Assessment of Physical Activity in Adults using Wrist Accelerometers

Comparing cadence-based and machine learning based estimates for physical activity intensity classification: The UK Biobank

OBJECTIVES

Cadence thresholds have been widely used to categorize physical activity intensity in health-related research. We examined the convergent validity of two cadence-based intensity classification approaches against a machine-learning-based intensity schema in 84,315 participants (≥40 years) with wrist-worn accelerometers.

DESIGN

Validity study.

METHODS

Both cadence-based methods (one-level cadence, two-level cadence) calculated intensity-specific time based on cadence-thresholds while the two-level cadence identified stepping behaviors first. We used an overlapping plot, mean absolute error, and Spearman's correlation coefficient to examine agreements between the cadence-based and machine-learning methods. We also evaluated agreements between methods based on practically-important-difference (moderate-to-vigorous-physical activity: ±20 min/day, moderate-physical activity: ±15, vigorous-physical activity: ±2.5, light-physical activity: ±30).

RESULTS

The group-level (median) minutes of moderate-to-vigorous- and moderate-physical activity estimated by one-level cadence were within the range of practically-important-difference compared to the machine-learning method (bias of median: moderate-to-vigorous-physical activity, -3.5, interquartile range [-15.8, 12.2]; moderate-physical activity, -6.0 [-17.2, 4.1]). The group-level vigorous- and light-physical activity minutes derived by two-level cadence were within practically-important-difference range (vigorous-physical activity: -0.9 [-3.1, 0.5]; light-physical activity, -1.3 [-28.2, 28.9]). The individual-level differences between the cadence-based and machine learning methods were high across intensities (e.g., moderate-to-vigorous-physical activity: mean absolute error [one-level cadence: 24.2 min/day; two-level cadence: 26.2]), with the proportion of participants within the practically-important-difference ranging from 8.4 % to 61.6 %.

CONCLUSIONS

One-level cadence showed acceptable group-level estimates of moderate-to-vigorous and moderate-physical activity while two-level cadence showed acceptable group-level estimates of vigorous- and light-physical activity. The cadence-based methods might not be appropriate for individual-level intensity-specific time estimation.

Neighborhood Walkability Is Associated With Global Positioning System-Derived Community Mobility of Older Adults

BACKGROUND

Neighborhood walkability may encourage greater out-of-home travel (ie, community mobility) to support independent functioning in later life. We examined associations between a novel walkability audit index and Global Positioning System (GPS)-derived community mobility in community-dwelling older adults. We compared associations with the validated Environmental Protection Agency (EPA) National Walkability Index and further examined moderation by clinical walking speed.

METHODS

Participants were 146 older adults (Mean = 77.0 ± 6.5 years, 68% women) at baseline of a randomized trial to improve walking speed. A walkability index (range: 0-5; eg, land-use mix, crosswalks, and so on) was created using Google Street View audits within 1/8-mile of the home. Participants carried a GPS device for 5-7 days to derive objective measures of community mobility (eg, time spent out of home, accumulated distance from home).

RESULTS

Each 1 SD (~1.3-point) greater walkability audit score was associated with a median 2.16% more time spent out of home (95% confidence interval [95% CI]: 0.30-4.03, p = .023), adjusting for individual demographics/health and neighborhood socioeconomic status. For slower walkers (4-m walking speed <1 m/s), each 1 SD greater audit score was also associated with a median 4.54 km greater accumulated distance from home (95% CI: 0.01-9.07, p (interaction) = .034). No significant associations were found for the EPA walkability index.

CONCLUSIONS

Walkability immediately outside the home was related to greater community mobility, especially for older adults with slower walking speeds. Results emphasize the need to consider the joint influence of local environment and individual functioning when addressing community mobility in older populations.

Differences in Daily Physical Activity by Alzheimer's Risk Markers Among Older Adults

BACKGROUND

Daily physical activity patterns differ by Alzheimer's disease (AD) status and might signal cognitive risk. It is critical to understand whether patterns are disrupted early in the AD pathological process. Yet, whether established AD risk markers (β-amyloid [Aβ] or apolipoprotein E-ε4 [APOE-ε4]) are associated with differences in objectively measured activity patterns among cognitively unimpaired older adults is unclear.

METHODS

Wrist accelerometry, brain Aβ (+/-), and APOE-ε4 genotype were collected in 106 (Aβ) and 472 (APOE-ε4) participants (mean age 76 [standard deviation{SD}: 8.5) or 75 [SD: 9.2] years, 60% or 58% women) in the Baltimore Longitudinal Study of Aging. Adjusted linear and function-on-scalar regression models examined whether Aβ or APOE-ε4 status was cross-sectionally associated with activity patterns (amount, variability, or fragmentation) overall and by time of day, respectively. Differences in activity patterns by combinations of Aβ and APOE-ε4 status were descriptively examined (n = 105).

RESULTS

There were no differences in any activity pattern by Aβ or APOE-ε4 status overall. Aβ+ was associated with lower total amount and lower within-day variability of physical activity overnight and early evening, and APOE-ε4 carriers had higher total amount of activity in the evening and lower within-day variability of activity in the morning. Diurnal curves of activity were blunted among those with Aβ+ regardless of APOE-ε4 status, but only when including older adults with mild cognitive impairment/dementia.

CONCLUSIONS

Aβ+ in cognitively unimpaired older adults might manifest as lower amount and variability of daily physical activity, particularly during overnight/evening hours. Future research is needed to examine changes in activity patterns in larger samples and by other AD biomarkers.

Physical Activity Fragmentation and Falls in Older Adults: Findings From the National Health and Aging Trends Study

BACKGROUND

Physical activity (PA) may be an important fall prevention strategy. Current PA guidelines emphasize total PA dose, but daily patterning of PA is underappreciated. With aging, PA bouts become less frequent and shorter in duration (ie, more fragmented). PA fragmentation may be an indicator of fall risk, but the relationship is not well understood. This study examined daily PA accumulation and patterns with fall risk in older adults.

