Assessment of free-living physical activity in humans: an overview of currently available and proposed new measures

Exercise Intensity and Activity Energy Expenditure of Professional Golf Players in Official Competitive Setting

BACKGROUND

Research regarding the physical needs of professional golf players is lacking. With advances in wearable technology, it has become easier to analyze physiological responses such as heart rate (HR) to determine activity energy expenditure (AEE). The purpose of the study was to evaluate exercise intensity (EI) and AEE during 4 consecutive tournament's golf rounds using a popular wrist-based HR monitoring.

HYPOTHESIS

Wearable systems for HR monitoring can be used to provide an accurate estimate of energy expenditure.

STUDY DESIGN

Cross-sectional study.

LEVEL OF EVIDENCE

Level 3.

METHODS

A total of 20 male professional golfers participated in the study. Each player was monitored during an official tournament consisting of 4 rounds of 18 holes. EI and AEE were determined using HR wrist monitoring (Whoop Strap 2.0). We calculated the percentage of HRmax (%HRmax) and the percentage of HRres (%HRres) and the AEE in kcal/min using Keytel's formula.

RESULTS

The calculated mean %HRmax and %HRres for the study population were 56.4% ± 1.8% and 40.5% ± 2.6%, respectively. Considering American College of Sports Medicine guidelines, these average percentages correspond to a moderate EI. The average caloric expenditure was 5.4 ± 0.4 kcal/min and 1555.8 ± 157.8 kcal per round considering an average golf round duration of 288.3 ± 19.5 minutes.

CONCLUSION

A professional player's golf round is moderate physical activity. The AEE of this activity was equal to 5.4 cal/min, which is moderate energy consumption.

CLINICAL RELEVANCE

These data could help golf coaches and conditioning coaches to have a better understanding of the load placed on golfers during tournaments.

Movement efficiency in survivors of childhood acute lymphoblastic leukemia: a report from the St. Jude lifetime cohort study

PURPOSE

Movement efficiency, a measure of neuromuscular biomechanics, may be modified by physical activity. We aimed to assess the risk of and risk factors for low movement efficiency in survivors of childhood acute lymphoblastic leukemia (ALL).

METHODS

Participants underwent an assessment of activity energy expenditure (AEE) with actigraphy, and the gold standard doubly labeled water, where the differences between elimination rates of oxygen and hydrogen from body water are evaluated over a week. Movement efficiency was assessed using the raw residuals of a linear regression between AEEs from accelerometers and doubly labeled water. Elastic-net logistic regressions were used to identify demographic, treatment, and functional variables associated with movement efficiency.

RESULTS

The study cohort included 256 non-cancer controls and 302 ALL survivors (48% female), categorized as efficient (N = 24), normal (N = 245), or inefficient (N = 33) based on their movement efficiency. There was no difference in the odds for poor movement efficiency between survivors (n = 33, 10.9%) compared to controls (n = 23, 9.0%, odds ratio [OR]: 1.19, 95% confidence interval [CI]: 0.67, 2.10; p = 0.55). In survivors, neuropathy was associated with a higher risk of being inefficient compared to efficient (OR 4.30, 95% CI 1.03-17.96), while obesity (≥ 30 kg/m2) had a protective association (OR 0.18, 95% CI 0.04-0.87).

CONCLUSIONS

Neuropathy was associated with a higher risk of poor movement efficiency in survivors of childhood ALL.

IMPLICATIONS FOR CANCER SURVIVORS

These results further highlight impairments associated with treatment-induced neuropathy in survivors of childhood ALL.

Associations between changes of smartphone pedometer-assessed step counts and levels of obesity-related breast cancer biomarkers in non-cancer women: A population-based observational study

While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level (β=-0.74, 95%CI=-1.23--0.26, P-value = 2.98 × 10-3). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

Sensitivity and specificity of measuring children's free-living cycling with a thigh-worn Fibion® accelerometer

Objective

Cycling is an important part of children's active travel, but its measurement using accelerometry is a challenge. The aim of the present study was to evaluate physical activity duration and intensity, and sensitivity and specificity of free-living cycling measured with a thigh-worn accelerometer.

Methods

Participants were 160 children (44 boys) aged 11.5 ± 0.9 years who wore a triaxial Fibion® accelerometer on right thigh for 8 days, 24 h per day, and reported start time and duration of all cycling, walking and car trips to a travel log. Linear mixed effects models were used to predict and compare Fibion-measured activity and moderate-to-vigorous activity duration, cycling duration and metabolic equivalents (METs) between the travel types. Sensitivity and specificity of cycling bouts during cycling trips as compared to walking and car trips was also evaluated.

Results

Children reported a total of 1,049 cycling trips (mean 7.08 ± 4.58 trips per child), 379 walking trips (3.08 ± 2.81) and 716 car trips (4.79 ± 3.96). There was no difference in activity and moderate-to-vigorous activity duration (p > .105), a lower cycling duration (-1.83 min, p < .001), and a higher MET-level (0.95, p < .001) during walking trips as compared to cycling trips. Both activity (-4.54 min, p < .001), moderate-to-vigorous activity (-3.60 min, p < .001), cycling duration (-1.74 min, p < .001) and MET-level (-0.99, p < .001) were lower during car trips as compared to cycling trips. Fibion showed the sensitivity of 72.2% and specificity of 81.9% for measuring cycling activity type during the reported cycling trips as compared to walking and car trips when the minimum required duration for cycling was less than 29 s.

Conclusions

The thigh-worn Fibion® accelerometer measured a greater duration of cycling, a lower MET-level, and a similar duration of total activity and moderate-to-vigorous activity during free-living cycling trips as compared to walking trips, suggesting it can be used to measure free-living cycling activity and moderate-to-vigorous activity duration in 10-12-year-old children.

