Amal A. Wanigatunga

Perceived Fatigability and Objective Physical Activity in Mid- to Late-Life

Background Fatigability, defined as fatigue in relation to a standardized task, predicts functional decline in older adults independent of reported tiredness or energy level. Although the sensation of fatigue, tiredness, and energy level adversely affect physical activity (PA), the association between fatigability and objectively measured PA is unknown. Methods Participants in the Baltimore Longitudinal Study of Aging (n = 557, 50% women, aged 50-97 years) were instructed to wear an Actiheart accelerometer for 7 consecutive days in the free-living environment. Perceived fatigability was assessed using the Borg rating of perceived exertion (RPE) after 5 minutes of treadmill walking at 1.5 mph (0.67 m/s) and categorized as low (6-7 RPE), intermediate (8-9 RPE), and high (10+ RPE) fatigability. Time-of-day PA differences between fatigability groups were assessed using mixed-effects modeling. Results Total daily PA was 1.3% lower for every unit increment in perceived fatigability after adjusting for demographic, behavioral, and medical factors (p = .01). In time-of-day analyses, the high fatigability group was less active compared to the low fatigability group throughout the day (8:00 am to 8:00 pm) and the intermediate fatigability group in the morning (8:00 am to 12:00 pm). Patterns of PA within the high fatigability group differed from both the intermediate and low groups in the morning but mirrored the intermediate group in the afternoon and evening. Discussion These results suggest that RPE is a bio-marker of fatigability associated with progressively lower PA with aging. Whether the effects of fatigability occurring at the end of the day reflect waning energy levels or a voluntary choice that could be modified remains to be evaluated.

Understanding physical activity in cancer patients and survivors: new methodology, new challenges, and new opportunities

Since the early 1990s, accumulating evidence has suggested that regular, sustained participation in physical activity may help prevent the onset and development of certain types of cancer. Given the worldwide incidence and prevalence of cancer, there is increasing interest in physical activity as a nonpharmacological intervention and prevention method. Moreover, the effectiveness of new and improved cancer therapies has also increased interest in the potential health benefits of physical activity during and after treatment. The development of wearable device technology (e.g., accelerometers) to monitor physical activity has created unprecedented opportunities to better understand the potential health benefits of physical activity in cancer patients and survivors by allowing researchers to observe, quantify, and define physical activity in real-world settings. This granular, detailed level of measurement provides the opportunity for researchers and clinicians to obtain a greater understanding of the health benefits of daily physical activity beyond the well-established benefits of “moderate-to-vigorous” physical activity and to tailor recommendations to a feasible level of activity for older and/or sicker patients and survivors. This article provides an overview of accelerometers, the potential benefits—and challenges—of using these devices in the research and clinical settings, and recommendations for future applications.

Effects of a Long-Term Physical Activity Program on Activity Patterns in Older Adults

Purpose To examine the effect of a long-term structured physical activity (PA) intervention on accelerometer-derived metrics of activity pattern changes in mobility-impaired older adults. Methods Participants were randomized to either a PA or health education (HE) program. The PA intervention included a walking regimen with strength, flexibility, and balance training. The HE program featured health-related discussions and a brief upper body stretching routine. Participants (n = 1341) wore a hip-worn accelerometer for ≥10 h·d−1 for ≥3 d at baseline and again at 6, 12, and 24 months postrandomization. Total PA (TPA)—defined as movements registering 100+ counts per minute—was segmented into the following intensities: low-light PA (LLPA; 100–759 counts per minute), high light PA (HLPA; 760–1040 counts per minute), low moderate PA (LMPA; 1041–2019 counts per minute), and high moderate and greater PA (HMPA; 2020+ counts per minute). Patterns of activity were characterized as bouts (defined as the consecutive minutes within an intensity). Results Across groups, TPA decreased an average of 74 min·wk−1 annually. The PA intervention attenuated this effect (PA = −68 vs HE: −112 min·wk−1, P = 0.002). This attenuation shifted TPA composition by increasing time in LLPA (10+ bouts increased 6 min·wk−1), HLPA (1+, 2+, 5+, and 10+ bouts increased 6, 3, 2, and 1 min·wk−1, respectively), LMPA (1+, 2+, 5+, and 10+ bouts increased: 19, 17,16, and 8 min·wk−1, respectively), and HMPA (1+, 2+, 5+, and 10+ bouts increased 23, 21, 17, and 14 min·wk−1, respectively). Conclusions The PA intervention increased PA by shifting the composition of activity toward higher-intensity activity in longer-duration bouts. However, a long-term structured PA intervention did not completely eliminate overall declines in total daily activity experienced by mobility-impaired older adults.

ROAMM: A software infrastructure for real-time monitoring of personal health

Mobile health (mHealth) based on smartphone and smartwatch technology is changing the landscape for how patients and research participants communicate about their health in real time. Flexible control of the different interconnected and frequently communicating mobile devices can provide a rich set of health care applications that can adapt dynamically to their environment. In this paper, we propose a real-time online activity and mobility monitoring (ROAMM) framework consisting of a smart-watch application for data collection, a server for data storage and retrieval as well as online monitoring and administrative tasks. We evaluated this framework to collect actigraphy data on the wrist and used it for feature detection and classification of different tasks of daily living conducted by participants. The information retrieved from the smartwatches yielded high accuracy for sedentary behavior prediction (accuracy = 97.44%) and acceptable performance for activity intensity level estimation (rMSE = 0.67 and R2 = 0.52).

