Evaluating Accelerometry Thresholds for Detecting Changes in Levels of Moderate Physical Activity and Resulting Major Mobility Disability

Predicting physical functioning status in older adults: insights from wrist accelerometer sensors and derived digital biomarkers of physical activity

OBJECTIVE

Conventional physical activity (PA) metrics derived from wearable sensors may not capture the cumulative, transitions from sedentary to active, and multidimensional patterns of PA, limiting the ability to predict physical function impairment (PFI) in older adults. This study aims to identify unique temporal patterns and develop novel digital biomarkers from wrist accelerometer data for predicting PFI and its subtypes using explainable artificial intelligence techniques.

MATERIALS AND METHODS

Wrist accelerometer streaming data from 747 participants in the National Health and Aging Trends Study (NHATS) were used to calculate 231 PA features through time-series analysis techniques-Tsfresh. Predictive models for PFI and its subtypes (walking, balance, and extremity strength) were developed using 6 machine learning (ML) algorithms with hyperparameter optimization. The SHapley Additive exPlanations method was employed to interpret the ML models and rank the importance of input features.

RESULTS

Temporal analysis revealed peak PA differences between PFI and healthy controls from 9:00 to 11:00 am. The best-performing model (Gradient boosting Tree) achieved an area under the curve score of 85.93%, accuracy of 81.52%, sensitivity of 77.03%, and specificity of 87.50% when combining wrist accelerometer streaming data (WAPAS) features with demographic data.

DISCUSSION

The novel digital biomarkers, including change quantiles, Fourier transform (FFT) coefficients, and Aggregated (AGG) Linear Trend, outperformed traditional PA metrics in predicting PFI. These findings highlight the importance of capturing the multidimensional nature of PA patterns for PFI.

CONCLUSION

This study investigates the potential of wrist accelerometer digital biomarkers in predicting PFI and its subtypes in older adults. Integrated PFI monitoring systems with digital biomarkers would improve the current state of remote PFI surveillance.

Is Wrist Accelerometry Suitable for Threshold Scoring? A Comparison of Hip-Worn and Wrist-Worn ActiGraph Data in Low-Active Older Adults With Obesity

BACKGROUND

Hip- and wrist-worn ActiGraph accelerometers are widely used in research on physical activity as they offer an objective assessment of movement intensity across the day. Herein we characterize and contrast key structured physical activities and common activities of daily living via accelerometry data collected at the hip and wrist from a sample of community-dwelling older adults.

METHODS

Low-active, older adults with obesity (age 60+ years) were fit with an ActiGraph GT3X+ accelerometer on their nondominant wrist and hip before completing a series of tasks in a randomized order, including sitting/standing, sweeping, folding laundry, stair climbing, ambulation at different intensities, and cycling at different intensities. Participants returned a week later and completed the tasks once again. Vector magnitude counts/second were time-matched during each task and then summarized into counts/minute (CPM).

RESULTS

Monitors at both wear locations similarly characterized standing, sitting, and ambulatory tasks. A key finding was that light home chores (sweeping, folding laundry) produced higher and more variable CPM values than fast walking via wrist ActiGraph. Regression analyses revealed wrist CPM values were poor predictors of hip CPM values, with devices aligning best during fast walking (R2 = 0.25) and stair climbing (R2 = 0.35).

CONCLUSIONS

As older adults spend a considerable portion of their day in nonexercise activities of daily living, researchers should be cautious in the use of simply acceleration thresholds for scoring wrist-worn accelerometer data. Methods for better classifying wrist-worn activity monitor data in older adults are needed.

Intervening on exercise and daylong movement for weight loss maintenance in older adults: A randomized, clinical trial

OBJECTIVE

This study aimed to determine the impact of dietary weight loss (WL) plus aerobic exercise (EX) and a "move more, more often" approach to activity promotion (SitLess; SL) on WL and maintenance.

METHODS

Low-active older adults (age 65-86 years) with obesity were randomized to WL+EX, WL+SL, or WL+EX+SL. Participants received a social-cognitive group-mediated behavioral WL program for 6 months, followed by a 12-month maintenance period. EX participants received guided walking exercise with the goal of walking 150 min/wk. SL attempted to achieve a step goal by moving frequently during the day. The primary outcome was body weight at 18 months, with secondary outcomes including weight regain from 6 to 18 months and objectively assessed physical activity and sedentary behavior at each time point.

