Relating wrist accelerometry measures to disability in older adults

A Voice-Activated Device Exercise and Social Engagement Program for Older Adult-Care Partner Dyads: Pilot Clinical Trial and Focus Group Study Evaluating the Feasibility, Use, and Estimated Functional Impact of EngAGE

BACKGROUND

Maintaining exercise is essential for healthy aging but difficult to sustain. EngAGE is a socially motivated exercise program delivered over a voice-activated device that targets older adult-care partner dyads.

OBJECTIVE

This 10-week pilot study aimed to assess EngAGE feasibility and use, obtain user experience feedback, and estimate potential impact on function.

METHODS

In total, 10 older adults aged ≥65 years were recruited from an independent living residence together with their self-identified care partners. EngAGE delivered National Institute on Aging Go4Life exercises to older adults daily, while care partners received progress reports and prompts to send encouraging messages that were read aloud by the device to the older adult. Older adults' use was tracked, and physical function was assessed at baseline and follow-up. Follow-up focus group data provided qualitative feedback.

RESULTS

On average, participants completed 393.7 individual exercises over the 10-week intervention period or 39.4 exercises/wk (range 48-492, median 431, IQR 384-481, SD 112.4) without injury and used EngAGE on an average of 41 of 70 days or 4.1 d/wk (range 7-66, median 51, IQR 23-56, and SD 21.2 days). Mean grip strength increased nonsignificantly by 1.3 kg (preintervention mean 26.3 kg, SD 11.0; postintervention mean 27.6 kg, SD 11.6; P=.34), and 4 of 10 participants improved by a minimal clinically important difference (MCID) of 2.5 kg. Further, the time for 5-repeated chair stands significantly reduced by 2.3 seconds (preintervention mean 12, SD 3.6 s; postintervention mean 9.7, SD 2.7 s; P=.02), and 3 of 9 participants improved by an MCID of -2.3 seconds. Furthermore, 3-meter usual walk performance was brisk at baseline (mean 2.1, SD 0.4 s) and decreased by 0.1 seconds (postintervention 2, SD 0.4 s; P=.13), although 5 of 9 participants improved by a MCID of 0.05 m/s. Qualitative results showed perceived benefits, favored program features, and areas for improvement.

CONCLUSIONS

We present a pilot study of a new voice-activated device application customized to older adult users that may serve as a guide to other technology development for older adults. Our pilot study served to further refine the application and to inform a larger trial testing EngAGE's impact on functional outcomes, a necessary step for developing evidence-based technology tools.

Daily Electronic Media Use and Sleep in Late Life

OBJECTIVES

Daily electronic media use, including television viewing and computer use, is common in older adulthood. Yet, increased electronic media usage may disrupt nightly sleep, leading to sleeping fewer hours and more sleep disruptions. The current study examined these relationships in older adulthood, as well as the potential buffering effect of having a regular sleep schedule.

METHODS

Older adults (N = 273) from the Daily Experiences and Well-Being Study (DEWS) completed 5-6 days of data collection where they answered questions at the beginning of the day about the previous night's sleep as well as questions throughout the day about daily electronic media use. They also wore Actical accelerometers to capture sleep regularity.

RESULTS

Older adults reported sleeping fewer hours and having more sleep disturbances on days when they reported more instances of computer use. Sleep regularity moderated the daily association between TV viewing and sleep disturbances such that daily TV viewing was associated with more sleep complaints only for older adults who had less regular sleep patterns. However, sleep regularity no longer moderated this association when accounting for napping behavior.

DISCUSSION

These findings provide evidence that older adults sleep worse after days when they engage in more electronic media use. The association with TV viewing with sleep disturbances on any given day is somewhat mitigated by engaging in regular sleep patterns. Researchers discuss the importance of assessing electronic media use and sleep in daily life as the role of sleep regularity may be a modifiable protective factor.

Physical Activity and Daily Stress Processes in Older Adulthood

OBJECTIVES

Older adults who are physically active report lower levels of stress. Less is known about the links between physical activity and exposure and reactivity to stressful events in daily life. The current study examined within-person associations between actigraphy-assessed daily physical activity and exposure and affective reactivity to naturally occurring interpersonal stressors.