METHODS

Participants (n = 685, 54.3% women, 61.5% aged 70-79 years) from the National Health and Aging Trends Study with wrist-worn accelerometry PA data from Round 11 (baseline) and sample person interviews with fall data from Round 12 (follow-up) were included. PA variables were categorized into tertiles and incident falls were defined as ≥1 self-reported fall in the year following the PA assessment between baseline and follow-up. A modified Poisson approach was used to estimate the relative risk of both PA accumulation and fragmentation with falls.

RESULTS

Overall, 40.0% reported an incident fall. After adjustment for sociodemographic and health characteristics, those in the highest tertile of total PA accumulation had lower fall risk (aRR = 0.74, 95% CI: 0.57, 0.95) and those in the highest tertile of PA fragmentation had increased fall risk (aRR = 1.33, 95% CI: 1.03, 1.73). Models were attenuated after adjustment for physical functioning.

CONCLUSIONS

PA fragmentation may identify fall risk in older adults. Longitudinal studies are needed to disentangle the temporal sequencing of the complex relationship between PA and physical functioning across the life course.

Association between profiles of accelerometer-measured daily movement behaviour and mortality risk: a prospective cohort study of British older adults

Objectives

We identified profiles of wake-time movement behaviours (sedentary behaviours, light intensity physical activity and moderate-to-vigorous physical activity) based on accelerometer-derived features among older adults and then examined their association with all-cause mortality.

Methods

Data were drawn from a prospective cohort of 3991 Whitehall II accelerometer substudy participants aged 60-83 years in 2012-2013. Daily movement behaviour profiles were identified using k-means cluster analysis based on 13 accelerometer-assessed features characterising total duration, frequency, bout duration, timing and activity intensity distribution of movement behaviour. Cox regression models were used to assess the association between derived profiles and mortality risk.

Results

Over a mean follow-up of 8.1 (SD 1.3) years, a total of 410 deaths were recorded. Five distinct profiles were identified and labelled as 'active' (healthiest), 'active sitters', 'light movers', 'prolonged sitters', and 'most sedentary' (most deleterious). In model adjusted for sociodemographic, lifestyle, and health-related factors, compared with the 'active' profile, 'active sitters' (HR 1.57, 95% CI 1.01 to 2.44), 'light movers' (HR 1.75, 95% CI 1.17 to 2.63), 'prolonged sitters' (HR 1.67, 95% CI 1.11 to 2.51), 'most sedentary' (HR 3.25, 95% CI 2.10 to 5.02) profiles were all associated with a higher risk of mortality.

Conclusion

Given the threefold higher mortality risk among those with a 'most sedentary' profile, public health interventions may target this group wherein any improvement in physical activity and sedentary behaviour might be beneficial.

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study

Low physical activity (PA) measured by accelerometers and low heart rate variability (HRV) measured from short-term ECG recordings are associated with worse cognitive function. Wearable long-term ECG monitors are now widely used, and some devices also include an accelerometer. The objective of this study was to evaluate whether PA or HRV measured from long-term ECG monitors was associated with cognitive function among older adults. A total of 1590 ARIC participants had free-living PA and HRV measured over 14 days using the Zio® XT Patch [aged 72-94 years, 58% female, 32% Black]. Cognitive function was measured by cognitive factor scores and adjudicated dementia or mild cognitive impairment (MCI) status. Adjusted linear or multinomial regression models examined whether higher PA or higher HRV was cross-sectionally associated with higher factor scores or lower odds of MCI/dementia. Each 1-unit increase in the total amount of PA was associated with higher global cognition (β = 0.30, 95% CI: 0.16-0.44) and executive function scores (β = 0.38, 95% CI: 0.22-0.53) and lower odds of MCI (OR = 0.38, 95% CI: 0.22-0.67) or dementia (OR = 0.25, 95% CI: 0.08-0.74). HRV (i.e., SDNN and rMSSD) was not associated with cognitive function. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia.

Measuring Physical Functioning Using Wearable Sensors in Parkinson Disease and Chronic Obstructive Pulmonary Disease (the Accuracy of Digital Assessment of Performance Trial Study): Protocol for a Prospective Observational Study

BACKGROUND

Physical capacity and physical activity are important aspects of physical functioning and quality of life in people with a chronic disease such as Parkinson disease (PD) or chronic obstructive pulmonary disease (COPD). Both physical capacity and physical activity are currently measured in the clinic using standardized questionnaires and tests, such as the 6-minute walk test (6MWT) and the Timed Up and Go test (TUG). However, relying only on in-clinic tests is suboptimal since they offer limited information on how a person functions in daily life and how functioning fluctuates throughout the day. Wearable sensor technology may offer a solution that enables us to better understand true physical functioning in daily life.

OBJECTIVE

We aim to study whether device-assisted versions of 6MWT and TUG, such that the tests can be performed independently at home using a smartwatch, is a valid and reliable way to measure the performance compared to a supervised, in-clinic test.

METHODS

This is a decentralized, prospective, observational study including 100 people with PD and 100 with COPD. The inclusion criteria are broad: age ≥18 years, able to walk independently, and no co-occurrence of PD and COPD. Participants are followed for 15 weeks with 4 in-clinic visits, once every 5 weeks. Outcomes include several walking tests, cognitive tests, and disease-specific questionnaires accompanied by data collection using wearable devices (the Verily Study Watch and Modus StepWatch). Additionally, during the last 10 weeks of this study, participants will follow an aerobic exercise training program aiming to increase physical capacity, creating the opportunity to study the responsiveness of the remote 6MWT.

RESULTS

In total, 89 people with PD and 65 people with COPD were included in this study. Data analysis will start in April 2024.