A Case for Unifying Accelerometry-Derived Movement Behaviors and Tests of Exercise Capacity for the Assessment of Relative Physical Activity Intensity

Albert Einstein taught us that "everything is relative." People's experience of physical activity (PA) is no different, with "relativism" particularly pertinent to the perception of intensity. Markers of absolute and relative intensities of PA have different but complimentary utilities, with absolute intensity considered best for PA guideline adherence and relative intensity for personalized exercise prescription. Under the paradigm of exercise and PA as medicine, our Technical Note proposes a method of synchronizing accelerometry with the incremental shuttle walking test to facilitate description of the intensity of the free-living PA profile in absolute and relative terms. Our approach is able to generate and distinguish "can do" or "cannot do" (based on exercise capacity) and "does do" or "does not do" (based on relative intensity PA) classifications in a chronic respiratory disease population, facilitating the selection of potential appropriate individually tailored interventions. By synchronizing direct assessments of exercise capacity and PA, clearer insights into the intensity of PA performed during everyday life can be gleaned. We believe the next steps are as follows: (1) to determine the feasibility and effectiveness of using relative and absolute intensities in combination to personalize the approach, (2) to determine its sensitivity to change following interventions (eg, exercise-based rehabilitation), and (3) to explore the use of this approach in healthier populations and in other long-term conditions.

The Mental Illness-Health Matrix and the Mental State Space Matrix: Complementary meta-conceptual frameworks for evaluating psychological states

OBJECTIVE

It is increasingly appreciated that mental health may not just involve a relative absence of mental illness, but the active presence of positive psychological desiderata. However, research attention on mental illness and health has tended to remain siloed and disconnected-proceeding along parallel tracks-with their potential relationship underexplored and undertheorized. As such, we sought to develop theoretical models to help us better understand the interaction of these two domains of experience.

METHODS

Through extensive engagement with relevant literature, we created two complementary meta-conceptual frameworks to represent and evaluate states of mental illness and health.

RESULTS

The Mental Illness-Health Matrix allows different forms of mental illness and health to be situated and assessed within a common framework. The Mental State Space Matrix further enables these various forms to be conceptualized and appraised in terms of numerous common parameters (e.g., valence and arousal).

CONCLUSION

It is hoped that these frameworks will stimulate and support further research on the inter-relational dynamics of illness and health. Indeed, the matrices themselves are provisional works-in-progress, with their articulation here intended as a foundation for their further development as understanding of these topics evolves and improves.

Associations between digital gaming behavior and physical activity among Finnish vocational students

Abstract

Digital gaming is considered to be a major sedentary lifestyle among youth. The time spent on digital gaming may also affect the physical behavior of young adults.

Objective

This study aimed to investigate the associations between various characteristics of digital gaming behavior (i.e., gaming time, device, and game type) and participation in physical activity among Finnish vocational students.

Materials and methods

The research employed a cross-sectional survey design. The analyzed sample consisted of 773 students (455 males, 318 females) from eight vocational school units in Northern Finland who regularly played digital games. Data were collected via an online self-reported questionnaire, which included questions concerning average weekly time spent on digital gaming, preferred device, favorite types of games, and physical activity.

Results

The students spent an average of two hours each day playing digital games. Males preferred to play using personal computers (PCs), whereas mobile gaming was more popular among females. Shooter (42.4%) and entertainment (64.2%) games were the most popular game types among males and females, respectively. The results revealed that male gender and PC gaming were both positively related to physical inactivity among vocational school students. A preference toward sport games was inversely related with physical inactivity.

Conclusion

The presented findings can be utilized to develop interventions that target the prevention of sedentary behavior among vocational students. Further longitudinal studies will be required to reliably assess the relationship between digital gaming and physical activity.

ARTE index revisited: linking biomarkers of cardiometabolic health with free-living physical activity in postmenopausal women

Activity-related energy expenditure (AEE) correlates with physical activity volume; however, between-person differences in body size and walking economy (net V̇o2) can influence AEE. The ratio of total energy expenditure (TEE) and resting energy expenditure (REE) estimates physical activity level (PAL) relative to body mass, yet does not account for variance in walking economy. The activity-related time equivalent (ARTEwalk) circumvents such constraints by adjusting for individual-specific walking economy. Herein, we compared AEE, PAL, and ARTEwalk index in a cohort (n = 81) of postmenopausal women while examining possible associations with biomarkers of cardiometabolic health. Secondary analyses were performed on postmenopausal women dichotomized above/below age group 50th percentile for body fat percent. TEE was reduced by 10% for the thermogenesis of digestion wherein AEE was calculated by subtracting REE from adjusted TEE. PAL was calculated as the ratio of TEE/REE. AEE was divided by the mean net energy expenditure of nongraded walking to calculate the ARTEwalk index. Between-group differences were not detected for AEE or PAL. However, the ARTEwalk index revealed that participants with less adiposity were more physically active (258 ± 149 vs. 198 ± 115 min·day-1; P = 0.046; g = 0.46). AEE and PAL did not correlate with cardiorespiratory fitness or biomarkers of cardiometabolic health. Cardiorespiratory fitness (r = 0.32), arterial elasticity (r = 0.24), total cholesterol/HDL-c ratio (r = -0.22), and body fat% (r = -0.24) were correlated with ARTEwalk. The ARTEwalk index may offer utility in detecting possible differences in physical activity volume among postmenopausal women and appears better associated with cardiometabolic biomarkers compared with AEE or PAL.

