Total volume of physical activity: TAC, TLAC or TAC( λ )

Varma, Vijay R.; Dey, Debangan; Leroux, Andrew; Di, Junrui; Urbanek, Jacek; Xiao, Luo; Zipunnikov, Vadim

doi:10.1016/j.ypmed.2017.10.028

Cited by 23 publications

(23 citation statements)

References 7 publications

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“…In addition, we considered total activity counts (TAC) which measure volume of activity. In contrast to total log activity counts (TLAC) which is associated with low/light activities, TAC is more highly associated with moderate/vigorous activities [32].…”

Section: Prediction Of Mortality In Nhanesmentioning

confidence: 94%

Organizing and Analyzing the Activity Data in NHANES

et al. 2019

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The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because: 1) currently, there are no agreed upon standard protocols for data storage and analysis; 2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to weartime protocols; 3) sampling weights need to be carefully adjusted and accounted for in individual analyses; 4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and 5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003-2004 and 2005-2006 surveys. We also provide an NHANES data package in R, to help disseminate high quality, processed activity data combined with mortality and demographic information. Thus, we provide the tools to transition from "available data online" to "easily accessible and usable data", which substantially reduces the large upfront costs of initiating studies of association between physical activity and human health outcomes using NHANES. We apply these tools in an analysis showing that accelerometry features have the potential to predict 5-year all cause mortality better than known risk factors such as age, cigarette smoking, and various comorbidities.

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Section: Prediction Of Mortality In Nhanesmentioning

confidence: 94%

Organizing and Analyzing the Activity Data in NHANES

et al. 2019

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“… 17 , 21 We calculated 3 novel metrics of physical activity: log-transformed total activity counts, total log-transformed activity counts, and physical activity fragmentation. 9 , 10 , 11 Total activity counts and total log-transformed activity counts are cutoff-free physical activity summaries that have been shown to be highly correlated with and share the same distribution with time spent in moderate-to-vigorous physical activity and light-intensity physical activity, respectively, in NHANES. 9 Log-transformed total activity counts were calculated by taking the logarithm of total activity counts to reduce the skewness of total activity counts.…”

Section: Methodsmentioning

confidence: 99%

“…With recent advances in wearable accelerometers and methods for analyzing these data, physical activity can be measured objectively, thus yielding different parameters of physical activity. 9 These metrics include conventional summary measures of time spent in various activities (light-intensity physical activity, moderate-to-vigorous physical activity, and sedentary behaviors), as well as 3 more novel metrics, including total activity count for moderate-to-vigorous physical activity and total log-transformed activity count for light-intensity physical activity, which are cutoff-free activity count–based physical activity measures, and patterns of physical activity (ie, activity-to-sedentary transition probability), which reflects the degree of activity fragmentation. 9 , 10 , 11 In this study, we hypothesize that hearing loss, measured by audiometry, is associated with physical activity as quantified by these 3 these novel metrics of objectively measured physical activity among the younger old population (ie, those aged 60-69 years).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Hearing Loss and Physical Activity Among US Adults Aged 60-69 Years

Kuo

Ferrucci

et al. 2021

JAMA Netw Open

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Key Points Question Is there an association between hearing loss and physical activity? Findings In this cross-sectional study that included 291 adults aged 60 to 69 years, hearing loss was associated with a worse physical activity profile, including less moderate-to-vigorous physical activity, less light-intensity activity, and a more fragmented physical activity pattern. Meaning These findings suggest that promoting physical activity among older adults with hearing loss is important, and further research is needed to investigate whether hearing loss interventions could improve physical health profiles.

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“…With aging, daily PA becomes less frequent and intense, and more fragmented, with shorter active bouts and longer bouts of sedentary or rest throughout the day (4)(5)(6)(7). Previous studies linking PA with health outcomes in older adults have mainly focused on defining the health effects of total volume or intensity of PA (4,8,9) and, more recently, bouts of sedentary behavior (10)(11)(12)(13), but the compensatory changes that mark the transition from active to sedentary states, and their relationship to health and functional status with aging, is not well understood.…”

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confidence: 99%

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

Schrack

Kuo

Wanigatunga

et al. 2018

The Journals of Gerontology: Series A

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Background: With aging, daily physical activity (PA) becomes less frequent and more fragmented. Accumulation patterns of daily PAincluding 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-andabove 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.

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Total volume of physical activity: TAC, TLAC or TAC( λ )

Cited by 23 publications

References 7 publications

Organizing and Analyzing the Activity Data in NHANES

Organizing and Analyzing the Activity Data in NHANES

Analysis of Hearing Loss and Physical Activity Among US Adults Aged 60-69 Years

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

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