RESULTS

All groups demonstrated significant WL over 6 months (p < 0.001), with no group differences. Groups that received SL improved total activity time (p ≤ 0.05), and those who received EX improved moderate-to-vigorous activity time (p = 0.003). Over the 12-month follow-up period, those who received WL+EX demonstrated greater weight regain (5.2 kg; 95% CI: 3.5-6.9) relative to WL+SL (2.4 kg; 95% CI: 0.8-4.0).

CONCLUSIONS

Pairing dietary WL with a recommendation to accumulate physical activity contributed to similar WL and less weight regain compared with traditional aerobic exercise.

Relationships Between Profiles of Physical Activity and Major Mobility Disability in the LIFE Study

OBJECTIVES

To examine the relationship between time spent in light physical activity (LPA) and in moderate to vigorous physical activity (MVPA) and the pattern of accumulation on the risk for major mobility disability (MMD) in a large multicenter study of physical activity (PA) and aging, the Lifestyle Interventions and Independence for Elders (LIFE) study.

DESIGN

Data were collected from individuals randomized to a PA intervention as part of the LIFE study, an eight-center single-blind randomized clinical trial conducted between February 2010 and December 2013.

SETTING

Lifestyle Interventions and Independence for Elders Study PARTICIPANTS: Older adult participants (78.4 years; N = 507) at risk for MMD.

INTERVENTION

All older adults included in these analyses were randomized to a structured PA intervention that included two center-based plus three to four home-based exercise sessions per week with a primary goal of walking for 150 minutes weekly. Participants attended the intervention for 2.5 years on average.

MEASUREMENTS

MMD was defined as the inability to complete a 400-m walk within 15 minutes and without assistance. Physical function was assessed via the Short Physical Performance Battery (SPPB). Actigraph accelerometers were used to quantify amount and variability in LPA and MVPA.

RESULTS

In an adjusted Cox proportional hazards regression, we identified a significant interaction (P = .017) between SPPB score and LPA amount and variability such that more LPA was associated with a reduced risk for MMD among those with higher initial function, as was lower variability (eg, via distributing LPA across the day). The SPPB × MVPA interaction was significant (P = .04), such that more MVPA was associated with lower MMD risk among those with lower function. Finally, greater MVPA variability was associated with lower risk for MMD.

CONCLUSION

A prescription of PA for older adults should account for key factors such as physical function and emphasize both amount and pattern of accumulation of PA from across the intensity continuum. J Am Geriatr Soc 68:1476-1483, 2020.

Active-to-Sedentary Behavior Transitions, Fatigability, and Physical Functioning in Older Adults

BACKGROUND

With aging, daily physical activity (PA) becomes less frequent and more fragmented. Accumulation patterns of daily PA-including transitions from active-to-sedentary behaviors-may provide important insights into functional status in older, less active populations.

METHODS

Participants of the Baltimore Longitudinal Study of Aging (n = 680, 50% male, aged 27-94 years) completed a clinical assessment and wore an Actiheart accelerometer. Transitions between active and sedentary states were modeled as a probability (Active-to-Sedentary Transition Probability [ASTP]) defined as the reciprocal of the average PA bout duration. Cross-sectional associations between ASTP and gait speed (m/s), fatigability (rating-of-perceived-exertion [RPE]), 400 m time (seconds), and expanded short physical performance battery score were modeled using linear and logistic regression, adjusted for chronic conditions. Further analyses explored the utility of ASTP over-and-above total daily PA.

RESULTS

In continuous models, each 0.10-unit higher ASTP was associated slower gait (β = -0.06 m/s, SE = 0.01), higher fatigability (β = 0.60 RPE, SE = 0.12), slower 400 m time (β = 16.31 s, SE = 2.70), and lower functioning (β = -0.13 expanded short physical performance battery score, SE = 0.03; p < .001). In categorical analyses, those in the highest tertile of ASTP were >2 times more likely to have high fatigability (rating of perceived exertion ≥10), slow 400 m time (>300 seconds) and reduced functional performance (expanded short physical performance battery score < 3.07) than those in the lowest tertile (p < .01). Further analyses demonstrated ASTP provided additional insight into functional outcomes beyond total daily PA.

CONCLUSION

Fragmented daily PA-as measured by ASTP-is strongly linked with measures of health and functional status and may identify those at risk of high fatigability and reduced functional performance over and above traditional PA metrics.

Assessing physical performance and physical activity in large population-based aging studies: home-based assessments or visits to the research center?

