Validity of GT3X and Actiheart to estimate sedentary time and breaks using ActivPAL as the reference in free-living conditions

Júdice, Pedro B.; Santos, Diana A.; Hamilton, Marc T.; Sardinha, Luís B.; Silva, Analiza M.

doi:10.1016/j.gaitpost.2015.03.326

Cited by 55 publications

(32 citation statements)

References 31 publications

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“…The ActiGraph Inclinometer function on the hip accelerometer did not perform more favorably than the other ActiGraph methods. These findings are similar to those in adult samples that showed poor validity for using accelerometer cut points to assess sit-to-stand transitions (4, 16, 20, 23). …”

Section: Discussionsupporting

confidence: 85%

“…Few studies have investigated accelerometers for assessing sit-to-stand transitions (4, 12, 16, 20, 23), and limitations of these studies were that all were in adults. The current study extended the previous literature by examining both epoch-level and hour-level validity of these measures in youth with overweight and obesity, a population frequently targeted for intervention (3).…”

Section: Discussionmentioning

confidence: 99%

“…Each of these studies found that hip-worn accelerometers substantially overestimated the number of sit-to-stand transitions as compared to activPAL (4, 16) or direct observation (20, 23). Few studies were identified that investigated the validity of the thigh-worn activPAL for measuring sit-to-stand transitions.…”

Section: Introductionmentioning

confidence: 99%

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Using Activity Monitors to Measure Sit-to-Stand Transitions in Overweight/Obese Youth

Mitchell

Borner

Finch

et al. 2017

Medicine &Amp; Science in Sports &Amp; Exercise

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Introduction Reducing sedentary behavior has emerged as an important health intervention strategy. Although hip-worn, and more recently wrist-worn, accelerometers are commonly used for measuring physical activity and sedentary behavior, they may not provide accurate measures of postural changes. The current study examined the validity of commonly used hip- and wrist-worn accelerometer cut points and the thigh-worn activPAL activity monitor for measuring sit-to-stand transitions as compared to direct observation in youth with overweight and obesity. Methods Nine children wore three activity monitors while being directly observed. The monitors included a hip- and wrist-worn ActiGraph and thigh-worn activPAL. The hip-worn ActiGraph was processed with the normal and low frequency filters and the inclinometer function. Cut points of ≤25 counts per 15-second epoch for the hip, and ≤105 counts per 15-second epoch for the wrist were applied to the vertical axis to identify sit-to-stand transitions. Epoch-level absolute agreement, Bland-Altman plots, mixed-effects linear regression, and Intraclass Correlation Coefficients (ICCs) were investigated. Results The hip and wrist accelerometer cut points and hip inclinometer function overestimated the number of hourly sit-to-stand transitions by approximately triple as compared to direct observation. ICCs between the ActiGraph methods and direct observation were all <0.12. Sit-to-stand transitions assessed from ActivPAL were within 17% of direct observation; ICC was 0.26. Conclusion Despite the common use of the 100 count hip-worn accelerometer cut point for assessing sedentary time, these processing decisions should be used with caution for assessing sit-to-stand transitions. Future research should investigate other processing methods for ActiGraph data, and studies investigating postural changes should consider including devices such as activPALs.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

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Using Activity Monitors to Measure Sit-to-Stand Transitions in Overweight/Obese Youth

Mitchell

Borner

Finch

et al. 2017

Medicine &Amp; Science in Sports &Amp; Exercise

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“…A limitation of our study is that the assessment of movement behavior by the Actiheart ® monitor, which combines information of heart rate and body movements, may overestimate LPA and underestimate ST because not only PA but also sympathetic activation at rest increases heart rate. [47][48][49] In case of some children, it may also have been difficult to determine the time of falling asleep or waking up which may entail some error into ST estimation. Moreover, Actiheart ® is a device for measuring the intensity and energy expenditure of PA but not different types of PA that reflect PA as a behavior.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal associations of physical activity and sedentary time with cardiometabolic risk factors in children