Physical Activity and Its Association with Traditional Outcome Measures in Pulmonary Arterial Hypertension

Rationale Limitation of physical activity is a common presenting complaint for patients with pulmonary arterial hypertension (PAH). Physical activity is thought to be determined by cardiopulmonary function, yet there are limited data that investigate this relationship. Objective We aimed to study the relationship between right ventricular function and daily activity and its impact on health-related quality of life (HRQoL) in PAH. Methods Baseline data for 55 patients enrolled in PHANTOM, an ongoing multicenter randomized controlled trial of anastrozole in PAH were used. Post-menopausal women and men were eligible and underwent six-minute walk testing, echocardiography and completed HRQoL questionnaires. Each patient wore an accelerometer for 7-days. Multivariable linear regression models were used to study the association between tricuspid annular plane systolic excursion (TAPSE) and vector magnitude counts, and between daily activity and HRQoL. Principal component analysis and K-means clustering were used to identify activity-based phenotypes. K-nearest neighbors' classification was applied to an independent cross-sectional cohort from the University of Pennsylvania. Results The mean age of patients in PHANTOM was 61 years. 67% were women with idiopathic PAH as the most common etiology. A 0.4 cm increase in TAPSE was associated with an increase in daily vector magnitude counts (ß:34000, 95%CI:900-67000, p=0.004) after adjustment for age, sex, body mass index, etiology of PAH and wear time. A 1-standard deviation increase in vector magnitude counts was associated with higher six-minute walk distance (ß: 56.1 meters, 95%CI:28.6-83.7, p<0.001) and lower emPHasis-10 scores (ß:-3.3, 95%CI:0.3-6.4, p=0.03). Three activity phenotypes, low, medium, and high, were identified. The most active phenotype had greater six-minute walk distances (p=0.001) and lower emPHasis-10 scores (p=0.009) after adjustment for age, sex, body mass index, WHO functional class and parenteral prostacyclin use. Phenotypes of physical activity were reproduced in the second cohort and were independently associated with six-minute walk distance. Conclusion Better right ventricular systolic function was associated with increased levels of activity in PAH. Increased daily activity was associated with greater six-minute walk distance and better HRQoL. Distinct activity-based phenotypes may be helpful in risk stratification of PAH patients or provide novel endpoints for clinical trials.

Personalised Accelerometer Cut-point Prediction for Older Adults' Movement Behaviours using a Machine Learning approach

BACKGROUND AND OBJECTIVES

Body-worn accelerometers are the most popular method for objectively assessing physical activity in older adults. Many studies have developed generic accelerometer cut-points for defining activity intensity in metabolic equivalents for older adults. However, methodological diversity in current studies has led to a great deal of variation in the resulting cut-points, even when using data from the same accelerometer. In addition, the generic cut-point approach assumes that 'one size fits all' which is rarely the case in real life. This study proposes a machine learning method for personalising activity intensity cut-points for older adults.

METHODS

Firstly, raw accelerometry data was collected from 33 older adults who performed set activities whilst wearing two accelerometer devices: GENEActive (wrist worn) and ActiGraph (hip worn). ROC analysis was applied to generate personalised cut-point for each data sample based on a device. Four cut-points have been considered: Sensitivity optimised Sedentary Behaviour; Specificity optimised Moderate to Vigorous Physical Activity; Youden optimised Sedentary Behaviour; and Youden optimised Moderate to Vigorous Physical Activity. Then, an additive regression algorithm trained on biodata features, that concern the individual characteristics of participants, was used to predict the cut-points. As the model output is a numeric cut-point value (and not discrete), evaluation was based on two error metrics, Mean Absolute Error and Root Mean Square Error. Standard Error of estimation was also calculated to measure the accuracy of prediction (goodness of fit) and this was used for performance comparison between our approach and the state-of-the-art. Hold-out and 10-Fold cross validation methods were used for performance validation and comparison.

RESULTS

The results show that our personalised approach performed consistently better than the state-of-the-art with 10-Fold cross validation on all four cut-points considered for both devices. For the ActiGraph device, the Standard Error of estimation from our approach was lower by 0.33 (Youden optimised Sedentary Behaviour), 9.50 (Sensitivity optimised Sedentary Behaviour), 0.64 (Youden optimised Moderate to Vigorous Physical Activity) and 22.11 (Specificity optimised Moderate to Vigorous Physical Activity). Likewise, the Standard Error of estimation from our approach was lower for the GENEActiv device by 2.29 (Youden optimised Sedentary Behaviour), 41.65 (Sensitivity optimised Sedentary Behaviour), 4.31 (Youden optimised Moderate to Vigorous Physical Activity) and 347.15 (Specificity optimised Moderate to Vigorous Physical Activity).

CONCLUSIONS

personalised cut-point can be predicted without prior knowledge of accelerometry data. The results are very promising especially when we consider that our method predicts cut-points without prior knowledge of accelerometry data, unlike the state-of-the-art. More data is required to expand the scope of the experiments presented in this paper.

Machine Learning Approach for Fatigue Estimation in Sit-to-Stand Exercise

Physical exercise (PE) has become an essential tool for different rehabilitation programs. High-intensity exercises (HIEs) have been demonstrated to provide better results in general health conditions, compared with low and moderate-intensity exercises. In this context, monitoring of a patients' condition is essential to avoid extreme fatigue conditions, which may cause physical and physiological complications. Different methods have been proposed for fatigue estimation, such as: monitoring the subject's physiological parameters and subjective scales. However, there is still a need for practical procedures that provide an objective estimation, especially for HIEs. In this work, considering that the sit-to-stand (STS) exercise is one of the most implemented in physical rehabilitation, a computational model for estimating fatigue during this exercise is proposed. A study with 60 healthy volunteers was carried out to obtain a data set to develop and evaluate the proposed model. According to the literature, this model estimates three fatigue conditions (low, moderate, and high) by monitoring 32 STS kinematic features and the heart rate from a set of ambulatory sensors (Kinect and Zephyr sensors). Results show that a random forest model composed of 60 sub-classifiers presented an accuracy of 82.5% in the classification task. Moreover, results suggest that the movement of the upper body part is the most relevant feature for fatigue estimation. Movements of the lower body and the heart rate also contribute to essential information for identifying the fatigue condition. This work presents a promising tool for physical rehabilitation.

Comparison of self-reported & device-based, measured physical activity among children in Germany

BACKGROUND

As children show a more complex but less structured movement behavior than adults, assessment of their many spontaneous and impulsive movements is a challenge for physical activity (PA) assessment. Since neither questionnaires nor accelerometers enable optimal detection of all facets of PA, a multimodal, combined approach of self-reported and device-based methods is recommended. Based on the number of days on which the participants reached the physical activity (PA) values given in the WHO guideline, this study examines 1) the difference between self-reported and device-based, measured PA and 2) whether PA differences between age and gender groups obtained by two methods are comparable.

