The adverse effects of drugs may influence results on tests of mobility and balance, but the drug-specific impact is not identified when using these tests. We propose that a quantitative drug index (QDI) will assist in assessing fall risk based on these tests, when combined with other fall risk variables.
Fifty-seven community-dwelling older adults who could walk independently on a treadmill and had Mini-Mental State Examination (MMSE) scores equal to or greater than 24 participated. Mobility and balance outcome measures included the Balance Evaluation Systems Test (BESTest), Berg Balance Scale (BBS), Timed Up and Go (TUG) and cognitive dual task TUG (TUGc). Fall history, current drug list, and Activity-Specific Balance Confidence (ABC) scale scores were also collected. Body mass index (BMI) was calculated. The QDI was derived from the drug list for each individual, and based on fall-related drug adverse effects. Multiple linear regression analyses were conducted using age, BMI, and QDI as predictor variables for determining mobility and balance test scores, and ABC scale scores. Subsequently, participants were divided into (QDI = 0) low-impact drug group (LIDG) and (QDI > 0) high-impact drug group (HIDG) for Mann-Whitney 2-group comparisons.
Age, BMI, and QDI were all significant (P < .001) independent variables in multiple regression analyses for mobility and balance test scores, but not for the ABC scale. Separately, the 2 group comparisons for the BESTest, BBS, TUG, and TUGc demonstrated that HIDG scored significantly (P < .05) worse on these tests compared with the LIDG. Drug counts were also significantly higher for the HIDG than for the LIDG. In contrast, age, BMI, MMSE, and reported falls in the last 12 months were not significantly different between groups.
Age, BMI, and QDI—all contributed independently to the mobility and balance test scores examined, and may provide health care professionals a screening tool to determine whether additional mobility and balance testing is required. In addition, the QDI is a more precise marker of adverse effects of drugs compared with drug counts, as the latter does not quantitate the influence of drugs on physiologic function.
1Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University, Baltimore, School of Medicine, Maryland.
2Departments of Kinesiology and Physical Therapy, Temple University, Philadelphia, Pennsylvania.
3Pharmacy Practice, Gatton College of Pharmacy, East Tennessee State University, Johnson City, Tennessee.
4Departments of Kinesiology and Bioengineering, Shriners Hospital for Children, Temple University, Philadelphia, Pennsylvania.
5Pharmaceutical Sciences, Gatton College of Pharmacy, East Tennessee State University, Johnson City, Tennessee.
Address correspondence to: Peter C. Panus, PT, PhD, Pharmaceutical Sciences, Gatton College of Pharmacy, Box 70657, East Tennessee State University, TN 37614 (firstname.lastname@example.org).
This study was partially supported by a Promotion of Doctoral Studies II scholarship from the Foundation for Physical Therapy, Inc, for Eric Anson. The study was also supported by the following NIH Grant 7R21AG041714 given to John Jeka.
The authors declare no conflicts of interest.
Bill Andrews was the Decision Editor.