scholarly journals Comparison of physical activity energy expenditure in Japanese adolescents assessed by EW4800P triaxial accelerometry and the doubly labelled water method

2013 ◽  
Vol 110 (7) ◽  
pp. 1347-1355 ◽  
Author(s):  
Kazuko Ishikawa-Takata ◽  
Kayoko Kaneko ◽  
Kayo Koizumi ◽  
Chinatsu Ito
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Precise Measurement ◽  
Physical Activity Energy Expenditure ◽  
Triaxial Accelerometer ◽  
Doubly Labelled Water ◽  
Japanese Adolescents ◽  
Percentage Of Body Fat ◽  
Percentage Difference ◽  
Activity Energy

The present study compared the accuracy of triaxial accelerometry and the doubly labelled water (DLW) method for measuring physical activity (PA) in Japanese adolescents. A total of sixty adolescents aged 12–15 years were analysed. The total energy expenditure (TEE) was measured over 7 d by the DLW method and with an EW4800P triaxial accelerometer (Panasonic Corporation). The measured (RMRm) and predicted RMR (RMRp) were 5·7 (sd 0·9) and 6·0 (sd 1·0) MJ/d, respectively. TEE measured by the DLW method and accelerometry using RMRm or RMRp were 11·0 (sd 2·6), 10·3 (sd 1·9), and 10·7 (sd 2·1) MJ/d, respectively. The PA levels (PAL) measured by the DLW method using RMRm or RMRp were 1·97 (sd 0·31) and 1·94 (sd 0·31) in subjects who exercised, and 1·85 (sd 0·27) and 1·74 (sd 0·29) in subjects who did not exercise. The percentage of body fat correlated significantly with the percentage difference between RMRmv. RMRp, TEE, PA energy expenditure (PAEE) and PAL using RMRp, and PAL using RMRm assessed by the DLW method and accelerometry. The present data showed that while accelerometry estimated TEE accurately, it did not provide the precise measurement of PAEE and PAL. The error in accelerometry was attributed to the prediction error of RMR and assessment in exercise.

The Actiheart in Adolescents: A Doubly Labelled Water Validation

2012 ◽  
Vol 24 (4) ◽  
pp. 589-602 ◽  
Author(s):  
Nerissa Campbell ◽  
Harry Prapavessis ◽  
Casey Gray ◽  
Erin McGowan ◽  
Elaine Rush ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Equation Modeling ◽  
Physical Activity Energy Expenditure ◽  
Limits Of Agreement ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Future Work ◽  
Activity Energy

Background/Objective: This study investigated the validity of the Actiheart device for estimating free-living physical activity energy expenditure (PAEE) in adolescents. Subjects/Methods: Total energy expenditure (TEE) was measured in eighteen Canadian adolescents, aged 15–18 years, by DLW. Physical activity energy expenditure was calculated as 0.9 X TEE minus resting energy expenditure, assuming 10% for the thermic effect of feeding. Participants wore the chest mounted Actiheart device which records simultaneously minute-by-minute acceleration (ACC) and heart rate (HR). Using both children and adult branched equation modeling, derived from laboratory-based activity, PAEE was estimated from the ACC and HR data. Linear regression analyses examined the association between PAEE derived from the Actiheart and DLW method where DLW PAEE served as the dependent variable. Measurement of agreement between the two methods was analyzed using the Bland-Altman procedure. Results: A nonsignificant association was found between the children derived Actiheart and DLW PAEE values (R = .23, R2 = .05, p = .36); whereas a significant association was found between the adult derived Actiheart and DLW PAEE values (R = .53, R2 = .29, p < .05). Both the children and adult equation models lead to overestimations of PAEE by the Actiheart compared with the DLW method, by a mean difference of 31.42 kcal·kg−·d−1 (95% limits of agreement: −45.70 to −17.15 kcal·kg−1·d−1 and 9.80 kcal·kg−1·d−1 (95% limits of agreement: −21.22-1.72 kcal·kg−1·d−1), respectively. Conclusion: There is relatively poor measurement of agreement between the Actiheart and DLW for assessing free-living PAEE in adolescents. Future work should develop group based branched equation models specifically for adolescents to improve the utility of the device in this population.