CONCLUSIONS

The results of this study will provide information on the measurement properties of the device-assisted 6MWT and TUG in the clinic and at home. When reliable and valid, this can contribute to a better understanding of a person's physical capacity in real life, which makes it possible to personalize treatment options.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05756075; https://clinicaltrials.gov/study/NCT05756075.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/55452.

Examining the Association Between Objective Physical Activity and Momentary Pain: A Systematic Review of Studies Using Ambulatory Assessment

Chronic pain (CP) is a debilitating and increasingly common health condition that adversely impacts function, including physical activity (PA). Research using ambulatory assessment (AA) methods (eg, ecological momentary assessment, actigraphy) offers promise for elucidating the relationship between momentary pain and objective PA in CP populations. This study aimed to systematically review articles assessing the association between momentary pain and PA in adults with CP as measured using AA and to make recommendations for the measurement and study of this relationship. Five databases were systematically searched, and 13 unique records (N = 768) met the inclusion criteria. CP conditions included mixed/nonspecific CP (k = 3), low back pain (k = 2), fibromyalgia (k = 1), unspecified arthritis (k = 1), and hip/knee osteoarthritis (k = 6). The average age of participants across studies was 55.29 years, and the majority identified as women (60.68%) and White (83.16%). All studies measured objective PA via actigraphy, and momentary pain with either a diary/log or ratings on an actigraph. Studies varied in the quantification of PA (ie, activity counts, step count, moderate-vigorous PA), statistical method (ie, correlation, regression, multilevel modeling), and inclusion of moderators (eg, pain acceptance). Studies reported mixed results for the pain-PA relationship. This heterogeneity suggests that no summarizing conclusions can be drawn about the pain-PA relationship without further investigation into its complex nuances. More within-person and exploratory examinations that maximize the richness of AA data are needed. A greater understanding of this relationship can inform psychotherapeutic and behavioral recommendations to improve CP outcomes. PERSPECTIVE: This article presents a systematic review of the literature on the association between momentary pain and PA in adults with CP as measured using AA methods. A better understanding of this nuanced relationship could help elucidate areas for timely intervention and may inform clinical recommendations to improve CP outcomes. PROSPERO REGISTRATION NUMBER: CRD42023389913.

Study protocol and rationale of "the UP project": evaluating the effectiveness of active breaks on health indicators in desk-based workers

Background

Excessive sedentary time has been negatively associated with several health outcomes, and physical activity alone does not seem to fully counteract these consequences. This panorama emphasizes the essential of sedentary time interruption programs. "The Up Project" seeks to assess the effectiveness of two interventions, one incorporating active breaks led by a professional and the other utilizing a computer application (self-led), of both equivalent duration and intensity. These interventions will be compared with a control group to evaluate their impact on physical activity levels, sedentary time, stress perception, occupational pain, and cardiometabolic risk factors among office workers.

Methods

This quasi-experimental study includes 60 desk-based workers from universities and educational institutes in Valparaiso, Chile, assigned to three groups: (a) booster breaks led by professionals, (b) computer prompts that are unled, and (c) a control group. The intervention protocol for both experimental groups will last 12 weeks (only weekdays). The following measurements will be performed at baseline and post-intervention: cardiometabolic risk based on body composition (fat mass, fat-free mass, and bone mass evaluated by DXA), waist circumference, blood pressure, resting heart rate, and handgrip strength. Physical activity and sedentary time will be self-reported and device-based assessed using accelerometry. Questionnaires will be used to determine the perception of stress and occupational pain.

Discussion

Governments worldwide are addressing health issues associated with sedentary behavior, particularly concerning individuals highly exposed to it, such as desk-based workers. Despite implementing certain strategies, there remains a noticeable gap in comprehensive research comparing diverse protocols. For instance, studies that contrast the outcomes of interventions led by professionals with those prompted by computers are scarce. This ongoing project is expected to contribute to evidence-based interventions targeting reduced perceived stress levels and enhancing desk-based employees' mental and physical well-being. The implications of these findings could have the capacity to lay the groundwork for future public health initiatives and government-funded programs.

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: the ARIC Neurocognitive Study

BACKGROUND

Low physical activity (PA) measured from accelerometers and low heart rate variability (HRV) measured from short-term ECG recordings are associated with worse cognitive function. Wearable long-term ECG monitors are now widely used. These monitors can provide long-term HRV data and, if embedded with an accelerometer, they can also provide PA data. Whether PA or HRV measured from long-term ECG monitors is associated with cognitive function among older adults is unknown.

METHODS

Free-living PA and HRV were measured simultaneously over 14-days using the Zio ® XT Patch among 1590 participants in the Atherosclerosis Risk in Communities Study [aged 72-94 years, 58% female, 32% Black]. Total amount of PA was estimated by total mean amplitude deviation (TMAD) from the 14-day accelerometry raw data. HRV indices (SDNN and rMSSD) were measured from the 14-day ECG raw data. Cognitive factor scores for global cognition, executive function, language, and memory were derived using latent variable methods. Dementia or mild cognitive impairment (MCI) status was adjudicated. Linear or multinomial regression models examined whether higher PA or higher HRV was cross-sectionally associated with higher factor scores or lower odds of MCI/dementia. Models were adjusted for demographic and medical comorbidities.

RESULTS

Each 1-unit higher in total amount of PA was significantly associated with 0.30 higher global cognition factor scores (95% CI: 0.16-0.44), 0.38 higher executive function factor scores (95% CI: 0.22-0.53), and 62% lower odds of MCI (OR: 0.38, 95% CI: 0.22-0.67) or 75% lower odds of dementia (OR: 0.25, 95% CI: 0.08-0.74) versus unimpaired cognition. Neither HRV measure was significantly associated with cognitive function or dementia.

