Original Study| Volume 21, ISSUE 5, P669-674, May 2020

The Multidimensional Prognostic Index Predicts Falls in Older People: An 8-Year Longitudinal Cohort Study of the Osteoarthritis Initiative

Published:November 25, 2019DOI:



      Falls are associated with several negative outcomes. Early identification of those who are at risk of falling is of importance in geriatrics, and comprehensive geriatric assessment (CGA) seems to be promising in this regard. Therefore, the present study investigated whether the multidimensional prognostic index (MPI), based on a standard CGA, is associated with falls in the Osteoarthritis Initiative (OAI).


      Longitudinal, 8 years of follow-up.

      Setting and participants

      Community-dwelling older people (≥65 years of age) with knee osteoarthritis or at high risk for this condition.


      A standardized CGA including information on functional, nutritional, mood, comorbidities, medications, quality of life, and cohabitation status was used to calculate a modified version of the MPI, categorized as MPI-1 (low), MPI-2 (moderate), and MPI-3 (high risk). Falls were self-reported and recurrent fallers were defined as ≥2 in the previous year. Logistic regression was carried out and results are reported as odds ratio (ORs) with their 95% confidence intervals (CIs).


      The final sample consisted of 885 older adults (mean age 71.3 years, female = 54.6%). Recurrent fallers showed a significant higher MPI than their counterparts (0.46 ± 0.17 vs 0.38 ± 0.16; P < .001). Compared with those in MPI-1 category, participants in MPI-2 (OR 2.13; 95% CI 1.53‒2.94; P < .001) and in MPI-3 (OR 5.98; 95% CI 3.29-10.86; P < .001) reported a significant higher risk of recurrent falls over the 8-years of follow-up. Similar results were evident when using an increase in 0.1 points in the MPI or risk of falls after 1 year.

      Conclusions and implications

      Higher MPI values at baseline were associated with an increased risk of recurrent falls, suggesting the importance of CGA in predicting falls in older people.


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