durechova, Martina
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Med Univ Vienna, Clin Dept Rheumatol, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Durechova, Martina
Dioso, Daffodil
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Med Univ Vienna, Clin Dept Rheumatol, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Dioso, Daffodil
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Aletaha, Daniel
Hobusch, Gerhard
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Med Univ Vienna, Dept Orthopaed, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Hobusch, Gerhard
Windhager, Reinhard
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Med Univ Vienna, Dept Orthopaed, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Windhager, Reinhard
Stamm, Tanja
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Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
Ludwig Boltzmann Inst Arthrit & Rehabil, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Outcomes Res, Vienna, Austria
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Boston Univ, Dept Radiol, Quantitat Imaging Ctr, Sch Med, Boston, MA USA
Boston Imaging Core Lab LLC, Boston, MA USA
VA Boston Hlth care Syst, Dept Radiol, Boston, MA USASalzburg Univ, Inst Anat & Cell Biol, Paracelsus Med, Dept Imaging & Funct Musculoskeletal Res, Salzburg, Austria
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Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China
Chen, Tianrong
Or, Calvin Kalun
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Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China
Univ Hong Kong, Dept Ind & Mfg Syst Engn, Room 8-7,8-F,Haking Wong Bldg, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China
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Univ E Anglia, Sch Hlth Sci, Fac Med & Hlth Sci, Norwich Res Pk,Queens Bldg, Norwich NR4 7TJ, Norfolk, EnglandUniv E Anglia, Sch Hlth Sci, Fac Med & Hlth Sci, Norwich Res Pk,Queens Bldg, Norwich NR4 7TJ, Norfolk, England
Smith, T. O.
Pearson, M.
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Hinchingbrooke Hosp, Cambridgeshire Community Serv, Huntingdon, Cambs, EnglandUniv E Anglia, Sch Hlth Sci, Fac Med & Hlth Sci, Norwich Res Pk,Queens Bldg, Norwich NR4 7TJ, Norfolk, England
Pearson, M.
Latham, S. K.
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St George Hosp, London, EnglandUniv E Anglia, Sch Hlth Sci, Fac Med & Hlth Sci, Norwich Res Pk,Queens Bldg, Norwich NR4 7TJ, Norfolk, England