METHOD

Older adults (N = 180) from the Daily Experiences and Well-being Study completed ecological momentary assessments (EMAs) every 3 hr for 5-6 days where they reported negative affect throughout the day and interpersonal tensions at the end of the day. They also wore Actical accelerometers to capture physical activity.

RESULTS

Older adults reported greater numbers of interpersonal stressors on days when they spent less time being sedentary and engaged in more light physical activity. On days when older adults experienced more interpersonal stressors, they reported higher levels of negative affect, but this association was attenuated when they were more physically active that day.

DISCUSSION

Physical activity may bolster older adults' capabilities to manage affective responses to interpersonal stressors in a more successful way. These findings underscore the importance of assessing physical activity and stressful events in daily life and have implications for both physical and psychological well-being.

Gait Detection from a Wrist-Worn Sensor Using Machine Learning Methods: A Daily Living Study in Older Adults and People with Parkinson's Disease

Remote assessment of the gait of older adults (OAs) during daily living using wrist-worn sensors has the potential to augment clinical care and mobility research. However, hand movements can degrade gait detection from wrist-sensor recordings. To address this challenge, we developed an anomaly detection algorithm and compared its performance to four previously published gait detection algorithms. Multiday accelerometer recordings from a wrist-worn and lower-back sensor (i.e., the “gold-standard” reference) were obtained in 30 OAs, 60% with Parkinson’s disease (PD). The area under the receiver operator curve (AUC) and the area under the precision−recall curve (AUPRC) were used to evaluate the performance of the algorithms. The anomaly detection algorithm obtained AUCs of 0.80 and 0.74 for OAs and PD, respectively, but AUPRCs of 0.23 and 0.31 for OAs and PD, respectively. The best performing detection algorithm, a deep convolutional neural network (DCNN), exhibited high AUCs (i.e., 0.94 for OAs and 0.89 for PD) but lower AUPRCs (i.e., 0.66 for OAs and 0.60 for PD), indicating trade-offs between precision and recall. When choosing a classification threshold of 0.9 (i.e., opting for high precision) for the DCNN algorithm, strong correlations (r > 0.8) were observed between daily living walking time estimates based on the lower-back (reference) sensor and the wrist sensor. Further, gait quality measures were significantly different in OAs and PD compared to healthy adults. These results demonstrate that daily living gait can be quantified using a wrist-worn sensor.

Exploring Shared Effects of Multisensory Impairment, Physical Dysfunction, and Cognitive Impairment on Physical Activity: An Observational Study in a National Sample

Multisensory, physical, and cognitive dysfunction share age-related physiologic disturbances and may have common health effects. We determined whether the effect of multisensory impairment on physical activity (PA) is explained by physical (timed up and go) or cognitive (Short Portable Mental Status Questionnaire) dysfunction. A National Social Life, Health, and Aging Project participant subset (n = 507) underwent objective sensory testing in 2005-2006 and wrist accelerometry in 2010-2011. We related multisensory impairment to PA using multivariate mixed-effects linear regression and compared the effect magnitude after adjusting for physical then cognitive dysfunction. Worse multisensory impairment predicted lower PA across three scales (Global Sensory Impairment: β = -0.04, 95% confidence interval [-0.07, -0.02]; Total Sensory Burden: β = -0.01, 95% confidence interval [-0.03, -0.003]; and Number of Impaired Senses: β = -0.02, 95% confidence interval [-0.04, -0.004]). Effects were similar after accounting for physical and cognitive dysfunction. Findings suggest that sensory, physical, and cognitive dysfunction have unique mechanisms underlying their PA effects.

