Accelerometer Derived Activity Counts and Oxygen Consumption between Young and Older Individuals

Whitcher, Lucas; Papadopoulos, Charilaos

doi:10.1155/2014/184693

Cited by 10 publications

(12 citation statements)

References 24 publications

(49 reference statements)

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“…2). Whitcher et al [36] found that oxygen consumption during walking exercise was greater among an elderly group than a younger group, even though activity counts were similar between the 2 groups. Table 4 shows that both LPA locomotive time determined by the ACC and walking time estimated by the questionnaire were significantly higher in the high PAL group compared with the other groups, which is one of the reasons why PAL ACC tended to be underestimated in high PAL DLW group.…”

Section: Discussion/conclusionmentioning

confidence: 98%

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study

et al. 2020

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Introduction: Evaluation of total energy expenditure (TEE) and physical activity level (PAL) is important for treatment of patients with type 2 diabetes mellitus (T2DM). However, the validity of accelerometers (ACC) and physical activity questionnaires (PAQ) for estimating TEE and PAL remains unknown in elderly populations with T2DM. We evaluated the accuracy of TEE and PAL results estimated by an ACC (TEE ACC and PAL ACC ) and a PAQ (TEE PAQ and PAL PAQ ) in elderly patients with T2DM. Methods: Fifty-one elderly patients with T2DM (aged 61-79 years) participated in this study. TEE ACC was calculated with PAL ACC using a triaxial ACC (Active style Pro HJA-750c) over 2 weeks and predicted basal metabolic rate (BMR) by Ganpule's equation. TEE PAQ was estimated using predicted BMR and the PAL PAQ from the Japan Public Health Center Study-Long questionnaire. We compared the results to TEE DLW measured with the doubly labeled water (DLW) method and PAL DLW calculated with BMR using indirect calorimetry. Results: TEE DLW was 2,165 ± 365 kcal/day, and TEE ACC was 2,014 ± 339 kcal/day; TEE ACC was strongly correlated with TEE DLW (r = 0.87, p < 0.01) but Physical Activity Estimated by Triaxial ACC and Questionnaire 63 Ann Nutr Metab 2020;76:62-72 significantly underestimated (-150 ± 183 kcal/day, p < 0.05). There was no significant difference in TEE PAQ and TEE DLW (-49 ± 284 kcal/day), while the range of difference seemed to be larger than TEE ACC . PAL DLW , PAL ACC , and PAL PAQ were calculated to be 1.71 ± 0.17, 1.69 ± 0.16, and 1.78 ± 0.24, respectively. PAL ACC was strongly correlated with PAL DLW (r = 0.71, p < 0.01), and there was no significant difference between the 2 values. PAL PAQ was moderately correlated with PAL DLW (r = 0.43, p < 0.01) but significantly overestimated. Predicted BMR was significantly lower than the BMR measured by indirect calorimetry (1,193 ± 186 vs. 1,262 ± 155 kcal/day, p < 0.01). Conclusions: The present ACC and questionnaire showed acceptable correlation of TEE and PAL compared with DLW method in elderly patients with T2DM. Systematic errors in estimating TEE may be improved by the better equation for predicting BMR.

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Section: Discussion/conclusionmentioning

confidence: 98%

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study

et al. 2020

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“…Some studies have also used other means of estimating EE, such as direct observation, video recordings, or use of the PA compendium. EE is expressed relative to the standard unit of resting metabolism [metabolic equivalent (MET)], and typically, 1.5, 3, and 6 METs are considered the thresholds between sedentary, LPA, MPA, and VPA (Copeland and Esliger, 2009 ) (although some studies have used 4 and 7 METs for the latter two) (Gorman et al, 2014 ; Whitcher and Papadopoulos, 2014 ; Evenson et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

“…ActiGraph devices prior to the GT3X provide results not in terms of raw acceleration, but in so-called counts , which are filtered signals, with the filtering parameters kept undisclosed by ActiGraph. For the hip-worn ActiGraph GT3X (ActiGraph, Pensacola, FL) accelerometer, ActiGraph count cutpoints have been compared in older (66.6 ± 2.9 years) and younger (21 ± 2.5 years) adults, with 824 and 2,207 counts · min −1 , respectively, associated with moderate-intensity (3 METs) activity (Whitcher and Papadopoulos, 2014 ). However, few studies have reported cutpoints for older adults (Gorman et al, 2014 ; Whitcher and Papadopoulos, 2014 ; Evenson et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Physical Activity Intensity Cut-Points for Wrist-Worn GENEActiv in Older Adults