METHODS

Participants aged 6-17 years were randomly chosen and data were collected representatively at 167 sample points throughout Germany within the Motorik-Modul Study. PA of n = 2694 participants (52.3% female) was measured using the ActiGraph accelerometer (ACC) and a physical activity questionnaire (PAQ). The sample was divided into three age groups (6-10 yrs. n = 788, 11-13 yrs. n = 823, 14-17 yrs. n = 1083). Numbers of days per week with at least 60 min moderate to vigorous PA (MVPA) were analyzed for both methods.

RESULTS

Only every 25th respondent (4%) reaches the WHO standard of 60 min MVPA every day if measured with ACC. Self-reported PA was slightly higher (9%) (meanPAQ = 3.82 days; meanACC = 2.34 days; Fmethod = 915.85; p = <.001; fCohen = .64). The differences between the methods are significantly smaller in younger children than in the older age groups (Fage = 264.2, p < .001; fCohen = .48). The older the subjects are, the lower is the proportion of those who meet the WHO guideline on each day, with girls meeting the guideline less frequently than boys in all age groups.

CONCLUSION

Children and adolescents living in Germany show a very low adherence to the WHO guideline on PA. While younger children are much more active with their free play, especially children over 10 years of age and especially girls should be the target of programs to increase PA.

Stretch-Shortening Cycle Potentiation and Resistance Training-Induced Changes in Walking Economy/Ease and Activity-Related Energy Expenditure in Older Women

ABSTRACT

Hunter, GR, Singh, H, Martins, C, Baranauskas, MN, and Carter, SJ. Stretch-shortening cycle potentiation and resistance training-induced changes in walking economy/ease and activity-related energy expenditure in older women. J Strength Cond Res 35(5): 1345-1349, 2021-Use of elastic energy to improve economy and ease of walking may be important for older adults. The purpose of this investigation was to determine whether baseline (i.e., untrained) stretch-shortening cycle potentiation (SSCP) was associated with potential changes in free-living activity-related energy expenditure (AEE) after supervised exercise training. Sedentary, postmenopausal women (n = 64) between 60 and 74 years of age were evaluated before and after 16 weeks of combined aerobic and resistance training. Assessments included: (a) body composition (dual-energy X-ray absorptiometry), (b) resting energy expenditure (indirect calorimetry), (c) submaximal and maximal walking (treadmill/indirect calorimetry), (d) total energy expenditure (doubly labeled water), and (e) one repetition maximum performed on an incline leg press and SSCP (calculated as the difference between concentric and countermovement leg press throw). Results indicated that baseline SSCP was related (r = -0.29; p < 0.02) to changes in AEE. However, subjects who possessed a high baseline SSCP did not increase SSCP or AEE, whereas subjects with low to moderate baseline SSCP demonstrated a significant increase in both SSCP (low +0.54 and moderate +0.47 m·s-1) and AEE (low +158 and moderate +333 kcal·d-1) post-training (all p less than 0.05). Our findings suggest that among subjects with low to moderate baseline SSCP, 16 weeks of combined aerobic and resistance training can increase SSCP and free-living AEE. However, subjects with high baseline SSCP may require tailored exercise to increase SSCP and possibly AEE.

Micronutrient status and associated factors of adiposity in primary school children with normal and high body fat in Colombo municipal area, Sri Lanka

BACKGROUND

The prevalence of obesity and associated risk of chronic diseases are increasing among the paediatric population. The effectiveness of preventive measures and interventions are likely to improve when all factors which associate with obesity in a specific target group are considered. Currently such comprehensive data is unavailable for Sri Lankan children aged 8-9 years.

METHODS

This paper pertains to the data collected from August-2015 to November-2016 for a case-control study which included cases (high body fat) (N = 160; males-81) and controls (normal body fat) (N = 164; males-80) recruited from primary schools in the Colombo Municipal area. Anthropometry and body composition (Bioelectrical impedance analysis-BIA) were measured. Diet, physical activity and socio-demographic data were collected using validated interviewer administered questionnaires. Serum concentrations of vitamins A, D [25(OH)D], E, folate (serum and red blood cell-RBC), zinc (Zn), selenium (Se), copper (Cu), iron (Fe), magnesium (Mg), calcium (Ca), chromium (Cr), manganese (Mn), cobalt (Co), ferritin, leptin and high sensitivity C-reactive protein (hs-CRP) were assessed using fasting blood samples.

RESULTS

Cases were from higher socio-economic strata and spent significantly less time on physical activities, more time on sedentary behaviours and consumed higher energy compared to the controls. Cases from both genders had significantly lower levels of vitamin D [25 (OH)D], Fe and Mg (all p < 0.05) and higher levels of Cu and Ca (all p < 0.01) compared to controls. Higher levels of ferritin and Cr were seen among male (p < 0.001) and female (p > 0.05) cases compared to the controls. However, total serum folate levels were lower in male (p < 0.01) and female (p > 0.05) cases while the RBC folate levels were higher among male (p < 0.01) and female (p > 0.05) cases compared with controls. Vitamins A, E, Se, Mn and Co (p > 0.05) were not significantly different between groups. The inflammatory markers, both hs-CRP and leptin levels were higher among cases (p < 0.001) compared to the controls.

CONCLUSIONS

This study highlights higher socio-economic status, lower physical activity, more sedentary behaviours, higher energy intake and inconsistent distribution of micronutrients among the children with high body fat when compared with the control group. Increased levels of inflammatory markers indicate the presence of the risk of chronic inflammation in children with high body fat.

Improving Energy Expenditure Estimation through Activity Classification and Walking Speed Estimation Using a Smartwatch

Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. The challenge is to provide accurate EE estimations in free-living environment through portable and unobtrusive devices. In this paper, we present an experimental study to estimate energy expenditure during sitting, standing and treadmill walking using a smartwatch. We introduce a novel methodology, which aims to improve the EE estimation by first separating sedentary (sitting and standing) and non-sedentary (walking) activities, followed by estimating the walking speeds and then calculating the energy expenditure using advanced machine learning based regression models. Ten young adults participated in the experimental trials. Our results showed that combining activity type and walking speed information with the acceleration counts substantially improved the accuracy of regression models for estimating EE. On average, the activity-based models provided 7% better EE estimation than the traditional acceleration-based models.