Free-living wrist and hip accelerometry forecast cognitive decline among older adults without dementia over 1- or 5-years in two distinct observational cohorts

The prevalence of major neurocognitive disorders is expected to rise over the next 3 decades as the number of adults ≥65 years old increases. Noninvasive screening capable of flagging individuals most at risk of subsequent cognitive decline could trigger closer monitoring and preventive strategies. In this study, we used free-living accelerometry data to forecast cognitive decline within 1- or 5-years in older adults without dementia using two cohorts. The first cohort, recruited in the south side of Chicago, wore hip accelerometers for 7 continuous days. The second cohort, nationally recruited, wore wrist accelerometers continuously for 72 h. Separate classifier models forecasted 1-year cognitive decline with over 85% accuracy using hip data and forecasted 5-year cognitive decline with nearly 70% accuracy using wrist data, significant improvements compared to demographics and comorbidities alone. The proposed models are readily translatable to clinical practices serving ageing populations.

Daily Physical Activity Patterns as a Window on Cognitive Diagnosis in the Baltimore Longitudinal Study of Aging (BLSA)

BACKGROUND

Gradual disengagement from daily physical activity (PA) could signal present or emerging mild cognitive impairment (MCI) or Alzheimer's disease (AD).

OBJECTIVE

This study examined whether accelerometry-derived patterns of everyday movement differ by cognitive diagnosis in participants of the Baltimore Longitudinal Study of Aging (BLSA).

METHODS

Activity patterns, overall and by time-of-day, were cross-sectionally compared between participants with adjudicated normal cognition (n = 549) and MCI/AD diagnoses (n = 36; 5 participants [14%] living with AD) using covariate-adjusted regression models.

RESULTS

Compared to those with normal cognition, those with MCI/AD had 2.1% higher activity fragmentation (SE = 1.0%, p = 0.036) but similar mean total activity counts/day (p = 0.075) and minutes/day spent active (p = 0.174). Time-of-day analyses show MCI/AD participants had lower activity counts and minutes spent active during waking hours (6:00 am-5:59 pm; p < 0.01 for all). Also, they had lower activity fragmentation from 12:00-5:59 am (p < 0.001), but higher fragmentation from 12:00-5:59 pm (p = 0.026).

CONCLUSION

Differences in the timing and patterns of physical activity throughout the day linked to MCI/AD diagnoses warrant further investigation into potential clinical utility.

Wrist-Worn Accelerometry, Aging, and Gait Speed in the Baltimore Longitudinal Study of Aging

Wrist-worn accelerometry metrics are not well defined in older adults. Accelerometry data from 720 participants (mean age 70 years, 55% women) were summarized into (a) total activity counts per day, (b) active minutes per day, (c) active bouts per day, and (d) activity fragmentation (the reciprocal of the mean active bout length). Linear regression and mixed-effects models were utilized to estimate associations between age and gait speed with wrist accelerometry. Activity counts per day, daily active minutes per day, and active bouts per day were negatively associated with age among all participants, while positive associations with activity fragmentation were only observed among those ≥65 years. More activity counts, more daily active minutes, and lower activity fragmentation were associated with faster gait speed. There were baseline age interactions with annual changes in total activity counts per day, active minutes per day, and activity fragmentation (Baseline age × Time, p < .01 for all). These results help define and characterize changes in wrist-based physical activity patterns among older adults.

The Association of Objectively Measured Physical Activity and Sedentary Behavior with (Instrumental) Activities of Daily Living in Community-Dwelling Older Adults: A Systematic Review

Up to 60% of older adults have a lifestyle characterized by low physical activity (PA) and high sedentary behavior (SB). This can amplify age-related declines in physical and cognitive functions and may therefore affect the ability to complete basic and instrumental activities of daily living (ADL and IADL, respectively), which are essential for independence. This systematic review aims to describe the association of objectively measured PA and SB with ADL and IADL in community-dwelling older adults. Six databases (PubMed, Embase, the Cochrane library, CINAHL, PsychINFO, SPORTDiscuss) were searched from inception to 21/06/2020 for articles meeting our eligibility criteria: 1) observational or experimental study, 2) participants’ mean/median age ≥60 years, 3) community-dwelling older adults, 4) PA and SB were measured with a(n) accelerometer/pedometer, 5) PA and SB were studied in relation to ADL and/or IADL. Risk of bias was assessed in duplicate using modified versions of the Newcastle–Ottawa scale. Effect direction heat maps provided an overview of associations and standardized regression coefficients (βs) were depicted in albatross plots. Thirty articles (6 longitudinal; 24 cross-sectional) were included representing 24,959 (range: 23 to 2749) community-dwelling older adults with mean/median age ranging from 60.0 to 92.3 years (54.6% female). Higher PA and lower SB were associated with better ability to complete ADL and IADL in all longitudinal studies and overall results of cross-sectional studies supported these associations, which underscores the importance of an active lifestyle. The median [interquartile range] of βs for associations of PA/SB with ADL and IADL were, respectively, 0.145 [0.072, 0.280] and 0.135 [0.093, 0.211]. Our strategy to address confounding may have suppressed the true relationship of PA and SB with ADL or IADL because of over-adjustment in some included studies. Future research should aim for standardization in PA and SB assessment to unravel dose–response relationships and inform guidelines.