CONCLUSIONS

PA derived from a 2-week ECG monitor with an embedded accelerometer was significantly associated with higher cognitive test performance and lower odds of MCI/dementia among older adults. By contrast, HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia.

CLINICAL PERSPECTIVE

What Is New?: This cross-sectional study evaluated associations between physical activity (PA) and heart rate variability (HRV) measured over 14 days from a wearable ECG monitor with cognitive function.Higher total amount of PA was associated with higher global cognition and executive function, as well as lower odds of mild cognitive impairment or dementia.HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes.What Are the Clinical Implications?: These findings replicate positive associations between PA and cognitive function using accelerometer data from a wearable ECG monitor with an embedded accelerometer.These findings raise the possibility of using wearable ECG monitors (with embedded accelerometers) as a promising tool for digital phenotyping of dementia.

Determinants of Physical Activity Among Black Women During Pregnancy

OBJECTIVE

To describe associations among background determinants of physical activity, modifiable theoretical determinants of physical activity, and measures of physical activity during the second and third trimesters of pregnancy among Black women.

DESIGN

Longitudinal cohort.

SETTING

Medical center obstetric clinic.

PARTICIPANTS

Pregnant Black women (n = 40 in second trimester, n = 38 in third trimester) METHODS: We measured background determinants (demographic and pregnancy characteristics, discrimination, and neighborhood walkability) during the second trimester. We measured modifiable theoretical determinants (self-efficacy and social support) and physical activity using self-report and device measures during the second and third trimesters. We used paired t tests to determine differences in the modifiable theoretical determinants from the second trimester to third trimester and used Pearson correlations among background and modifiable determinants and physical activity measures during the second trimester.

RESULTS

Participants' physical activity levels were low during the second and third trimesters (32% and 22% met recommendation, respectively). We found no changes in self-efficacy or social support between trimesters and found no associations between these modifiable determinants and actual physical activity. We found a positive correlation between previous pregnancies and physical activity measured by devices, r(36) = .33, p = .048. Pregnancy-specific stress, r(38) = -.40, p = .013, was negatively correlated, and age, r(38) = .38, p = .017, was positively correlated with self-reported physical activity.

CONCLUSIONS

Low levels of physical activity during pregnancy coupled with the absence of an association with modifiable factors affecting pregnancy physical activity indicate a need to further examine the social, cultural, and environmental determinants of physical activity.

Comparison of sleep parameters from wrist-worn ActiGraph and Actiwatch devices

Sleep and physical activity, two important health behaviors, are often studied independently using different accelerometer types and body locations. Understanding whether accelerometers designed for monitoring each behavior can provide similar sleep parameter estimates may help determine whether one device can be used to measure both behaviors. Three hundred and thirty one adults (70.7 ± 13.7 years) from the Baltimore Longitudinal Study of Aging wore the ActiGraph GT9X Link and the Actiwatch 2 simultaneously on the non-dominant wrist for 7.0 ± 1.6 nights. Total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, number of wake bouts, mean wake bout length, and sleep fragmentation index (SFI) were extracted from ActiGraph using the Cole-Kripke algorithm and from Actiwatch using the software default algorithm. These parameters were compared using paired t-tests, Bland-Altman plots, and Deming regression models. Stratified analyses were performed by age, sex, and body mass index (BMI). Compared to the Actiwatch, the ActiGraph estimated comparable TST and sleep efficiency, but fewer wake bouts, longer WASO, longer wake bout length, and higher SFI (all p < .001). Both devices estimated similar 1-min and 1% differences between participants for TST and SFI (β = 0.99, 95% CI: 0.95, 1.03, and 0.91, 1.13, respectively), but not for other parameters. These differences varied by age, sex, and/or BMI. The ActiGraph and the Actiwatch provide comparable absolute and relative estimates of TST, but not other parameters. The discrepancies could result from device differences in movement collection and/or sleep scoring algorithms. Further comparison and calibration is required before these devices can be used interchangeably.

Relationship between rest-activity rhythms and cardiorespiratory fitness in middle-aged workers: a cross-sectional study with non-parametric analysis using accelerometers worn on the thigh

BACKGROUND

Rest-activity rhythms are directly related to health risks, but there are limited objective methods to assess them. This study aimed to investigate the relationship between rest-activity rhythms and cardiorespiratory fitness (CRF) in middle-aged workers.

METHODS

Peak oxygen uptake was measured on a treadmill to assess CRF in 254 middle-aged workers who were divided into low, medium, and high-CRF groups based on tertiles. Participants were asked to wear an accelerometer (activPAL) on their thighs for 1 week, and the logarithmically transformed acceleration data were used for the analysis of a 24-hour rest-activity rhythm. Sex, age, body mass index, occupation, smoking status, and alcohol consumption were used as covariates in Model 1, with Model 2 also including walking count on non-workdays. Repeated measures analysis of variance was used to compare time course of rest-activity rhythms changes on workdays between groups, and post-hoc tests were conducted using Bonferroni's correlation.

RESULTS

Higher CRF correlated with increased physical activity. In model 1, higher CRF showed improved interdaily stability, but the significant difference disappeared in model 2 after adjusting for non-workday walking counts. A time-course group comparison showed that the high group had significantly higher activity levels than those of the low group from 6:00 to 8:59 and 17:00 to 17:59 and the medium group from 6:00 to 7:59 and 19:00 to 19:59.

CONCLUSIONS

Workers who have better rest-activity rhythms and engage in higher levels of physical activity on workdays tend to have higher CRF levels. Regular daily routines, influenced by physical activity during holidays, can positively impact cardiopulmonary endurance.

Hearing Loss and Physical Activity Among Older Adults in the United States

BACKGROUND

Hearing loss is associated with adverse health outcomes among older adults. Lower physical activity levels may partly explain these observations, yet the association between hearing loss, hearing aid use, and physical activity among older adults is understudied.