Metabolic costs of daily activity in older adults (Chores XL) study: Design and methods

Background For over 20 years, normative data has guided the prescription of physical activity. This data has since been applied to research and used to plan interventions. While this data seemingly provides accurate estimates of the metabolic cost of daily activities in young adults, the accuracy of use among older adults is less clear. As such, a thorough evaluation of the metabolic cost of daily activities in community dwelling adults across the lifespan is needed. Methods The Metabolic Costs of Daily Activity in Older Adults Study is a cross-sectional study designed to compare the metabolic cost of daily activities in 250 community dwelling adults across the lifespan. Participants (20 + years) performed 38 common daily activities while expiratory gases were measured using a portable indirect calorimeter (Cosmed K4b2). The metabolic cost was examined as a metabolic equivalent value (O2 uptake relative to 3.5 mL min−1 kg−1), a function of work rate – metabolic economy, and a relative value of resting and peak oxygen uptake. Results The primary objective is to determine age-related differences in the metabolic cost of common lifestyle and exercise activities. Secondary objectives include (a) investigating the effect of functional impairment on the metabolic cost of daily activities, (b) evaluating the validity of perception-based measurement of exertion across the lifespan, and (c) validating activity sensors for estimating the type and intensity of physical activity. Conclusion Results of this study are expected to improve the effectiveness by which physical activity and nutrition is recommended for adults across the lifespan.

Longitudinal Relationship Between Interleukin-6 and Perceived Fatigability Among Well-Functioning Adults in Mid-to-Late Life

Background Chronically elevated interleukin-6 (IL-6) levels contribute to fatigue and functional decline via multiple pathways that often lead to frailty. Lesser known is the contribution of IL-6 to fatigue in relation to a standardized workload (fatigability), a precursor to functional decline. Therefore, the purpose of this study was to examine the longitudinal relationship between IL-6 and fatigability. Methods 985 participants from the Baltimore Longitudinal Study of Aging (mean age: 70+/-10 years) were evaluated every 1-4 years. IL-6 was measured in fasting serum samples at each visit and log-transformed for analyses. Perceived fatigability (PF) was defined as self-reported exertion (Rate of Perceived Exertion; RPE) after a 5-minute, 0.67 m/s, 0% grade treadmill walk. Continuous and categorical associations between IL-6 (baseline and repeated measures) and PF were assessed using generalized estimating equations, adjusting for demographics, behavioral factors, and comorbid conditions. Results In fully adjusted continuous models, 2-fold higher baseline IL-6 was associated with a 0.28 higher RPE (p=0.03). This relationship tended to remain constant annually (baseline log IL-6 by time interaction p=0.29). To provide clinical relevance, the sample median (3.7 pg/ml) was used to examine high versus low IL-6 levels. Over time, the high group reported an average 0.25 higher RPE (p=0.03) than the low group. Annual change in logged IL-6 was not associated with annual change in PF (p=0.48). Conclusion Findings suggest that elevated IL-6 is a biomarker of physiological dysregulation associated with greater fatigability, but there is no longitudinal association between IL-6 and fatigability. Future studies should evaluate whether interventions that aim to reduce inflammation also attenuate fatigability.

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.

Transition Icons for Time-Series Visualization and Exploratory Analysis

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets—postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

Community-based activity and sedentary patterns are associated with cognitive performance in mobility-limited older adults

Over the last few decades, considerable evidence shows that greater levels of aerobic exercise and cardiovascular fitness benefit cognitive performance. However, the degree to which free-living activity in community settings is related to cognitive performance remains unclear, particularly in older adults vulnerable to disability. Also, it is unknown whether the manner in which daily physical activity (PA) and sedentary time are accumulated throughout the day is associated with cognition. Cross-sectional associations between accelerometer-characterized PA and sedentary patterns and cognitive performance were examined in 1,274 mobility-limited older adults. Percent time spent in various bout lengths of PA (≥1, ≥2, and ≥5 min) and sedentary (≥1, ≥30, and ≥60 min) was defined as the number of minutes registered divided by total wear time × 100. Percent time was then tertiled for each bout length. Multiple linear regression models were used to estimate the associations between accelerometer bout variables and separate cognitive domains that included processing speed (Digit Symbol Coding; DSC), immediate and delayed recall (Hopkins Verbal Learning Test; HVLT), information processing and selective attention (Flanker), working memory (n-back), reaction time (switch and non-switch reaction time), and a composite score that averaged results from all cognitive tests. After adjusting for demographics, behavioral factors, and morbid conditions, more time spent in PA was associated with higher DSC for all bout lengths (p < 0.03 for all). Higher PA was associated with higher HVLT and global cognition scores but only for longer bout lengths (p < 0.05 for all). The association was largely driven by participants who spent the lowest amount of time performing activity while awake (p < 0.04). An inverse linear relationship was observed between total sedentary time and DSC (p = 0.02), but not for other measures of cognition. These results suggest that, while higher PA was associated with higher cognitive performance, PA’s association with memory was sensitive to bout duration. The time, but not the manner, spent in sedentary behaviors showed a minor association with executive function. Further research is warranted to characterize longitudinal changes in daily activity and sedentary patterns as potential biophysical markers of cognitive status in older adults.

Contrasting characteristics of daily physical activity in older adults by cancer history

Using objectively collected physical activity (PA) data from the Baltimore Longitudinal Study of Aging, the authors tested whether patterns of daily activity and sedentary time differed by cancer survivorship in older adults.