Ageing and physical function in East African foragers and pastoralists

Human lifespans are exceptionally long compared with those of other primates. A key element in exploring the evolution of human longevity is understanding how modern humans grow older. Our current understanding of common age-related changes in human health and function stems mostly from studies in industrialized societies, where older adulthood is often associated with an increased incidence of chronic diseases. However, individuals who engage in different lifestyles across industrialized and non-industrialized contexts may display variance in age-related changes in health and function. Here, we explore aspects of physical function in a non-industrialized context using three objective measures of physical function. We assessed physical activity levels, walking endurance and muscle strength in two East African populations: Hadza hunter-gatherers in Tanzania and Pokot pastoralists in Kenya. Both Hadza and Pokot participants displayed significant age-related differences in most, but not all, functional measures. Our results suggest that some age-related differences in physical function seen in industrialized contexts could be consistently experienced by most humans, while other age-related differences may vary across populations. Studies of ageing should expand to include a broad range of populations so we can create a more comprehensive understanding of how senescence varies across different lifestyle contexts. This article is part of the theme issue 'Evolution of the primate ageing process'.

Association Between the Predictors of Functional Capacity and Heart Rate Off-Kinetics in Patients with Chronic Obstructive Pulmonary Disease

Background

The heart rate (HR) kinetics as well as other predictors of functional capacity such as the Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT), the Duke Activity Status Index (DASI) and the handgrip strength (HGS) represent important tools in assessing the impact of COPD on exercise performance and health status of individuals with COPD.

Purpose

To verify the relationship between functional capacity, measured using the six-minute walking test (6MWT), with the HR off-kinetics, HGS and the DASI and CAT scores.

Methods

For this cross-sectional study, 29 subjects with COPD underwent body composition, pulmonary function and cardiac function tests. Subsequently, the DASI and CAT questionnaires and HGS test were performed. The beat-to-beat R-R intervals (IRR) were collected in rest, during the test and in recovery after the 6MWT. The HR off-kinetics was obtained during a 360-second period in post-exercise recovery through the HR mono-exponential decay.

Results

Moderate correlations were observed between: 1) walked distance (WD) in the 6MWT and the CAT and DASI scores (r= −0.58, p=0.001 and r= 0.58, p=0.001, respectively); 2) WD and HGS (r=0.37, p=0.05); 3) and WD and HR off-kinetics (τ; r= −0.54, p=0.002 and MRT; r= −0.55, p=0.002, respectively).

Conclusion

The 6MWT performance is a direct measurement to evaluate functional capacity. Additionally, it is related to other direct and indirect markers for functional evaluation in patients with COPD. These results suggest the application of these tools in clinical practice, based on the accessibility, non-invasive character and easy applicability of these methods.

The Activ8 activity monitor: Validation of posture and movement classification

Introduction

To set up and guide interventions with the aim to increase physical activity and lower sedentary behavior valid monitoring of physical behavior is essential. The aim of this study was to evaluate the validity of the single-unit Activ8 activity monitor to classify several body postures and movements.

Methods

Twelve healthy adults performed a series of activities, representative for everyday life, according to a standard protocol. Activ8 was both worn in the trouser pocket (prescribed location) and fixated to the front of the thigh. Activities were video recorded and analyzed thereafter. Postures and movements that were analyzed were lying/sitting, standing, walking, cycling, and running.

Results

The agreement between Activ8 output and video analysis was 89.7% (inter-subject range: 66.0 to 96.6%) for the pocket location and 91.9% (range 85.5 to 95.1%) for the thigh location. Sensitivity and positive predictive value scores for both locations were all above 80%, except for standing (69% or higher). Differences in classified duration of separate postures and movements were within 20% for walking, sitting and running.

Conclusion

The Activ8 is a valid instrument to quantify a defined set of body postures and movements. Because of the smaller time difference, the thigh location is preferred for research purposes.

Windows Into Human Health Through Wearables Data Analytics

Background

Wearable sensors (wearables) have been commonly integrated into a wide variety of commercial products and are increasingly being used to collect and process raw physiological parameters into salient digital health information. The data collected by wearables are currently being investigated across a broad set of clinical domains and patient populations. There is significant research occurring in the domain of algorithm development, with the aim of translating raw sensor data into fitness- or health-related outcomes of interest for users, patients, and health care providers.

Objectives

The aim of this review is to highlight a selected group of fitness- and health-related indicators from wearables data and to describe several algorithmic approaches used to generate these higher order indicators.

Methods

A systematic search of the Pubmed database was performed with the following search terms (number of records in parentheses): Fitbit algorithm (18), Apple Watch algorithm (3), Garmin algorithm (5), Microsoft Band algorithm (8), Samsung Gear algorithm (2), Xiaomi MiBand algorithm (1), Huawei Band (Watch) algorithm (2), photoplethysmography algorithm (465), accelerometry algorithm (966), ECG algorithm (8287), continuous glucose monitor algorithm (343). The search terms chosen for this review are focused on algorithms for wearable devices that dominated the commercial wearables market between 2014-2017 and that were highly represented in the biomedical literature. A second set of search terms included categories of algorithms for fitness-related and health-related indicators that are commonly used in wearable devices (e.g. accelerometry, PPG, ECG). These papers covered the following domain areas: fitness; exercise; movement; physical activity; step count; walking; running; swimming; energy expenditure; atrial fibrillation; arrhythmia; cardiovascular; autonomic nervous system; neuropathy; heart rate variability; fall detection; trauma; behavior change; diet; eating; stress detection; serum glucose monitoring; continuous glucose monitoring; diabetes mellitus type 1; diabetes mellitus type 2. All studies uncovered through this search on commercially available device algorithms and pivotal studies on sensor algorithm development were summarized, and a summary table was constructed using references generated by the literature review as described (Table 1).

