The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults - a multicentric cross-sectional study

Abstract

Background: The decline in everyday life physical activity reflects and contributes to the frailty syndrome. While especially self-reported frailty assessments have the advantage of reaching large groups at low costs, little is known about the relationship between the self-report and objective measured daily physical activity behavior. The main objective was to evaluate whether and to what extent a self-reported assessment of frailty is associated with daily physical activity patterns.

Methods: Daily activity data were obtained from 88 elderly participants (mean 80.6 ± 9.1 years) over up to 21 days. Acceleration data were collected via smartwatch. According to the results of a self-report frailty questionnaire, participants were retrospectively split up into three groups, F (frail, n = 43), P (pre-frail, n = 33), and R (robust, n = 12). Gait- and activity-related measures were derived from the built-in step detector and acceleration sensor and comprised, i.a., standard deviation of 5-s-mean amplitude deviation (MADstd), median MAD (MADmedian), and the 95th percentile of cadence (STEP95). Parameters were fed into a PCA and component scores were used to derive behavioral clusters.

Results: The PCA suggested two components, one describing gait and one upper limb activity. Mainly gait related parameters showed meaningful associations with the self-reported frailty score (STEP95: R² = 0.25), while measures of upper limb activity had lower coefficients (MADmedian: R² = 0.07). Cluster analysis revealed two clusters with low and relatively high activity in both dimensions (cluster 2 and 3). Interestingly, a third cluster (cluster 1) was characterized by high activity and low extent of ambulation. Comparisons between the clusters showed significant differences between activity, gait, age, sex, number of chronic diseases, health status, and walking aid. Particularly, cluster 1 contained a higher number of female participants, whose self-reports tended towards a low health status, the frequent use of a walking aid, and a higher score related to frailty questions.

Conclusions: The results demonstrate that subjective frailty assessments may be a simple first screening approach. However, especially older women using walking aids may classify themselves as frail despite still being active. Therefore, the results of self-reports may be particularly biased in older women.

Keywords: Accelerometry; Actigraphy; Ageing; Assessment; Frailty; Physical activity; Self-report.

Fig. 1

Graphical representation of the MAD-based activity parameters

Fig. 2

Flowchart of the recruitment procedure

Fig. 3

Kaplan Meier curve for measurement days per participants

Fig. 4

Correlation matrix (reporting the coefficient of determination R²) including all objective activity parameters, the subjective frailty scores, and the dimensions gait and activity derived from the confirmatory principal component analysis. Frailty 0:5, Frailty red. reduced frailty score 0:3, MADmean mean of all MAD values, MADstd standard deviation of all MAD values, MADrel relative amount time spend in MAD levels > 100 m-g, MADmedian median of all MAD values, MAD95 95th percentile of all MAD values, MADfrag standard deviation of the first derivate of the MAD time-series in milli-g, STEP95 95th percentile of cadence in steps per minute, STEPmean average number of steps taken per 5 s

Fig. 5

Both frailty scores (full 0:5, reduced 0:3) for the parameters STEP95 and MADmedian. STEP95 95th percentile of cadence, MADmedian median of all MAD values

Fig. 6

Individuals’ component scores in relation to ‘gait’ and ‘activity’ (left side) and in relation to age and self-reported frailty status (right)

Fig. 7

Mean scores of both self-reported frailty scores (full 0:5, reduced 0:3) between the three clusters