Dataset Information

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

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.

SUBMITTER: Lindsay T

PROVIDER: S-EPMC6902569 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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

Lindsay Tim T Westgate Kate K Wijndaele Katrien K Hollidge Stefanie S Kerrison Nicola N Forouhi Nita N Griffin Simon S Wareham Nick N Brage Søren S

The international journal of behavioral nutrition and physical activity 20191209 1

<h4>Background</h4>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 ...[more]

PMID: 31818302

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Project description:BackgroundLittle is known about population levels of energy expenditure, as national surveillance systems typically employ only crude measures. The National Diet and Nutrition Survey (NDNS) in the UK measured energy expenditure in a 10% subsample by gold-standard doubly labelled water (DLW).MethodsDLW-subsample participants from the NDNS (383 males, 387 females) aged 4-91 years were recruited between 2008 and 2015 (rolling programme). Height and weight were measured and body-fat percentage estimated by deuterium dilution.ResultsAbsolute total energy expenditure (TEE) increased steadily throughout childhood, ranging from 6.2 and 7.2 MJ/day in 4- to 7-year-olds to 9.7 and 11.7 MJ/day for 14- to 16-year-old girls and boys, respectively. TEE peaked in 17- to 27-year-old women (10.7 MJ/day) and 28- to 43-year-old men (14.4 MJ/day), before decreasing gradually in old age. Physical-activity energy expenditure (PAEE) declined steadily with age from childhood (87 kJ/day/kg in 4- to 7-year-olds) through to old age (38 kJ/day/kg in 71- to 91-year-olds). No differences were observed by time, region and macronutrient composition. Body-fat percentage was strongly inversely associated with PAEE throughout life, irrespective of expressing PAEE relative to body mass or fat-free mass. Compared with females with <30% body fat, females with >40% recorded 29 kJ/day/kg body mass and 18 kJ/day/kg fat-free mass less PAEE in analyses adjusted for age, geographical region and time of assessment. Similarly, compared with males with <25% body fat, males with >35% recorded 26 kJ/day/kg body mass and 10 kJ/day/kg fat-free mass less PAEE.ConclusionsThis first nationally representative study reports levels of human-energy expenditure as measured by gold-standard methodology; values may serve as a reference for other population studies. Age, sex and body composition are the main determinants of energy expenditure. Key Messages This is the first nationally representative study of human energy expenditure, covering the UK in the period 2008-2015. Total energy expenditure (MJ/day) increases steadily with age throughout childhood and adolescence, peaks in the 3rd decade of life in women and 4th decade of life in men, before decreasing gradually in old age. Physical activity energy expenditure (kJ/day/kg or kJ/day/kg fat-free mass) declines steadily with age from childhood to old age, more steeply so in males. Body-fat percentage is strongly inversely associated with physical activity energy expenditure. We found little evidence that energy expenditure varied by geographical region, over time, or by dietary macronutrient composition.

Project description:BackgroundPhysical exercise interventions have been extensively advocated for the treatment of obesity; however, clinical trials evaluating the effectiveness of exercise interventions on weight control show controversial results. Compensatory mechanisms through a decrease in energy expenditure and/or an increase in caloric consumption is a possible explanation. Several physiological mechanisms involved in the energy balance could explain compensatory mechanisms, but the influences of physical exercise on these adjustments are still unclear. Therefore, the present trial aims to evaluate the effects of exercise on non-exercise physical activity energy expenditure, energy intake and appetite sensations among active overweight/obese adults, as well as, to investigate hormonal changes associated with physical exercise.MethodsThis study is a randomized controlled trial with parallel, three-group experimental arms. Eighty-one overweight/obese adults will be randomly allocated (1:1:1 ratio) to a vigorous exercise group, moderate exercise group or control group. The trial will be conducted at a military institution and the intervention groups will be submitted to exercise sessions in the evening, three times a week for 65 min, during a 2-week period. The primary outcome will be total spontaneous physical activity energy expenditure during a 2-week period. Secondary outcomes will be caloric intake, appetite sensations and laboratorial biomarkers. Intention-to-treat analysis will be performed using linear mixed-effects models to evaluate the effect of treatment-by-time interaction on primary and secondary outcomes. Data analysis will be performed using SAS 9.3 and statistical significance will be set at p?<?0.05.DiscussionThe results of the present study will help to understand the effect of physical exercise training on subsequent non-exercise physical activity, appetite and energy intake as well as understand the physiological mechanisms underlying a possible compensatory phenomenon, supporting the development of more effective interventions for prevention and treatment of obesity.Trial registrationPhysical Exercise and Energy Balance trial registry, trial registration number: NCT 03138187 . Registered on 30 April 2017.

Project description:Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels.Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves.On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA.The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate/vigorous levels of PA in preschoolers.

Project description:BackgroundResearch has shown the feasibility of human activity recognition using wearable accelerometer devices. Different studies have used varying numbers and placements for data collection using sensors.ObjectiveThis study aims to compare accuracy performance between multiple and variable placements of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults.MethodsIn total, 93 participants (mean age 72.2 years, SD 7.1) completed a total of 32 activities of daily life in a laboratory setting. Activities were classified as sedentary versus nonsedentary, locomotion versus nonlocomotion, and lifestyle versus nonlifestyle activities (eg, leisure walk vs computer work). A portable metabolic unit was worn during each activity to measure metabolic equivalents (METs). Accelerometers were placed on 5 different body positions: wrist, hip, ankle, upper arm, and thigh. Accelerometer data from each body position and combinations of positions were used to develop random forest models to assess activity category recognition accuracy and MET estimation.ResultsModel performance for both MET estimation and activity category recognition were strengthened with the use of additional accelerometer devices. However, a single accelerometer on the ankle, upper arm, hip, thigh, or wrist had only a 0.03-0.09 MET increase in prediction error compared with wearing all 5 devices. Balanced accuracy showed similar trends with slight decreases in balanced accuracy for the detection of locomotion (balanced accuracy decrease range 0-0.01), sedentary (balanced accuracy decrease range 0.05-0.13), and lifestyle activities (balanced accuracy decrease range 0.04-0.08) compared with all 5 placements. The accuracy of recognizing activity categories increased with additional placements (accuracy decrease range 0.15-0.29). Notably, the hip was the best single body position for MET estimation and activity category recognition.ConclusionsAdditional accelerometer devices slightly enhance activity recognition accuracy and MET estimation in older adults. However, given the extra burden of wearing additional devices, single accelerometers with appropriate placement appear to be sufficient for estimating energy expenditure and activity category recognition in older adults.

Dataset Information

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

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

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