Väistö

Haapala

Viitasalo

et al. 2018

Scandinavian Med Sci Sports

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Background There are few prospective studies on the associations of changes in objectively measured vigorous physical activity (VPA∆), moderate-to-vigorous physical activity (MVPA∆), light physical activity (LPA∆), and sedentary time (ST∆) with changes in cardiometabolic risk factors (∆) in children. We therefore investigated these relationships among children. Methods The participants were a population sample of 258 children aged 6–8 years followed for 2 years. We assessed PA and ST by a combined heart rate and movement sensor; computed continuous age- and sex-adjusted z-scores for waist circumference, blood pressure, and fasting insulin, glucose, triglycerides, and high-density lipoprotein (HDL) cholesterol; and constructed a cardiometabolic risk score (CRS) of these risk factors. Data were analysed using linear regression models adjusted for age, sex, the explanatory and outcome variables at baseline, and puberty. Results VPA∆ associated inversely with CRS∆ (β=-0.209, p=0.001), body fat percentage (BF%)∆ (β=-0.244, p=0.001), insulin∆ (β=-0.220, p=0.001), and triglycerides∆ (β=-0.164, p=0.012) and directly with HDL cholesterol∆ (β=0.159, p=0.023). MVPA∆ associated inversely with CRS∆ (β=-0.178, p=0.012), BF%∆ (β=-0.298, p=<0.001), and insulin∆ (β=-0.213, p=0.006) and directly with HDL cholesterol∆ (β=0.184, p=0.022). LPA∆ only associated negatively with CRS∆ (β=-0.163, p=0.032). ST∆ associated directly with CRS∆ (β=0.218, p=0.003), BF%∆ (β=0.212, p=0.016), and insulin∆ (β=0.159, p=0.049). Conclusions Increased VPA and MVPA and decreased ST were associated with reduced overall cardiometabolic risk and major individual risk factors. Change in LPA had weaker associations with changes in these cardiometabolic risk factors. Our findings suggest that increasing at least moderate-intensity PA and decreasing ST decrease cardiometabolic risk in children.

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“…activPAL ™ is considered the reference method for estimating sedentary time in free-living individuals [54]. The inclinometer function is used to detect posture and thus can distinguish between sitting and standing.…”

Section: Methodsmentioning

confidence: 99%

Dietary Intervention for Glucose Tolerance In Teens (DIG IT): Protocol of a randomized controlled trial using health coaching to prevent youth-onset type 2 diabetes

Wagner

Braun

Armah

et al. 2017

Contemporary Clinical Trials

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Background Youth-onset type 2 diabetes (T2D) is a disease that is newly emerging and behavioral strategies for its prevention are limited. Interventions that target the lifestyle behaviors of adolescents, to improve poor dietary quality and reduce excessive sedentariness, promise to reduce the risk of developing T2D. Health coaching is effective for promoting healthy behaviors in patients who have chronic disease, but few experimental studies are in adolescents. This randomized controlled trial, in adolescents with prediabetes, will determine the effectiveness of a health coaching intervention to facilitate adoption of healthy diet and activity behaviors that delay or prevent development of T2D. Methods/design The Dietary Intervention for Glucose Tolerance In Teens (DIG IT) trial will involve an evaluation of a health coaching intervention in adolescents with prediabetes. Eligible participants will be randomized to receive 6 months of health coaching or a single dietary consultation that is standard-of-care. The primary outcome will be 2-hour oral glucose tolerance test concentration. Secondary outcomes will include measures of glycemia and insulin action as well as dietary, physical activity and sedentary behaviors measured using an electronic food record, and by inclinometer. Data will be collected before and after the intervention (at 6 months) and at 12 months (to assess sustainability). Discussion This trial will determine whether a health coaching intervention, a personalized and low-cost approach to modify dietary and activity behaviors, is effective and sustainable for prevention of youth-onset T2D, relative to standard-of-care. Health coaching has the potential to be widely implemented in clinical or community settings.

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Validity of GT3X and Actiheart to estimate sedentary time and breaks using ActivPAL as the reference in free-living conditions

Cited by 55 publications

References 31 publications

Using Activity Monitors to Measure Sit-to-Stand Transitions in Overweight/Obese Youth

Using Activity Monitors to Measure Sit-to-Stand Transitions in Overweight/Obese Youth

Longitudinal associations of physical activity and sedentary time with cardiometabolic risk factors in children

Dietary Intervention for Glucose Tolerance In Teens (DIG IT): Protocol of a randomized controlled trial using health coaching to prevent youth-onset type 2 diabetes

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