METHODS

Cross-sectional analysis of National Health and Aging Trends Study (2021) participants. The better-hearing ear pure-tone average (BPTA) at speech frequencies (0.5-4 kHz) was modeled continuously (10-dB increments) and categorically (no: ≤25 dB, mild: 26-40 dB, moderate or greater: >40 dB hearing loss). Activity measures were wrist accelerometry-derived (Actigraph) total activity counts, daily active minutes, activity fragmentation (using active-to-sedentary transition probability), and self-reported participation in vigorous activities and walking for exercise in the last month. We used multivariable regression adjusted for sociodemographic and health covariates.

RESULTS

Among 504 participants excluding hearing aid users (mean age = 79 years, 57% female, 9% Black), 338 (67%) had hearing loss. Worse hearing (continuously and categorically) was associated with fewer counts and active minutes, more fragmented activity, and greater odds of not reporting recent vigorous activities. Among 472 participants with hearing loss including hearing aid users, nonusers (n = 338) had more fragmented activity and greater odds of not reporting walking for exercise compared to users.

CONCLUSIONS

Older adults with hearing loss are less physically active. This may mediate the association between hearing loss and other adverse outcomes. Recognition of this potential association is essential for providers to better support older adults in maintaining an active lifestyle. Future research is warranted to understand the impact of hearing interventions.

Supervised Learning of Physical Activity Features From Functional Accelerometer Data

OBJECTIVE

We propose a new health informatics framework to analyze physical activity (PA) from accelerometer devices. Accelerometry data enables scientists to extract personal digital features useful for precision health decision making. Existing methods in accelerometry data analysis typically begin with discretizing summary counts by certain fixed cutoffs into activity categories. One well-known limitation is that the chosen cutoffs are often validated under restricted settings, and cannot be generalizable across populations, devices, or studies.

METHODS

We develop a data-driven approach to overcome this bottleneck in PA data analysis, in which we holistically summarize a subject's activity profile using Occupation-Time curves (OTCs), which describe the percentage of time spent at or above a continuum of activity count levels. We develop multi-step adaptive learning algorithms to perform supervised learning via a scalar-on-function model that involves OTC as the functional predictor of interest as well as other scalar covariates. Our learning analytic first incorporates a hybrid approach of fused lasso for clustering and Hidden Markov Model for changepoint detection, then executes refinement procedures to determine activity windows of interest.

RESULTS

We evaluate and illustrate the performance of the proposed learning analytic through simulation experiments and real-world data analyses to assess the influence of PA on biological aging. Our findings indicate a different directional relationship between biological age and PA depending on the specific outcome of interest.

SIGNIFICANCE

Our bioinformatics methodology involves the biomedical outcome of interest to detect different critical points, and is thus adaptive to the specific data, study population, and health outcome under investigation.

The influence of ultra-processed food consumption on reward processing and energy intake: Background, design, and methods of a controlled feeding trial in adolescents and young adults

BACKGROUND

The greatest age-related weight gain occurs in the early/mid-20s. Overall dietary quality among adolescents and emerging adults (age 18-25) is poor, with ultra-processed foods (UPF) representing more than two-thirds of adolescents' total energy intake (i.e., 68%). UPF consumption may impact cognitive and neurobiological factors that influence dietary decision-making and energy intake (EI). To date, no research has addressed this in this population.

METHODS

Participants aged 18-25 will undergo two 14-day controlled feeding periods (81% UPF, 0% UPF) using a randomly assigned crossover design, with a 4-week washout between conditions. Brain response to a UPF-rich milkshake, as well as behavioral measures of executive function, will be evaluated before and after each diet. Following each diet, measurements include ad libitum buffet meal EI, food selection, eating rate, and eating in the absence of hunger (EAH). Prior to initiating recruitment, controlled diet menus, buffet, and EAH snacks were developed and evaluated for palatability. Sensory and texture attributes of buffet and EAH snack foods were also evaluated.

RESULTS

Overall diet palatability was rated "like very much" (8)/"like moderately"(7) (UPF: 7.6 ± 1.0; Non-UPF: 6.8 ± 1.5). Subjective hardness rating (range = 1-9 [1 = soft, 9 = hard] was similar between UPF and Non-UPF buffet and snack items (UPF:4.22 ± 2.19, Non-UPF: 4.70 ± 2.03), as was the objective measure of hardness (UPF: 2874.33 ± 2497.06 g, Non-UPF: 2243.32 ± 1700.51 g).

CONCLUSIONS

Findings could contribute to an emerging neurobiological understanding of the effects of UPF consumption including energy overconsumption and weight gain among individuals at a critical developmental stage.

Dose-response associations of Monitor-Independent Movement Summary with health-related fitness in youth

The purpose of this study was to determine the dose-response associations between Monitor-Independent Movement Summary (MIMS) units and health-related fitness in youth. The sample comprised US children and adolescents who participated in the 2012 National Youth Fitness Survey (NNYFS; N = 1158, 48.9% female). Health-related fitness domains were assessed using tests of cardiorespiratory endurance (timed maximal and graded treadmill tests), muscular strength (modified pull-up and grip tests), and muscular endurance (plank test). Movement data were collected using wrist-worn ActiGraph accelerometers with raw data processed using MIMS and the calculated metrics of average MIMS/day, Peak 60-min MIMS, and Peak 30-min MIMS. Weighted regression models examined linear associations between MIMS metrics and fitness test scores. Nonlinear associations were examined using weighted spline models with knots placed at the 10th, 50th, and 90th percentiles. Models were adjusted for covariates and fit was examined using the coefficient of determination (R2 ). The strongest adjusted linear relationships included a positive association between MIMS/day (per every 1000 units) and maximal endurance times (b = 5.5 s, p < 0.001) and between Peak 60-min MIMS (per every 10 units) and estimated aerobic capacity (b = 1.7 mL/kg/min, p < 0.001), modified pull-ups (b = 0.7 reps, p < 0.001), and plank test scores (b = 5.0 s, p < 0.001). Linear spline models had slightly higher R2 values (R2 range = 16.9%-74.8%) compared to linear models (R2 range = 15.0%-74.5%). The relationship between MIMS metrics and fitness test scores was best modeled as piecewise linear functions. Although all MIMS metrics associated with cardiorespiratory endurance, Peak 60-min MIMS showed stronger associations with tests of muscular strength and endurance.