Fraysse¹,

Post²,

Eston³

et al. 2021

Front. Sports Act. Living

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Purpose: This study aims to (1) establish GENEActiv intensity cutpoints in older adults and (2) compare the classification accuracy between dominant (D) or non-dominant (ND) wrist, using both laboratory and free-living data.Methods: Thirty-one older adults participated in the study. They wore a GENEActiv Original on each wrist and performed nine activities of daily living. A portable gas analyzer was used to measure energy expenditure for each task. Testing was performed on two occasions separated by at least 8 days. Some of the same participants (n = 13) also wore one device on each wrist during 3 days of free-living. Receiver operating characteristic analysis was performed to establish the optimal cutpoints.Results: For sedentary time, both dominant and non-dominant wrist had excellent classification accuracy (sensitivity 0.99 and 0.97, respectively; specificity 0.91 and 0.86, respectively). For Moderate to Vigorous Physical Activity (MVPA), the non-dominant wrist device had better accuracy (ND sensitivity: 0.90, specificity 0.79; D sensitivity: 0.90, specificity 0.64). The corresponding cutpoints for sedentary-to-light were 255 and 375 g · min (epoch independent: 42.5 and 62.5 mg), and those for the light-to-moderate were 588 and 555 g · min (epoch-independent: 98.0 and 92.5 mg) for the non-dominant and dominant wrist, respectively. For free-living data, the dominant wrist device resulted in significantly more sedentary time and significantly less light and MVPA time compared to the non-dominant wrist.

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“…Both are higher than the accepted MVPA cut point intensity of 3 METs. The two previous studies that used measured RMR when examining the relationship between VA accelerometer (ActiGraph GT3X) counts and the 3 MET cut point specifically for walking in older adults have limitations [12, 31]. These included small sample sizes (20 and 15 older adults) and the use of treadmill walking in the determination of speed, energy expenditure and accelerometer count relationships [20].…”

Section: Introductionmentioning

confidence: 99%

Measuring moderate-intensity walking in older adults using the ActiGraph accelerometer

et al. 2016

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BackgroundAccelerometry is the method of choice for objectively assessing physical activity in older adults. Many studies have used an accelerometer count cut point corresponding to 3 metabolic equivalents (METs) derived in young adults during treadmill walking and running with a resting metabolic rate (RMR) assumed at 3.5 mL · kg−1 · min−1 (corresponding to 1 MET). RMR is lower in older adults; therefore, their 3 MET level occurs at a lower absolute energy expenditure making the cut point derived from young adults inappropriate for this population. The few studies determining older adult specific moderate-to-vigorous intensity physical activity (MVPA) cut points had methodological limitations, such as not measuring RMR and using treadmill walking.MethodsThis study determined a MVPA hip-worn accelerometer cut point for older adults using measured RMR and overground walking. Following determination of RMR, 45 older adults (mean age 70.2 ± 7 years, range 60–87.6 years) undertook an outdoor, overground walking protocol with accelerometer count and energy expenditure determined at five walking speeds.ResultsMean RMR was 2.8 ± 0.6 mL · kg−1 · min−1. The MVPA cut points (95% CI) determined using linear mixed models were: vertical axis 1013 (734, 1292) counts · min−1; vector magnitude 1924 (1657, 2192) counts · min−1; and walking speed 2.5 (2.2, 2.8) km · hr−1. High levels of inter-individual variability in cut points were found.ConclusionsThese MVPA accelerometer and speed cut points for walking, the most popular physical activity in older adults, were lower than those for younger adults. Using cut points determined in younger adults for older adult population studies is likely to underestimate time spent engaged in MVPA. In addition, prescription of walking speed based on the adult cut point is likely to result in older adults working at a higher intensity than intended.

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Accelerometer Derived Activity Counts and Oxygen Consumption between Young and Older Individuals

Cited by 10 publications

References 24 publications

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study

Physical Activity Intensity Cut-Points for Wrist-Worn GENEActiv in Older Adults

Measuring moderate-intensity walking in older adults using the ActiGraph accelerometer

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