Abstract
Developing a model to predict mobility decline in community dwelling older people
Introduction
The maintenance of mobility is a priority for older people and is key to maintaining their independence. Declining mobility is an early predictor of loss of independence, reduced quality of life, increased health care use and death. The aim of this study was to develop and validate a prediction model to identify when an older person was at risk of self-reported mobility decline over a 2-year period.
Method
We used self-reported data from a prospective cohort study of 5,409 people aged 65 years and over in England (The Oxford Pain, Activity and Lifestyle (OPAL Cohort Study). Mobility status was assessed using the EQ-5D-5L mobility question. The outcome was any mobility decline at two years. Thirty-one candite variables were entered into the model included sociodemographic factors, pain, walking, falls, comorbidities, general health and physical activity. LASSO logistic regression was used to select predictors. Models were internally validated using bootstrapping. Scores were assigned to each identified predictor to calculate an individual’s risk of mobility decline.
Results:
Over 18% of participants who could walk reported mobility decline at year two.
The following variables were identified as predictors.
- Age
- Adequacy of income
- Body Mass Index
- Usual walking pace
- Difficulties maintaining balance
- Confidence to walk
- Use of walking aid
- Change in walking ability over 12 months
- Lower limb pain
- Current pain/discomfort severity
- Number of health conditions
- Physical tiredness
- Self-reported general health
- Current mobility level
Conclusions:
A prediction model for mobility decline was developed and internally validated. These questions could be used as an assessment tool within primary care or by older people themselves. External validation is required. We are working with stakeholders to understand how this model could be used to help older people maintain mobility.