Conclusions

Wearable health technologies aim to collect and process raw physiological or environmental parameters into salient digital health information. Much of the current and future utility of wearables lies in the signal processing steps and algorithms used to analyze large volumes of data. Continued algorithmic development and advances in machine learning techniques will further increase analytic capabilities. In the context of these advances, our review aims to highlight a range of advances in fitness- and other health-related indicators provided by current wearable technologies.

Dietary Intake and Physical Activity Assessment: Current Tools, Techniques, and Technologies for Use in Adult Populations

Accurate assessment of dietary intake and physical activity is a vital component for quality research in public health, nutrition, and exercise science. However, accurate and consistent methodology for the assessment of these components remains a major challenge. Classic methods use self-report to capture dietary intake and physical activity in healthy adult populations. However, these tools, such as questionnaires or food and activity records and recalls, have been shown to underestimate energy intake and expenditure as compared with direct measures like doubly labeled water. This paper summarizes recent technological advancements, such as remote sensing devices, digital photography, and multisensor devices, which have the potential to improve the assessment of dietary intake and physical activity in free-living adults. This review will provide researchers with emerging evidence in support of these technologies, as well as a quick reference for selecting the "right-sized" assessment method based on study design, target population, outcome variables of interest, and economic and time considerations.

THEME INFORMATION

This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry

Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions.

NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Comparison of Different Physical Activity Measurement Methods in Adults Aged 45 to 64 Years Under Free-Living Conditions

OBJECTIVE

To compare physical activity (PA) measured by 4 methods in adults under free-living conditions in relation to selected demographic and anthropometric variables.

DESIGN

Cohort study.

SETTING

Department of Sports Medicine.

PARTICIPANTS

Clinically healthy men (81) and women (69) aged 45 to 64 years.

INTERVENTIONS

Physical activity monitoring for 7 consecutive days under free-living conditions by pedometer (P) and accelerometer (A) simultaneously and PA questionnaires: International Physical Activity Questionnaire (IPAQ) and Seven-Day Physical Activity Questionnaire Recall (SDPAR) completed after the 7-day PA.

MAIN OUTCOME MEASURES

Comparison of PA measured by pedometer, IPAQ, and SDPAR with accelerometer with regard to age, body mass, gender, and obesity type.

RESULTS

Total energy expenditure (EE) by IPAQ was higher than A (P < 0.001) in both groups regardless of age, body mass, or obesity type. Mean EE value by P was greater than A (P < 0.001) in central-obesity males and lower than A (P < 0.001) in central-obesity females. There were differences in step counts in women, unnoticed in men. SDPAR overestimated total EE in gynoid-obesity males and in central-obesity females compared with A. Ninety-five percent CI was the largest around IPAQ compared with P and SDPAR, with SDPAR showing the best agreement with A.

CONCLUSIONS

Body mass and obesity type influenced PA measurements. To monitor PA, it is recommended to use pedometer in normal bodyweight and overweight groups while accelerometer is advisable in obese subjects. A combined approach of objective and subjective PA monitoring tools is preferable.

A comparison of nutritional intake and daily physical activity of girls aged 8-11 years old in Makkah, Saudi Arabia according to weight status

BACKGROUND

Obesity rates in Saudi Arabia are amongst the highest in the world. It is known that teenage girls are less active than teenage boys, but less is known about the diet and activity patterns in younger girls. Therefore this study sought to investigate dietary intake and daily physical activity in girls aged 8-11 years old in Saudi Arabia.

METHODS

This was a cross- sectional observational study conducted in seven schools across the city of Makkah. A total of 266 girls had anthropometric measurements taken including height, weight, waist circumference and body fat estimations. Dietary assessment using a 4 day unweighed diet diary was undertaken in 136 of these participants, and 134 agreed to monitor their physical activity for the 4 days using an accelerometer. After exclusion for under-reporting, 109 remained in the dietary analysis and 78 in the physical activity analyses. Differences in means between BMI groups were determined using one-way ANOVA with post hoc Tukey test. Multivariable linear regression analysis was performed to look at the effect of multiple variables on body weight.

RESULTS

A total of 30% of participants were classified obese or overweight. There was a significant difference in the mean daily energy intake between the BMI groups with the obese group having the highest energy, fat, carbohydrate and protein intake (obese group: 2677 ± 804 kcal/d; healthy weight group: 1806 ± 403 kcal/d, p < 0.001), but the percentage contribution of the macronutrients to energy intake remained the same across the BMI groups. There were no differences in number of steps taken per day or time spent in moderate to vigorous intensity exercise according to BMI category. Most of the girls did not meet daily physical activity guidelines (5969 to 6773 steps per day and 18.5 - 22.5 mins per day of moderate to vigorous activity). Multiple linear regression showed that energy intake positively predicted body weight (Beta = 0.279, p =0 .001), whereas, total energy expenditure per kg of body weight and family income had a significant negative influence on body weight (Beta = -0.661, p < 0.001; -0.131, p = 0.028 respectively).

CONCLUSIONS

The results of this cross sectional analysis suggest that obesity in girls aged 8-11 years is linked to excessive energy intake from all macronutrients and the majority of girls in all weight categories are inactive. Research should be conducted to further investigate causal relationships in longitudinal studies and develop interventions to promote dietary change and activity that is culturally acceptable for girls in Saudi Arabia.

Impact of accelerometer and pedometer use on physical activity and glycaemic control in people with Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Self-directed pedometer use increases physical activity levels in the general population; however, evidence of benefit for Type 2 diabetes is unclear and has not been systematically reviewed for accelerometers.

AIM

To examine the impact of using physical activity monitoring devices (pedometers and accelerometers) on free-living physical activity and HbA_1c levels in people with Type 2 diabetes.

METHODS

We conducted a systematic literature review. Bibliographic databases included Medline, Embase, Web of Science, CINAHL, SportDiscus and the Cochrane Central Register of Controlled Trials. We included controlled trials evaluating interventions based on the use of pedometers or accelerometers to promote physical activity in people with Type 2 diabetes. Primary outcomes were physical activity (min/week or steps) and HbA_1c [mmol/mol (%)]. Secondary outcomes were weight, blood pressure and lipid profile.

