2017
DOI: 10.1016/j.ypmed.2017.05.030
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Re-evaluating the effect of age on physical activity over the lifespan

Abstract: Advancements in accelerometer analytic and visualization techniques allow researchers to more precisely identify and compare critical periods of physical activity (PA) decline by age across the lifespan, and describe how daily PA patterns may vary across age groups. We used accelerometer data from the 2003–2006 cohorts of the National Health and Nutrition Examination Survey (NHANES) (n = 12,529) to quantify total PA as well as PA by intensity across the lifespan using sex-stratified, age specific percentile cu… Show more

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Cited by 107 publications
(105 citation statements)
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References 45 publications
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“…Sedentary behavior is a significant risk factor for a wide range of chronic diseases, comorbidities, and mortality [110]. As people age, sedentary behaviors increase [7,11,12]. However, little is known about the detailed changes in daily sedentary patterns that accompany these shifts.…”
Section: Introductionmentioning
confidence: 99%
“…Sedentary behavior is a significant risk factor for a wide range of chronic diseases, comorbidities, and mortality [110]. As people age, sedentary behaviors increase [7,11,12]. However, little is known about the detailed changes in daily sedentary patterns that accompany these shifts.…”
Section: Introductionmentioning
confidence: 99%
“…We thank Wolff-Hughes and colleagues for their thoughtful response (Wolff-Hughes et al, 2017) to our recently published findings (Varma et al, 2017). Wolff-Hughes et al correctly indicate that our findings, which model physical activity (PA) over the lifespan using total log-transformed activity counts (TLAC) as a proxy measure for total volume of PA, are inconsistent with their findings (Wolff-Hughes et al, 2014; Wolff-Hughes et al, 2015) that use total (non-transformed) activity counts (TAC).…”
Section: Introductionmentioning
confidence: 84%
“…There is an approximate 10-fold difference in the median daily percent of MVPA compared to LiPA among youth and older adults, and the largest contributor to total PA is LiPA accumulated across the day. Our decision to use TLAC in our paper (Varma et al, 2017) was based partially on this observation. It is important to additionally note that our results showing trends in MVPA across the lifespan very closely match the results from Wolf-Hughes et al showing TAC in youth (Wolff-Hughes et al, 2014) and adults (Wolff-Hughes et al., 2015) further indicating TAC may closely approximate MVPA however does not adequately model the contribution of lower intensity PA.…”
Section: Total Volume Vs Intensitymentioning
confidence: 99%
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“…Thus, we had few instances of nonwear time during the 4-day assessment period. To reduce skewness in the data and be consistent with prior studies, we log-transformed minute-level activity counts by applying the transformation log(1 + activity counts) (25). We summed the log-transformed activity counts for each minute to obtain daily activity counts, a measure of total volume of physical activity per day.…”
Section: Exposure: Infant Physical Activitymentioning
confidence: 99%