Significant Dose-Response Association of Physical Activity and Diet Quality With Mortality in Adults With Suspected NAFLD in a Population Study

INTRODUCTION

We aimed to determine whether higher levels (volume and intensity) of physical activity (PA) and diet quality (DQ) are associated with better survival rates in nonalcoholic fatty liver disease (NAFLD).

METHODS

Using data from the 2011-2014 National Health and Nutrition Examination Survey, 3,548 participants with a Fatty Liver Index ≥60 were included. PA was collected using a wrist-worn triaxial accelerometer and expressed as 2 metrics using Monitor-Independent Movement Summary (MIMS) units: the average of daily MIMS, which represents volume, and peak 30-minute MIMS, which is the average of the highest 30 MIMS min/d and represents intensity. DQ was assessed by the Healthy Eating Index-2015. Mortality follow-up was recorded using the National Death Index linkage through December 31, 2019.

RESULTS

Our analyses revealed a dose-dependent, nonlinear association of PA (volume and intensity) with all-cause mortality and a dose-dependent, linear association of DQ with all-cause mortality. The maximum protective dose of PA volume was observed at 14,300 MIMS/min (adj. HR: 0.20, 95% CI: 0.11-0.38). The maximum protective dose of PA intensity was observed at 54.25 MIMS/min (adj. HR: 0.10, 95% CI: 0.05-0.23), beyond which mortality risks flattened. The Healthy Eating Index-2015 showed its maximum protective effect at 66.17 (adj. HR: 0.54, 95% CI: 0.40-0.74). Higher PA (volume and intensity) levels were associated with a lower risk of cardiovascular-related but not cancer-related mortality. A healthier diet was linked to a reduced risk of cardiovascular-specific and cancer-specific mortality. Sensitivity analyses showed that the beneficial effects of PA and DQ on survival rates remained significant across sex, racial/ethnic, and age groups as well as in participants without NAFLD.

DISCUSSION

Our findings suggest that higher daily accumulated and peak effort PA and DQ are associated with lower all-cause and cardiovascular mortality in US adults with NAFLD.

Convergent validity of time in bed estimates from activPAL and Actiwatch in free-living youth and adults

Actiwatch devices are often used to estimate time in bed (TIB), but recently became commercially unavailable. Thigh-worn activPAL devices could be a viable alternative. We tested convergent validity between activPAL (CREA algorithm) and Actiwatch devices. Data were from free-living samples comprising 47 youth (3-16 valid nights/participant) and 42 adults (6-26 valid nights/participant) who wore both devices concurrently. On average, activPAL predicted earlier bedtimes and later risetimes compared to Actiwatch, resulting in longer overnight intervals (by 1.49 hours/night for youth and 0.67 hours/night for adults; both p < 0.001). TIB interruptions were predicted less commonly by activPAL (mean < 2 interruptions/night for both youth and adults) than Actiwatch (mean of 24-26 interruptions/night in both groups; both p < 0.001). Overnight intervals for both devices tended to overlap for lengthy periods (mean of 7.38 hours/night for youth and 7.69 hours/night for adults). Within these overlapping periods, the devices gave matching epoch-level TIB predictions an average of 87.9% of the time for youth and 84.3% of the time for adults. Most remaining epochs (11.8% and 15.1%, respectively) were classified as TIB by activPAL but not Actiwatch. Overall, the devices had fair agreement during the overlapping periods, but limited agreement when predicting interruptions, bedtime, or risetime. Future work should assess the criterion validity of activPAL devices to understand implications for health research. The present findings demonstrate that activPAL is not interchangeable with Actiwatch, which is consistent with their differing foundations (thigh inclination for activPAL versus wrist movement for Actiwatch).

Physical Activity Intensity Measurement and Health: State of the Art and Future Directions for Scientific Research

Physical activity guidelines for health recommend any type of unstructured physical activity for health promotion. Adults should perform at least 150-300 min per week of moderate intensity or 75-150 min per week of vigorous intensity activities, or an equivalent combination of the two intensities. However, the relationship between physical activity intensity and longevity remains a debated topic, with conflicting perspectives offered by epidemiologists, clinical exercise physiologists or anthropologists. This paper addresses the current known role of physical activity intensity (in particular vigorous versus moderate intensity) on mortality and the existing problems of measurement. Given the diversity of existing proposals to categorize physical activity intensity, we call for a common methodology. Device-based physical activity measurements (e.g., wrist accelerometers) have been proposed as a valid method to measure physical activity intensity. An appraisal of the results reported in the literature, however, highlights that wrist accelerometers have not yet demonstrated sufficient criterion validity when they are compared to indirect calorimetry. Novel biosensors and wrist accelerometers will help us understand how different metrics of physical activity relates to human health, however, all these technologies are not enough mature to provide personalized applications for healthcare or sports performance.

Free-Living Gait Cadence Measured by Wearable Accelerometer: A Promising Alternative to Traditional Measures of Mobility for Assessing Fall Risk

BACKGROUND

Wearable devices have become widespread in research applications, yet evidence on whether they are superior to structured clinic-based assessments is sparse. In this manuscript, we compare traditional, laboratory-based metrics of mobility with a novel accelerometry-based measure of free-living gait cadence for predicting fall rates.