RESULTS

Twelve trials (1458 participants) were identified, of which nine studied pedometers and three accelerometers. Random-effects meta-analysis showed an overall increase in physical activity (standardized mean difference 0.57, 95% CI 0.24, 0.91) in the intervention groups. Accelerometers and pedometers produced a similar effect size. No significant differences were observed in HbA_1c , BMI, blood pressure or lipid profile.

CONCLUSIONS

People with Type 2 diabetes, provided with an accelerometer or pedometer, substantially increased their free-living physical activity. There is no evidence that monitor use alone improves HbA_1c or other clinical outcomes. Further trials are needed to compare the relative effects of activity monitors within differing complex interventions.

Measuring Physical Activity and Sedentary Behavior in Youth with Type 2 Diabetes

BACKGROUND

Lifestyle interventions that encourage increasing physical activity (PA) and losing weight are critical for overweight and obese youth with comorbid conditions. Assessing PA within such lifestyle intervention efforts requires measurement tool(s) that are both accurate and appropriate for these youth. This research compares PA levels and sedentary behavior in an ethnically diverse cohort of overweight/obese youth with type 2 diabetes using both accelerometry and a questionnaire previously validated in the general youth population.

METHODS

Spearman's correlations were used to compare time spent sedentary and in different PA intensities between a questionnaire, the three-day PA recall (3DPAR), and an objective PA measure, the ActiGraph accelerometer, in 236 overweight/obese youth with diabetes.

RESULTS

Spearman correlations between 3DPAR and accelerometer results for total PA were small and not significant (rho = 0.11, p > 0.05 for males and females). Correlations for specific PA intensities (moderate/vigorous and light) were also small and not significant. Sedentary time between instruments was significant, but weakly correlated in females (rho = 0.19, p < 0.05), but not in males (rho = 0.07, p = 0.48).

CONCLUSIONS

Subjective PA measures validated in the general youth population may not be the best method for differentiating levels of movement in overweight/obese youth with type 2 diabetes, who spend most of their time in light-intensity activity and sedentary pursuits with little or no time spent in moderate/vigorous-intensity activities. Objective measures such as accelerometers that can capture the lower end of the movement scale are likely the more appropriate measures under these conditions.

The convergent validity of Actiwatch 2 and ActiGraph Link accelerometers in measuring total sleeping period, wake after sleep onset, and sleep efficiency in free-living condition

PURPOSE

Physical activity (PA) and sleep are important to health; thus, it is important for researchers to have valid tools to measure them. Accelerometers have been proven valid for measuring PA and sleep, but only one device does this simultaneously: the ActiGraph Link (ActiGraph, LLC); however, the sleep-monitoring function has not been validated. This study aimed to evaluate the predictive power of ActiGraph Link sleep parameters against a validated accelerometer (Actiwatch 2, Phillips Respironics Mini-Mitter).

METHODS

A total of 49 Hong Kong adults aged 18-64 provided valid data on both accelerometers on their non-dominant wrist for seven consecutive days. Epochs from both accelerometers were classified as either sleep or awake using seven established algorithms (Cole-Kripke, Sadeh, Sazonov, high sensitivity threshold, medium sensitivity threshold, low sensitivity threshold, and neural network model), and these data were transformed to total sleeping period, wake after sleep onset, and sleep efficiency.

RESULTS

The non-zero count data for both accelerometers (331,103 observations) were strongly correlated with a Spearman correlation of 0.83 (p < 0.001). The total sleeping period was highly correlated (Spearman correlation ranged from 0.74 to 0.90) regardless of the algorithms used. All algorithms yielded insignificant difference in total sleep time measured by the two accelerometers (p > 0.05) with a negligible effect size of d < 0.2. The agreement of sleep/wake status was high for all algorithms, with accuracy ranging from 93.05 % (Sadeh's algorithm) to 96.13 % (Cole-Kripke's algorithm).

CONCLUSIONS

Results showed that the sleep function of the ActiGraph Link performs similar to a validated accelerometer (Actiwatch 2) and provides an opportunity to measure both sleep and PA simultaneously.

Energy Expenditures for Activities of Daily Living in Korean Young Adults: A Preliminary Study

OBJECTIVE

To investigate the energy expenditure (EE) of Korean young adults based on activities refined to a deskbound lifestyle.

METHODS

Sixty-four healthy office workers aged between 25 and 46 years participated in this study. EE was expressed as metabolic equivalent of task (MET). Participants were evaluated in terms of their EE during physical activities of sleeping (n=22), typing (n=37), folding laundry (n=34), dishwashing (n=32), studying (n=18), mopping (n=35), walking (n=33), stair climbing (n=23), and running (n=29). Volume of oxygen consumption was measured by indirect calorimetry K4b(2) (COSMED). The results were compared to the established Compendium MET.

RESULTS

The MET of activities were: sleeping, 1.24±0.43; typing, 1.35±0.25; folding laundry, 1.58±0.51; dishwashing, 2.20±0.51; studying, 2.11±0.90; mopping, 2.72±0.69; walking at 4 km/hr, 3.48±0.65; stair climbing of five stories, 6.18±1.08; and running at 8 km/hr, 7.57±0.57. The values of typing and mopping were similar to those in the Compendium, whereas those of sleeping, folding laundry, dishwashing, studying, walking, stair climbing and running were different.

CONCLUSION

To our knowledge, this estimation of EE in MET during activities of daily living is the first data of young adults in Korea. These data could be used as a reference to modify the guidelines of physical activities for the age group examined in this study.