scholarly journals Validation of Five Minimally Obstructive Methods to Estimate Physical Activity Energy Expenditure in Young Adults in Semi-Standardized Settings

Sensors ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. 6133-6151 ◽  
Author(s):  
Mikkel Schneller ◽  
Mogens Pedersen ◽  
Nidhi Gupta ◽  
Mette Aadahl ◽  
Andreas Holtermann
Keyword(s):  
Physical Activity ◽  
Young Adults ◽  
Energy Expenditure ◽  
Physical Activity Energy Expenditure ◽  
Activity Energy

Physical activity energy expenditure and fat-free mass: Relationship with metabolic syndrome in overweight or obese postmenopausal women

2020 ◽  
Author(s):  
René Maréchal ◽  
Ahmed Ghachem ◽  
Denis Prud'Homme ◽  
Rémi Rabasa-Lhoret ◽  
Isabelle J. Dionne ◽  
...  
Keyword(s):  
Physical Activity ◽  
Metabolic Syndrome ◽  
Energy Expenditure ◽  
Postmenopausal Women ◽  
Fat Free Mass ◽  
Physical Activity Energy Expenditure ◽  
Cross Sectional ◽  
Framingham Risk ◽  
Menopause Transition ◽  
Activity Energy

Menopause transition is associated with detrimental changes in physical activity, body composition and metabolic profile. Although physical activity energy expenditure (PAEE) is inversely associated with metabolic syndrome (MetS) in individuals at higher risk of CVD, the association is unknown in low-risk individuals. The aim of the study was to investigate the association between PAEE and MetS (prevalence and severity) in inactive overweight or obese postmenopausal women with a low Framingham Risk Score (FRS:< 10%). Cross-sectional data of 126 participants were divided into quartiles based on PAEE (Q1= lowest PAEE) while fat-free mass (FFM) and fat mass (FM) were measured by DXA. MetS prevalence was significantly different between Q1 and Q4 (37.9% vs 13.3%, p= 0.03). After controlling for potential confounders, MetS severity was negatively associated with PAEE (B= -0.057, p< 0.01) and positively with FFM (B= 0.038, p< 0.001). Moderation analyses indicated that a greater FFM exacerbated the association between PAEE and MetS severity in Q1 and Q2 (PAEE*FFM; B= -0.004; p= 0.1). Our results suggest that displaying a low FRS and lower PAEE increase MetS prevalence and severity. In addition, greater FFM interacts with lower PAEE to worsens MetS severity, while higher PAEE lessened this effect. Novelty - Inactive individuals displaying higher daily PAEE also have a lower MetS prevalence - Greater fat-free mass is associated with a worse MetS severity where a higher PAEE mitigates this deleterious effect in our cohort

scholarly journals Comparison of total and activity energy expenditure estimates from physical activity questionnaires and doubly labelled water: a systematic review and meta-analysis

2020 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad Sharifzadeh ◽  
Minoo Bagheri ◽  
John R. Speakman ◽  
Kurosh Djafarian
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Weighted Mean Difference ◽  
Meta Analysis ◽  
Mean Difference ◽  
Weighted Mean ◽  
Doubly Labelled Water ◽  
Significant Difference ◽  
Activity Questionnaires ◽  
Activity Energy