Variability in Hourly Activity Levels: Statistical Noise or Insight Into Older Adult Frailty?

BACKGROUND

Frailty is associated with lower mean activity; however, hourly activity is highly variable among older individuals. We aimed to relate frailty to hourly activity variance beyond frailty's association with mean activity.

METHOD

Using the 2010-2011 National Social Life, Health and Aging Project wrist accelerometry data (n = 647), we employed a mixed-effects location scale model to simultaneously determine whether an adapted phenotypic frailty scale (0-4) was associated with the log10-mean hourly counts per minute (cpm) and between-and within-subject hourly activity variability, adjusting for demographics, health characteristics, season, day-of-week, and time-of-day. We tested the significance of a Frailty × Time-of-day interaction and whether adjusting for sleep time altered relationships.

RESULTS

Each additional frailty point was associated with a 7.6% (10-0.0343, β = -0.0343; 95% CI: -0.05, -0.02) lower mean hourly cpm in the morning, mid-day, and late afternoon but not evening. Each frailty point was also associated with a 24.5% (e0.219, β = 0.219; 95% CI: 0.09, 0.34) greater between-subject hourly activity variance across the day; a 7% (e0.07, β = 0.07; 95% CI: 0.01¸ 0.13), 6% (e0.06, β = 0.06; 95% CI: 0, 0.12), and 10% (e0.091, β = 0.091; 95% CI: 0.03, 0.15) greater within-subject hourly activity variance in the morning, mid-day, and late afternoon, respectively; and a 6% (e-0.06, β = -0.06; 95% CI: -0.12, -0.003) lower within-subject hourly activity variance in the evening. Adjusting for sleep time did not alter results.

CONCLUSIONS

Frail adults have more variable hourly activity levels than robust adults, a potential novel marker of vulnerability. These findings suggest a need for more precise activity assessment in older adults.

Television Viewing, Physical Activity, and Loneliness in Late Life

BACKGROUND AND OBJECTIVES

Television viewing is the most common leisure activity in late life and may ease loneliness but encourage sedentary behavior. These associations may be particularly evident among older adults who live alone and who may lack other forms of companionship throughout the day.

RESEARCH DESIGN AND METHODS

Adults aged 65+ (N = 257) participated, of whom 34% lived alone. Participants completed an initial interview followed by a 5- to 6-day data collection involving multi-methods: (a) Electronically Activated Recorders (EAR) (30 seconds every 7 minutes) provided audio recordings of television viewing, (b) Actical accelerometers objectively measured physical activity, and (c) ecological momentary assessments (EMA) every 3 hours assessed social interactions.

RESULTS

On average, older adults spent approximately 37% of their waking time (6.4 hours a day) watching television. Multilevel models revealed that television viewing occurred when participants were alone or with a spouse and was associated with a greater proportion of time sedentary, lower activity, and higher ratings of loneliness compared to when not watching television. Older adults who lived alone reported greater loneliness during 3-hour intervals when viewing television, but older adults who lived with others spent a greater proportion of time sedentary when viewing television.

DISCUSSION AND IMPLICATIONS

Findings are discussed with regard to different rationales and ways of watching television - as compensation for social isolation or as a passive leisure activity with a social partner. We discuss ideas for research on additional aspects of television viewing and screen time in late life.

