Association of Total Daily Physical Activity and Fragmented Physical Activity With Mortality in Older Adults

Wanigatunga, Amal A.; Di, Junrui; Zipunnikov, Vadim; Urbanek, Jacek; Kuo, Pei Lun; Simonsick, Eleanor M.; Ferrucci, Luigi; Schrack, Jennifer A.

doi:10.1001/jamanetworkopen.2019.12352

Cited by 79 publications

(72 citation statements)

References 42 publications

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“…Describing the pattern of physical activity using active-to-sedentary transition probability provides a potential way to objectively quantify physical activity by incorporating 3 important components of physical activity: the time spent in active phase, the time spent in sedentary behaviors, and the transition between them. Previous studies 10 , 11 , 31 demonstrated that a more fragmented physical activity pattern, quantified by active-to-sedentary transition probability, is associated with slower gait speed and longer time to finish a 400-m walk independent of the total amount of physical activity, and may be more associated with risk of mortality compared with total amount of physical activity. Our study showed that both mild hearing loss and moderate or greater hearing loss were associated with a more fragmented physical activity pattern among these younger old adults.…”

Section: Discussionmentioning

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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Section: Discussionmentioning

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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“…Many investigators have developed new analytic approaches for accelerometer data in an effort to not just measure total accumulation of PA/SB time but to detect patterns in the data. Several studies have investigated patterns based on lengths of uninterrupted intervals ("bouts") and/or degree of fragmentation of PA/SB [15,22,[51][52][53][54][55][56][57]. More relevant to the current investigation, studies have also described variations in the timing of sedentary time and PA time accumulation with respect to hour of the day and/or day of the week, including differences in timing by sociodemographic factors [23,28,[58][59][60][61][62].…”

Section: Discussionmentioning

confidence: 99%

Diurnal patterns of sedentary behavior and changes in physical function over time among older women: a prospective cohort study

Reuter

Bellettiere

Liles

et al. 2020

Int J Behav Nutr Phys Act

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Background: Sedentary behavior (SB) is linked to negative health outcomes in older adults. Most studies use summary values, e.g., total sedentary minutes/day. Diurnal timing of SB accumulation may further elucidate SB-health associations. Methods: Six thousand two hundred four US women (mean age = 79 ± 7; 50% White, 34% African-American) wore accelerometers for 7-days at baseline, yielding 41,356 person-days with > 600 min/day of data. Annual follow-up assessments of health, including physical functioning, were collected from participants for 6 years. A novel two-phase clustering procedure discriminated participants' diurnal SB patterns: phase I grouped day-level SB trajectories using longitudinal k-means; phase II determined diurnal SB patterns based on proportion of phase I trajectories using hierarchical clustering. Mixed models tested associations between SB patterns and longitudinal physical functioning, adjusted for covariates including total sedentary time. Effect modification by moderate-vigorous-physical activity (MVPA) was tested. Results: Four diurnal SB patterns were identified: p1 = high-SB-throughout-the-day; p2 = moderate-SB-with-lower-morning-SB; p3 = moderate-SB-with-higher-morning-SB; p4 = low-SB-throughout-the-day. High MVPA mitigated physical functioning decline and correlated with better baseline and 6-year trajectory of physical functioning across patterns. In low MVPA, p2 had worse 6-year physical functioning decline compared to p1 and p4. In high MVPA, p2 had similar 6-year physical functioning decline compared to p1, p3, and p4. Conclusions: In a large cohort of older women, diurnal SB patterns were associated with rates of physical functioning decline, independent of total sedentary time. In particular, we identified a specific diurnal SB subtype defined by less SB earlier and more SB later in the day, which had the steepest decline in physical functioning among participants with low baseline MVPA. Thus, diurnal timing of SB, complementary to total sedentary time and MVPA, may offer additional insights into associations between SB and physical health, and provide physicians with early warning of patients at high-risk of physical function decline.

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“…It is essential as we strive to assess the physical activity of particular subjects, like the frail population in clinical practice. Recently, Wanigatunga et al [ 51 ] proposed that highly irregular habits of physical exercise might be an early indication of reduced ability culminating in premature mortality. To this end, recording the fragmentation of physical activity is a critical phenotypic predictor for the degradation in free-living patterns in physical activity correlated with mortality.…”

Section: Discussionmentioning

confidence: 99%

Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study

Bortone

Castellana

Lampignano

et al. 2020

Sensors

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Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. Resolving the differences between self-reported and objectively measured physical activity is an important surveillance challenge currently facing population health experts. The present work aims at providing the relationship between activity energy expenditure estimated from wrist-worn accelerometers and intensity of self-reported physical activity (InCHIANTI structured interview questionnaire) in a sub-cohort of a population-based study on aging in Southern Italy. Linear regression was used to test the association between measured and reported physical activity. We found that activity energy expenditure predicted clinical average levels of PA assessed through InCHIANTI classification.

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Association of Total Daily Physical Activity and Fragmented Physical Activity With Mortality in Older Adults

Cited by 79 publications

References 42 publications

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

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

Diurnal patterns of sedentary behavior and changes in physical function over time among older women: a prospective cohort study

Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study

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