Abstract Physical activity questionnaires (PAQ) could be suitable tools in free-living people for measures of physical activity, total and activity energy expenditure (TEE and AEE). This meta-analysis was performed to determine valid PAQ for estimating TEE and AEE using doubly labelled water (DLW). We identified data from relevant studies by searching Google Scholar, PubMed and Scopus databases. This revealed thirty-eight studies that had validated PAQ with DLW and reported the mean differences between PAQ and DLW measures of TEE (TEEDLW − TEEPAQ) and AEE (AEEDLW − AEEPAQ). We assessed seventy-eight PAQ consisting of fifty-nine PAQ that assessed TEE and thirty-five PAQ that examined AEE. There was no significant difference between TEEPAQ and TEEDLW with a weighted mean difference of –243·3 and a range of –841·4 to 354·6 kJ/d, and a significant weighted mean difference of AEEDLW – AEE PAQ 414·6 and a range of 78·7–750·5. To determine whether any PAQ was a valid tool for estimating TEE and AEE, we carried out a subgroup analysis by type of PAQ. Only Active-Q, administered in two seasons, and 3-d PA diaries were correlated with TEE by DLW at the population level; however, these two PAQ did not demonstrate an acceptable limit of agreement at individual level. For AEE, no PAQ was correlated with DLW either at the population or at the individual levels. Active-Q and 3-d PA diaries were identified as the only valid PAQ for TEE estimation. Further well-designed studies are needed to verify this result and identify additional valid PAQ.

scholarly journals Descriptive epidemiology of physical activity energy expenditure in UK adults (The Fenland study)

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Tim Lindsay ◽  
Kate Westgate ◽  
Katrien Wijndaele ◽  
Stefanie Hollidge ◽  
Nicola Kerrison ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Vigorous Physical Activity ◽  
Large Population ◽  
Population Based ◽  
Normal Weight ◽  
Physical Activity Energy Expenditure ◽  
Cardiometabolic Disorders ◽  
Sociodemographic Correlates ◽  
Activity Energy

Abstract Background Physical activity (PA) plays a role in the prevention of a range of diseases including obesity and cardiometabolic disorders. Large population-based descriptive studies of PA, incorporating precise measurement, are needed to understand the relative burden of insufficient PA levels and to inform the tailoring of interventions. Combined heart and movement sensing enables the study of physical activity energy expenditure (PAEE) and intensity distribution. We aimed to describe the sociodemographic correlates of PAEE and moderate-to-vigorous physical activity (MVPA) in UK adults. Methods The Fenland study is a population-based cohort study of 12,435 adults aged 29–64 years-old in Cambridgeshire, UK. Following individual calibration (treadmill), participants wore a combined heart rate and movement sensor continuously for 6 days in free-living, from which we derived PAEE (kJ•day− 1•kg− 1) and time in MVPA (> 3 & > 4 METs) in bouts greater than 1 min and 10 min. Socio-demographic information was self-reported. Stratum-specific summary statistics and multivariable analyses were performed. Results Women accumulated a mean (sd) 50(20) kJ•day− 1•kg− 1 of PAEE, and 83(67) and 33(39) minutes•day− 1 of 1-min bouted and 10-min bouted MVPA respectively. By contrast, men recorded 59(23) kJ•day− 1•kg− 1, 124(84) and 60(58) minutes•day− 1. Age and BMI were also important correlates of PA. Association with age was inverse in both sexes, more strongly so for PAEE than MVPA. Obese individuals accumulated less PA than their normal-weight counterparts, whether considering PAEE or allometrically-scaled PAEE (− 10 kJ•day− 1•kg− 1 or − 15 kJ•day− 1•kg-2/3 in men). Higher income and manual work were associated with higher PA; manual workers recorded 13–16 kJ•kg− 1•day− 1 more PAEE than sedentary counterparts. Overall, 86% of women and 96% of men accumulated a daily average of MVPA (> 3 METs) corresponding to 150 min per week. These values were 49 and 74% if only considering bouts > 10 min (15 and 31% for > 4 METs). Conclusions PA varied by age, sex and BMI, and was higher in manual workers and those with higher incomes. Light physical activity was the main driver of PAEE; a component of PA that is currently not quantified as a target in UK guidelines.

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