Assessment of Physical Activity in Adults using Wrist Accelerometers

The health benefits of physical activity have been widely recognized, yet traditional measures of physical activity including questionnaires and category-based assessments of volume and intensity provide only broad estimates of daily activities. Accelerometers have advanced epidemiologic research on physical activity by providing objective and continuous measurement of physical activity in free-living conditions. Wrist-worn accelerometers have become especially popular due to low participant burden. However, the validity and reliability of wrist-worn devices for adults have yet to be summarized. Moreover, accelerometer data provide rich information on how physical activity is accumulated throughout the day, but only a small portion of these rich data have been utilized by researchers. Lastly, new methodological developments that aim to overcome some of the limitations of accelerometers are emerging. The purpose of this review is to provide an overview of accelerometry research, with a special focus on wrist-worn accelerometers. We describe briefly how accelerometers work, summarize the validity and reliability of wrist-worn accelerometers, discuss the benefits of accelerometers including measuring light-intensity physical activity, and discuss pattern metrics of daily physical activity recently introduced in the literature. A summary of large-scale cohort studies and randomized trials that implemented wrist-worn accelerometry is provided. We conclude the review by discussing new developments and future directions of research using accelerometers, with a focus on wrist-worn accelerometers.

Variety Is the Spice of Late Life: Social Integration and Daily Activity

OBJECTIVES

Social integration (involvement with a diverse array of social ties) has been linked to positive outcomes including better physical health. Research has not investigated whether encounters with diverse social ties enhance individuals' daily behaviors. The objectives of this study were to assess whether social ties connect individuals to more diverse daily behaviors, physical activity, and nonsedentary time as well as more positive mood.

METHOD

Older adults (aged 65+, n = 313) provided information about their 10 closest social ties. Then they completed ecological momentary assessment (EMA) surveys every 3 hr for 5-6 days where they reported on social encounters and behaviors. They also wore Actical accelerometers to objectively measure physical activity.

RESULTS

Multilevel models revealed that encounters with a greater variety of social ties was associated with engaging in a greater variety of behaviors, more objectively measured physical activity, and a smaller proportion of time spent sedentary. Encounters with weak ties/peripheral social ties accounted for this increased activity (compared to being alone or with close friends or family). Moreover, involvement with diverse ties or diverse behaviors was associated with better mood.

DISCUSSION

Findings are discussed in terms of social engagement theory, network diversity, and the benefits of weak ties.

Enabling Older Adults' Health Self-Management through Self-Report and Visualization-A Systematic Literature Review

Aging is associated with a progressive decline in health, resulting in increased medical care and costs. Mobile technology may facilitate health self-management, thus increasing the quality of care and reducing costs. Although the development of technology offers opportunities in monitoring the health of older adults, it is not clear whether these technologies allow older adults to manage their health data themselves. This paper presents a review of the literature on mobile health technologies for older adults, focusing on whether these technologies enable the visualization of monitored data and the self-reporting of additional information by the older adults. The systematic search considered studies published between 2009 and 2019 in five online databases. We screened 609 articles and identified 95 that met our inclusion and exclusion criteria. Smartphones and tablets are the most frequently reported technology for older adults to enter additional data to the one that is monitored automatically. The recorded information is displayed on the monitoring device and screens of external devices such as computers. Future designs of mobile health technology should allow older users to enter additional information and visualize data; this could enable them to understand their own data as well as improve their experience with technology.

Long-Term Recreational Football Training and Health in Aging

This narrative review aims to critically analyze the effects of exercise on health in aging. Here we discuss the main clinical and biomolecular modifications induced by long-term recreational football training in older subjects. In particular, the effects induced by long-term recreational football training on cardiovascular, metabolic and musculo-skeletal fitness, together with the modifications in the muscle expression of hallmarks related to oxidative metabolism, DNA repair and senescence suppression pathways and protein quality control mechanisms will be provided. All these topics will be debated also in terms of preventing non-communicable metabolic diseases, in order to achieve successful aging over time.

The Association Between Objectively Measured Physical Activity and Subsequent Health Care Utilization in Older Men

BACKGROUND

To examine the associations between objective physical activity measures and subsequent health care utilization.