METHODS

Using negative binomial regression, we compared traditional in-clinic measures of mobility (6-minute gait cadence, speed, and distance, and 4-m gait speed) with free-living gait cadence from wearable accelerometers in predicting fall rates. Accelerometry data were collected with wrist-worn Actigraphs (GT9X) over 7 days in 432 community-dwelling older adults (aged 77.29 ± 5.46 years, 59.1% men, 80.2% White) participating in the Study to Understand Fall Reduction and Vitamin D in You. Falls were ascertained using monthly calendars, quarterly contacts, and ad hoc telephone reports. Accelerometry-based free-living gait cadence was estimated with the Adaptive Empirical Pattern Transformation algorithm.

RESULTS

Across all participants, free-living cadence was significantly related to fall rates; every 10 steps per minute higher cadence was associated with a 13.2% lower fall rate (p = .036). Clinic-based measures of mobility were not related to falls (p > .05). Among higher-functioning participants (cadence ≥100 steps/minute), every 10 steps per minute higher free-living cadence was associated with a 27.7% lower fall rate (p = .01). In participants with slow baseline gait (gait speed <0.8 m/s), all metrics were significantly associated with fall rates.

CONCLUSION

Data collected from biosensors in the free-living environment may provide a more sensitive indicator of fall risk than in-clinic tests, especially among higher-functioning older adults who may be more responsive to intervention.

CLINICAL TRIAL REGISTRATION

NCT02166333.

Method for Activity Sleep Harmonization (MASH): a novel method for harmonizing data from two wearable devices to estimate 24-h sleep-wake cycles

Background

Daily 24-h sleep-wake cycles have important implications for health, however researcher preferences in choice and location of wearable devices for behavior measurement can make 24-h cycles difficult to estimate. Further, missing data due to device malfunction, improper initialization, and/or the participant forgetting to wear one or both devices can complicate construction of daily behavioral compositions. The Method for Activity Sleep Harmonization (MASH) is a process that harmonizes data from two different devices using data from women who concurrently wore hip (waking) and wrist (sleep) devices for ≥ 4 days.

Methods

MASH was developed using data from 1285 older community-dwelling women (ages: 60-72 years) who concurrently wore a hip-worn ActiGraph GT3X + accelerometer (waking activity) and a wrist-worn Actiwatch 2 device (sleep) for ≥ 4 days (N = 10,123 days) at the same time. MASH is a two-tiered process using (1) scored sleep data (from Actiwatch) or (2) one-dimensional convolutional neural networks (1D CNN) to create predicted wake intervals, reconcile sleep and activity data disagreement, and create day-level night-day-night pairings. MASH chooses between two different 1D CNN models based on data availability (ActiGraph + Actiwatch or ActiGraph-only). MASH was evaluated using Receiver Operating Characteristic (ROC) and Precision-Recall curves and sleep-wake intervals are compared before (pre-harmonization) and after MASH application.

Results

MASH 1D CNNs had excellent performance (ActiGraph + Actiwatch ROC-AUC = 0.991 and ActiGraph-only ROC-AUC = 0.983). After exclusions (partial wear [n = 1285], missing sleep data proceeding activity data [n = 269], and < 60 min sleep [n = 9]), 8560 days were used to show the utility of MASH. Of the 8560 days, 46.0% had ≥ 1-min disagreement between the devices or used the 1D CNN for sleep estimates. The MASH waking intervals were corrected (median minutes [IQR]: -27.0 [-115.0, 8.0]) relative to their pre-harmonization estimates. Most correction (-18.0 [-93.0, 2.0] minutes) was due to reducing sedentary behavior. The other waking behaviors were reduced a median (IQR) of -1.0 (-4.0, 1.0) minutes.

Conclusions

Implementing MASH to harmonize concurrently worn hip and wrist devices can minimizes data loss and correct for disagreement between devices, ultimately improving accuracy of 24-h compositions necessary for time-use epidemiology.

Associations between older adults' physical fitness level and their engagement in different types of physical activity: cross-sectional results from the OUTDOOR ACTIVE study

OBJECTIVES

To describe the prevalence of different types of physical activities and to explore the association between engagement in these physical activities and performance in the physical fitness dimensions among older adults living in Bremen, Germany.

DESIGN

Cross-sectional study.

SETTING

Twelve subdistricts in Bremen, Germany.

PARTICIPANTS

1583 non-institutionalised adults aged 65-75 years residing in one of the 12 subdistricts in Bremen, Germany (53.1% female).

PRIMARY OUTCOME MEASURES

Level of physical fitness in five dimensions: handgrip strength (hand dynamometry), lower muscle strength (30 s-chair stand test), aerobic endurance (2 min-step test), lower body flexibility (sit-and-reach test), and upper body flexibility (back scratch test); classified using normative values.

RESULTS

In this study population, home-based activities (housework, gardening) and activities for transport (walking, cycling) were performed by nearly all the participants, while leisure activities were less prevalent. Logistic regression revealed a positive association between being in or over norm in handgrip strength with cycling (OR: 1.56, 95% CI: 1.13 to 2.15), hiking/running (OR: 1.50, 95% CI: 1.05 to 2.16) and other sports (OR: 3.22, 95% CI: 1.37 to 7.56). Lower muscle strength was positively related to cycling (OR: 1.91, 95% CI: 1.37 to 2.65), gym training (OR: 1.62, 95% CI: 1.16 to 2.26) and dancing (OR: 2.15, 95% CI: 1.00 to 4.61). Aerobic endurance was positively associated with cycling (OR: 1.90, 95% CI: 1.37 to 2.65), gym training (OR: 1.68, 95% CI: 1.20 to 2.36), aerobics (OR: 1.64, 95% CI: 1.19 to 2.26), dancing (OR: 2.62, 95% CI: 1.10 to 6.22) and ball sports (OR: 2.07, 95% CI: 1.30 to 3.29). Apart from housework and upper body flexibility (OR: 0.39, 95% CI: 0.19 to 0.78), flexibility dimensions did not show any significant associations.