Background

The current study aims to compare correlations between a range of measures of physical performance and physical activity assessing the same underlying construct in different settings, that is, in a home versus a highly standardized setting of the research center or accelerometer recording. We also evaluated the selective attrition of participants related to these different settings and how selective attrition affects the associations between variables and indicators of health, functioning and overall activity.

Methods

Cross-sectional analyses comprising population-based samples of people aged 75, 80, and 85 years living independently in Jyväskylä, Finland. The AGNES study protocol involved the following phases: 1) phone interview (n = 1886), 2) face-to-face at-home interview (n = 1018), 3) assessments in the research center (n = 910), and 4) accelerometry (n = 496). Phase 2 and 3 included walking and handgrip strength tests, and phase 4 a chest-worn and thigh-worn accelerometer estimating physical activity and assessing posture, respectively, for 3–10 days in free-living conditions.

Results

Older people with poorer health and functioning more likely refrained from subsequent study phases, each requiring more effort or commitment from participants. Paired measures of walking speed (R = 0.69), handgrip strength (R = 0.85), time in physical activity of at least moderate intensity (R = 0.42), and time in upright posture (R = 0.30) assessed in different settings correlated with each other, and they correlated with indicators of health, functioning and overall activity. Associations were robust regardless of limitations in health and functioning, and low overall activity.

Conclusions

Correlational analyses did not clearly reveal one superior setting for assessing physical performance or physical activity. Inclusion of older people with early declines in health, functioning and overall activity in studies on physical performance and physical activity is feasible in terms of study outcomes, but challenging for recruitment.

A comparison of accelerometry analysis methods for physical activity in older adult women and associations with health outcomes over time

This study compared five different methods for analyzing accelerometer-measured physical activity (PA) in older adults and assessed the relationship between changes in PA and changes in physical function and depressive symptoms for each method. Older adult females (N = 144, M_age = 83.3 ± 6.4yrs) wore hip accelerometers for six days and completed measures of physical function and depressive symptoms at baseline and six months. Accelerometry data were processed by five methods to estimate PA: 1041 vertical axis cut-point, 15-second vector magnitude (VM) cut-point, 1-second VM algorithm (Activity Index (AI)), machine learned walking algorithm, and individualized cut-point derived from a 400-meter walk. Generalized estimating equations compared PA minutes across methods and showed significant differences between some methods but not others; methods estimated 6-month changes in PA ranging from 4 minutes to over 20 minutes. Linear mixed models for each method tested associations between changes in PA and health. All methods, except the individualized cut-point, had a significant relationship between change in PA and improved physical function and depressive symptoms. This study is among the first to compare accelerometry processing methods and their relationship to health. It is important to recognize the differences in PA estimates and relationship to health outcomes based on data processing method. Abbreviation: Machine Learning (ML); Short Physical Performance Battery (SPPB); Center of Epidemiologic Studies Depression Scale (CES-D); Physical Activity (PA); Activity Index (AI); Activities of Daily Living (ADL).

Physical Activity Producing Low, but Not Medium or Higher, Vertical Impacts Is Inversely Related to BMI in Older Adults: Findings From a Multicohort Study

Background

High impact physical activity (PA) is thought to improve skeletal health, but its relation to other health outcomes are unclear. We investigated associations between PA impact magnitude and body mass index (BMI) in older adults.

Methods

Data were taken from the Cohort for Skeletal Health in Bristol and Avon (COSHIBA), Hertfordshire Cohort Study, and MRC National Survey of Health and Development. Vertical acceleration peaks from 7-day hip-worn accelerometer recordings were used to classify PA as low (0.5 < g < 1.0g), medium (1 < g < 1.5g), or higher (≥1.5g) impact. Cohort-specific associations of low, medium, and higher impact PA with BMI were examined using linear regressions and estimates combined using random-effects meta-analysis.

Results

A total of 1182 participants (mean age = 72.7 years, 68% female) were included. Low, medium, and higher impact PA were inversely related to BMI in initial models. After adjustment for confounders and other impacts, low, but not medium or higher, impacts were inversely related to BMI (-0.31, p < .001: overall combined standard deviation change in BMI per doubling in the number of low impacts). In adjusted analyses of body composition measured by dual-energy X-ray absorptiometry in COSHIBA, low, but not medium or higher, impacts were inversely related to total body fat mass (-0.19, p < .001) and android:gynoid fat mass ratio (-0.16, p = .01), whereas high impact PA was weakly and positively associated with lean mass (0.05, p = .06).

Conclusions

Greater exposure to PA producing low magnitude vertical impacts was associated with lower BMI and fat mass at older age. Low impact PA may help reduce obesity risk in older adults.