METHODS

We studied 1,283 men (mean age 79.1 years, SD 5.3) participating in the Osteoporotic Fractures in Men Study. Participants wore a SenseWear® Pro Armband monitor for 1 week. Data was summarized as daily (i) step counts, (ii) total energy expenditure, (iii) active energy expenditure, and (iv) activity time (sedentary, ≥ light, ≥ moderate). The outcome measures of 1-year hospitalizations/duration of stay from Medicare data were analyzed with a two-part hurdle model. Covariates included age, clinical center, body mass index, marital status, depressive symptoms, medical conditions, cognitive function, and prior hospitalization.

RESULTS

Each 1 SD = 3,092 step increase in daily step count was associated with a 34% (95% confidence interval [CI]: 19%-46%) lower odds of hospitalization in base model (age and center) and 21% (95% CI: 4%-35%) lower odds of hospitalization in fully adjusted models. Similar but smaller associations held for other physical activity measures, but these associations were not significant in fully adjusted models. Among those hospitalized, higher step count was associated with shorter total duration of acute/postacute care stays in the base model only. There was a fourfold significant difference (from model-based estimates) in predicted care days comparing those with 2,000 versus 10,000 daily steps in the base model, but only a twofold difference (not significant) in the full model.

CONCLUSION

Daily step count is an easily determined measure of physical activity that may be useful in assessment of future health care burden in older men.

The Relationship Between Physical Activity and Frailty Among U.S. Older Adults Based on Hourly Accelerometry Data

Background/Objectives

Accelerometry measures older adult (in)activity with high resolution. Most studies summarize activity over the entire wear time. We extend prior work by analyzing hourly activity data to determine how frailty and other characteristics relate to activity among older adults.

Methods

Using wrist accelerometry data collected from the National Social Life, Health and Aging Project (n = 651), a nationally-representative probability sample of older adults, we used mixed effects linear regression to model the logarithm of hourly counts per minute as a function of an adapted phenotypic frailty score, adjusting for demographic and health characteristics, season, day of week and time of day.

Results

Higher frailty scores were associated with modestly lower activity; each frailty point (0-4) corresponded to a 7% lower mean hourly counts per minute. Older age, more comorbidities, male gender, and higher BMI were also associated with lower activity, though the latter was not evident among frail respondents. After adjusting for differences associated with frailty and other covariates, a substantial amount of between-individual variability in activity remained, as well as within-individual variability across days.

Conclusion

Our findings indicate that frail elders, men, those who are older, overweight or have multiple comorbidities are most likely to have low activity. However, residual differences between individuals remain larger than the differences associated with frailty and other covariates. We suggest defining individual-specific activity goals and further research to identify the sources of between-individual variability to better understand how activity reflects health status and to permit the development of more effective interventions.

Social capital predicts accelerometry-measured physical activity among older adults in the U.S.: a cross-sectional study in the National Social Life, Health, and Aging Project

Background

Older adults receive important health benefits from more robust social capital. Yet, the mechanisms behind these associations are not fully understood. Some evidence suggests that higher levels of social capital ultimately affect health through alterations in physical activity (PA), but most of this research has relied on self-reported levels of PA. The aim of this study was to determine whether components of social capital, including social network size and composition as well as the frequency of participation in various social and community activities, were associated with accelerometry-measured PA levels in a nationally representative sample of community-dwelling older adults (≥ 62 years).

Methods

We conducted a cross-sectional analysis using data from the wrist accelerometry sub-study (n = 738) within Wave 2 of the National Social, Health, and Aging Project (NSHAP), a population-based longitudinal study that collects extensive survey data on the physical, cognitive, and social health of older adults. Participants’ physical activity was measured with a wrist accelerometer worn for 72 consecutive hours. We related seven, self-reported social relationship variables (network size, network proportion friends, and frequencies of socializing with friends and family, visiting with neighbors, attending organized group meetings, attending religious services, and volunteering) to accelerometer-measured PA (mean counts-per-minute) using multivariate linear regression analysis, while adjusting for potential confounders.