CONCLUSIONS

While muscle strength dimensions and aerobic endurance were associated with several physical activities, flexibility dimensions were associated with none of the investigated activities apart from housework. Especially cycling and leisure activities (eg, hiking/ running, gym training, aerobics, dancing) showed great potential for sustaining and increasing physical fitness in older age.

Development of a Novel Accelerometry-Based Performance Fatigability Measure for Older Adults

INTRODUCTION

Efforts to study performance fatigability have been limited because of measurement constrains. Accelerometry and advanced statistical methods may enable us to quantify performance fatigability more granularly via objective detection of performance decline. Thus, we developed the Pittsburgh Performance Fatigability Index (PPFI) using triaxial raw accelerations from wrist-worn accelerometer from two in-laboratory 400-m walks.

METHODS

Sixty-three older adults from our cross-sectional study (mean age, 78 yr; 56% women; 88% White) completed fast-paced ( n = 59) and/or usual-paced 400-m walks ( n = 56) with valid accelerometer data. Participants wore ActiGraph GT3X+ accelerometers (The ActiGraph LLC, Pensacola, FL) on nondominant wrist during the walking task. Triaxial raw accelerations from accelerometers were used to compute PPFI, which quantifies percentage of area under the observed gait cadence-versus-time trajectory during a 400-m walk to a hypothetical area that would be produced if the participant sustained maximal cadence throughout the entire walk.

RESULTS

Higher PPFI scores (higher score = greater fatigability) correlated with worse physical function, slower chair stands speed and gait speed, worse cardiorespiratory fitness and mobility, and lower leg peak power (| ρ | = 0.36-0.61 from fast-paced and | ρ | = 0.28-0.67 from usual-paced walks, all P < 0.05). PPFI scores from both walks remained associated with chair stands speed, gait speed, fitness, and mobility, after adjustment for sex, age, race, weight, height, and smoking status; PPFI scores from the fast-paced walk were associated with leg peak power.

CONCLUSIONS

Our findings revealed that the objective PPFI is a sensitive measure of performance fatigability for older adults and can serve as a risk assessment tool or outcome measure in future studies and clinical practice.

Exercise fatigue diagnosis method based on short-time Fourier transform and convolutional neural network

Reasonable exercise is beneficial to human health. However, it is difficult for ordinary athletes to judge whether they are already in a state of fatigue that is not suitable for exercise. In this case, it is easy to cause physical damage or even life-threatening. Therefore, to health sports, protecting the human body in sports not be injured by unreasonable sports, this study proposes an exercise fatigue diagnosis method based on short-time Fourier transform (STFT) and convolutional neural network (CNN). The method analyzes and diagnoses the real-time electrocardiogram, and obtains whether the current exerciser has exercise fatigue according to the electrocardiogram. The algorithm first performs short-time Fourier transform on the electrocardiogram (ECG) signal to obtain the time spectrum of the signal, which is divided into training set and validation set. The training set is then fed into the convolutional neural network for learning, and the network parameters are adjusted. Finally, the trained convolutional neural network model is applied to the test set, and the recognition result of fatigue level is output. The validity and feasibility of the method are verified by the ECG experiment of exercise fatigue degree. The experimental recognition accuracy rate can reach 97.70%, which proves that the constructed sports fatigue diagnosis model has high diagnostic accuracy and is feasible for practical application.

Association of Hearing Impairment and 24-Hour Total Movement Activity in a Representative Sample of US Adults

IMPORTANCE

Lower physical activity (PA) levels have been proposed as a mechanism to explain the association between hearing loss and various adverse outcomes of aging. But whether hearing loss is associated with lower PA is poorly understood.

OBJECTIVE

To evaluate whether hearing loss is associated with lower levels of PA.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional analysis was conducted in a representative sample of US adults (aged 30-69 years) who participated in the 2011-2012 cycle of the National Health and Nutrition Examination Survey (NHANES). Data analysis was conducted from July to September 2021.

EXPOSURES

Hearing was assessed, in dB, by pure-tone audiometry and summarized as the better hearing ear's pure-tone average (BPTA) of 4 speech frequencies (500, 1000, 2000, and 4000 kHz); a higher BTPA indicates worse hearing. Hearing was also categorized into normal (BPTA ≤25 dB), mild hearing impairment (>25 to 40 dB), and moderate or greater hearing impairment (>40 dB).

MAIN OUTCOMES AND MEASURES

Total 24-hour movement activity was measured using wrist accelerometers worn at all times for 7 consecutive days and summarized in monitor-independent movement summary units (MIMS) units (higher MIMS units indicate more movement). The association between BPTA and MIMS units was evaluated using a multivariable-adjusted (demographic characteristics and chronic conditions) piecewise spline regression (knot at 15 dB). Mean differences in MIMS units across hearing categories compared with normal hearing were estimated.

RESULTS

The study included 2490 participants (mean [SE] age, 48.9 [0.3] years; 900 [weighted percentage, 69.3%] White individuals, 1248 [weighted percentage, 50.8%] female participants). Before the knot at 15 dB, we found that each 10-dB higher BPTA was associated with 860.4 (95% CI, 444.8-1276.1) higher MIMS units. Conversely, after the knot, each 10-dB higher BPTA was associated with 458.6 (95% CI, 27.7-889.4) lower MIMS units. The difference in MIMS units across hearing categories was not statistically significant.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, in the range of hearing sensitivity of BPTA of 15 dB or greater, worse hearing was associated with lower MIMS units. Lower PA may be a mechanism contributing to the association between hearing impairment and adverse health.