scholarly journals Validity and reliability of Nike + Fuelband for estimating physical activity energy expenditure

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Wesley J. Tucker ◽  
Dharini M. Bhammar ◽  
Brandon J. Sawyer ◽  
Matthew P. Buman ◽  
Glenn A. Gaesser
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Physical Activity Energy Expenditure ◽  
Validity And Reliability ◽  
Activity Energy

Influence of Accelerometer Type and Placement on Physical Activity Energy Expenditure Prediction During WheelChair

2014 ◽  
Vol 46 ◽  
pp. 791-792
Author(s):  
Tom E. Nightingale ◽  
Jean-Philippe Walhin ◽  
Dylan Thompson ◽  
James L.J. Bilzon
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Physical Activity Energy Expenditure ◽  
Activity Energy

scholarly journals Physical Activity, Energy Expenditure and Work Intensity of Care‐Workers on Shift Work in a Special Nursing Home for the Elderly

2002 ◽  
Vol 44 (1) ◽  
pp. 8-14 ◽  
Author(s):  
Tadaaki Wakui ◽  
Setsuko Shirono ◽  
Seiichiro Takahashi ◽  
Takae Fujimura ◽  
Noriaki Harada
Keyword(s):  
Physical Activity ◽  
Nursing Home ◽  
Energy Expenditure ◽  
Shift Work ◽  
The Elderly ◽  
Physical Activity Energy Expenditure ◽  
Work Intensity ◽  
Care Workers ◽  
Intensity Of Care ◽  
Activity Energy

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 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.

Comparison of Lifecorder and MTI ActiGraph Accelerometer Estimates of Measuring Physical Activity Energy Expenditure

2006 ◽  
Vol 38 (Supplement) ◽  
pp. S103
Author(s):  
Tracy L. Washington ◽  
Cora L. Craig ◽  
James J. McClain ◽  
Susan S. Sisson ◽  
Catrine Tudor-Locke
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Physical Activity Energy Expenditure ◽  
Actigraph Accelerometer ◽  
Activity Energy
Sign in / Sign up

Export Citation Format

Share Document