Results

Larger social networks (p = 0.042), higher network proportion friends (p = 0.013), more frequent visiting with neighbors (p = 0.009), and more frequent attendance at organized group meetings (p = 0.035) were associated with higher PA levels after controlling for demographic and health covariates. Volunteering was significant prior to adjusting for covariates. No significant associations were found between frequencies of socializing with friends and relatives or attendance at religious services and PA.

Conclusions

This study suggests social capital is significantly related to objectively measured PA levels among older adults, and that friendships as well as social participation in groups and with neighbors may be particularly pertinent to PA. These findings expand our understanding of and offer a potential mechanism linking social relationships and overall health among older adults. They also have implications for how we might motivate older adults to be more physically active.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5664-6) contains supplementary material, which is available to authorized users.

A Review of Activity Trackers for Senior Citizens: Research Perspectives, Commercial Landscape and the Role of the Insurance Industry

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature. However, their application to older adults can present particular constraints. This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability. This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems. Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future.

Accelerometer assessed moderate-to-vigorous physical activity and successful ageing: results from the Whitehall II study

Physical activity is key for successful ageing, but questions remain regarding the optimal physical activity pattern. We examined the cross-sectional association between physical activity and successful ageing using data on 3,749 participants (age range = 60-83years) of the Whitehall II study. The participants underwent a clinical assessment, completed a 20-item physical activity questionnaire, and wore a wrist-mounted accelerometer for 9 days. Successful ageing was defined as good cognitive, motor, and respiratory functioning, along with absence of disability, mental health problems, and major chronic diseases. Time spent in moderate-to-vigorous physical activity (MVPA) episodes assessed by accelerometer was classified as "short" (1-9.59 minutes) and "long" (≥10 minutes) bouts. Linear multivariate regression showed that successful agers (N = 789) reported 3.79 (95% confidence interval (CI): 1.39-6.19) minutes more daily MVPA than other participants. Accelerometer data showed this difference to be 3.40 (95% CI:2.44-4.35) minutes for MVPA undertaken in short bouts, 4.16 (95% CI:3.11-5.20) minutes for long bouts, and 7.55 (95% CI:5.86-9.24) minutes for all MVPA bouts lasting 1 minute or more. Multivariate logistic regressions showed that participants undertaking ≥150 minutes of MVPA per week were more likely to be successful agers with both self-reported (Odd Ratio (OR) = 1.29,95% (CI):1.09-1.53) and accelerometer data (length bout ≥1 minute:OR = 1.92, 95%CI:1.60-2.30). Successful agers practice more MVPA, having both more short and long bouts, than non-successful agers.

Assessing Fatigability in the Lab and in Daily Life in Older Adults With Osteoarthritis Using Perceived, Performance, and Ecological Measures

BACKGROUND

Fatigue in older adults is associated with functional decline and reduced participation in daily life; however, it is not well characterized. Examining fatigue within activity performance, or "fatigability," is a recommended approach to begin to understand fatigue and its underlying mechanisms. This study examined the construct validity of lab-based measures of fatigability and compared these measures with fatigability in daily life (termed ecological fatigability).

METHODS

Participants with osteoarthritis and fatigue (n = 163) underwent laboratory assessments, completed questionnaires, and wore accelerometers for 7 days while tracking symptoms and behaviors. Lab-based fatigability measures were quantified using the 6-minute walk test. Perceived fatigability was assessed by asking participants before and after the test to report: (i) fatigue severity and (ii) perceived exertion. Performance fatigability was calculated using change in walking speed divided by total distance walked. Ecological fatigability was calculated from the 7-day assessment in which fatigue severity was reported five times a day and physical activity was continuously measured. Additional ecological measures (eg, self-pacing) were examined.

RESULTS

Lab-based perceived and performance fatigability measures were highly inter-correlated, moderately correlated with gait speed and metabolic measures, and weakly correlated with physical activity. Although ecological fatigability was weakly correlated with lab-based measures, participants with high fatigability on lab-based measures demonstrated more self-pacing behaviors than participants with low fatigability.

CONCLUSION

Lab-based fatigability measures are related to physical capacity measured both in the lab and daily life. Lab-based fatigability measures provide important information regarding daily life fatigability useful for future intervention development.