Predicting the risk of mobility difficulty in older women with screening nomograms: the Women's Health and Aging Study II.
BACKGROUND
A major obstacle to screening for early mobility disability (ie, mobility difficulty), a major public health concern, is the lack of a method that identifies those who are at high risk. The goal of this study was to develop easy-to-use clinical nomograms for estimation of the probability of incident mobility difficulty.


METHODS
We conducted a population-based prospective study using data from 266 high physically and cognitively functioning older women, aged 70 to 80 years, who were free of mobility disability at the baseline evaluation of the Women's Health and Aging Study II. The outcome measure was incident mobility disability within 18 months, defined as self-reported difficulty walking 0.8 km, climbing 10 steps, or transferring from or into a car or bus. Logistic regression and receiver operating characteristic curve analyses were used for evaluation of the optimal combination of self-reported and performance-based mobility measures. Bootstrap sampling and estimation was used for validation.


RESULTS
Predictive nomograms were developed based on a final model that included 3 simple-to-obtain measures of preclinical disability: self-report of modification in mobility tasks without having difficulty with them, one-leg stance balance, and time to walk 1 m at a usual pace. Final model accuracy (as estimated by the area under the receiver operating characteristic curve) was 73% (SE = 0.04). Validation analysis confirmed the high accuracy of these nomograms.


CONCLUSIONS
An original tool was developed for assessment of the risk of mobility difficulty in older women that can be used to assist physicians and researchers in deciding which women to target for preventive interventions.
Chaves
P H
PH
Center on Aging and Health, The Johns Hopkins University School of Medicine, 2024 E Monument St, Suite 2-600, Baltimore, MD 21205-2223, USA. pchaves@jhsph.edu
Garrett
E S
ES
Fried
L P
LP
D000368:Aged; D000369:Aged, 80 and over; D004185:Disability Evaluation; D005260:Female; D015577:Geriatric Assessment; D006305:Health Status Indicators; D006801:Humans; D016015:Logistic Models; D010809:Physical Fitness; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D013647:Task Performance and Analysis