Energetic Assessment of the Nonexercise Activities under Free-Living Conditions

Nonexercise activities (NAs) are common types of physical activity in daily life and critical component in energy expenditure. However, energetic assessment of NA, particularly in free-living subjects, is a technical challenge. In this study, mechanical modeling and portable device were used to evaluate five common types of NA in daily life: sit to stand, lie to sit, bowing while standing, squat, and right leg over left. A human indirect calorimeter was used to measure the activity energy expenditure of NA. Mechanical work and mechanical efficiency of NA were calculated for mechanical modeling. Thirty-two male subjects were recruited for the study (20 subjects for the development of models and 12 subjects for evaluation of models). The average (mean ± SD) mechanical work of 5 NAs was 2.31 ± 0.50, 2.88 ± 0.57, 1.75 ± 0.55, 3.96 ± 1.25, and 1.25 ± 0.51 J/kg·m, respectively. The mean mechanical efficiencies of those activities were 22.0 ± 3.3%, 26.5 ± 5.1%, 19.8 ± 3.7%, 24.0 ± 5.5%, and 26.3 ± 5.5%. The activity energy expenditure estimated by the models was not significantly different from the measurements by the calorimeter (p > 0.05) with accuracies of 102.2 ± 20.7%, 103.7 ± 25.8%, 105.6 ± 14.6%, 101.1 ± 28.0%, and 95.8 ± 20.7%, respectively, for those activities. These findings suggest that the mechanical models combined with a portable device can provide an alternative method for the energetic analysis of nonexercise activities under free-living condition.

Accelerometer-measured physical activity among older adults in urban India: Results of a study on global AGEing and adult health substudy

OBJECTIVES

Accelerometry provides researchers with a powerful tool to measure physical activity in population-based studies, yet this technology has been underutilized in cross-cultural studies of older adults. The present study was conducted among older adults in an urban setting in India with the following three objectives: (1) to compare average activity levels obtained through different durations of monitoring (1, 3, and 7 days); (2) to document differences in physical activity patterns by sex and age; and (3) to evaluate links between measures of physical activity and anthropometrics, as well as between activity parameters and measures of household size, work status, and social cohesion.

METHODS

The present study uses data from a physical activity substudy of the World Health Organization's Study on global AGEing and adult health (SAGE-PA). This study of 200 older adults (49-90 years old; 72 males, 128 females) in urban India combines 7 continuous days of ActiGraph GT3X accelerometry with anthropometric and sociodemographic data.

RESULTS

Results reveal overall low activity levels, with significantly lower activity energy expenditure (AEE) among females (P < 0.05). No significant differences were documented in activity level by monitoring duration. Age was negatively correlated with AEE in men (P < 0.01) and women (P < 0.001). AEE was positively correlated with BMI in men (P < 0.01) and women (P < 0.05). Finally, women who were more socially integrated had greater AEE (P < 0.01).

CONCLUSIONS

This study illustrates the utility of accelerometry for quantifying activity levels in aging populations in non-Western nations. Am. J. Hum. Biol. 28:412-420, 2016. © 2015 Wiley Periodicals, Inc.

Energy flux: staying in energy balance at a high level is necessary to prevent weight gain for most people

Energy flux, the rate of energy conversion from absorption to expenditure or storage, is a critical component of understanding weight management. Individuals who maintain body weight over time have common characteristics including a relatively high level of physical activity and minimal changes in body composition, muscle mass and metabolic rate. A higher state of energy flux resulting from high energy expenditure may provide for a greater 'sensitivity' between energy intake and expenditure. This sensitivity stabilizes body weight by enhancing reciprocal compensation among these components with changes in eating or activity. The energy balance framework suggests that a higher level of energy expenditure requires higher energy intake to maintain body mass. Maintaining energy balance at a higher caloric intake and expenditure should be a more successful long-term strategy for weight maintenance than reduced consumption or extreme caloric restriction at a low level of energy expenditure (a low energy flux) and improve intervention effectiveness for sustainable methods for body weight stability.

Nutritional epidemiology--there's life in the old dog yet!

Consideration is given to the idea that the nutritional epidemiology of cancer is dead, as some in the media have claimed. The basis for the claim does not lie in science nor has anyone with relevant knowledge made such a statement-although that, too, has been claimed. Evidence is adduced for the importance of past achievements of nutritional epidemiology. Attention is similarly drawn to recent contributions. In particular, I note the state of play of cancer and plant foods, fat and breast cancer, meat and cancer, vegetarians, intervention studies, migrant studies, and westernization of diet and lifestyle. Some next steps and some currently important questions are outlined.

Perceived athletic competence and physical activity in children with developmental coordination disorder who are clinically referred, and control children

The relationship between perceived athletic competence (PAC) and physical activity (PA) in children with developmental coordination disorder (DCD) is still unclear. This study investigated differences in PAC and PA between, and within, a group of children with DCD that were clinically referred (n = 31) and a group of control children (n = 38), aged 7-12 years. All children were categorized in four groups: (1) children with DCD/low PAC, (2) children with DCD/normal to high PAC, (3) control children/low PAC, and (4) control children/normal to high PAC. PAC was assessed with the Self-Perception Profile for Children, and PA was assessed with the Modifiable Activity Questionnaire. Children with DCD participated less in unorganized PA, but not in organized PA, compared with control children. Normal to high PAC was found in more than half of the children (64.5%) with DCD. Children with DCD/low PAC and children with DCD/normal to high PAC participated significantly less in unorganized physical activity compared with control children/normal to high PAC, but not compared with control children/low PAC. The results indicate that there are large individual differences in PAC in children with DCD.

A frequency questionnaire to estimate free-living physical activity among Tunisian preadolescent and adolescent children

OBJECTIVE

To develop a child- and adolescent-appropriate physical activity frequency questionnaire (PAFQ) in Tunisia, North Africa.

DESIGN

A PAFQ was developed from a physical activity (PA) inventory that comprised major activity components (at home, preparing meals, school time, transport, non-sport leisure, sports, prayer and sleeping time). Then, type and duration of each activity undertaken during the past week were estimated. Total energy expenditure (TEE) estimated by the PAFQ was compared with data derived from two criterion methods: heart-rate monitoring (HRM) and a 24 h PA recall (24h-R), both collected during a 3 d period including one weekday and two weekend days.

SETTING

Two elementary schools and two high schools of the most developed and urbanized area, Greater Tunis.

SUBJECTS

One hundred and forty-two volunteer children and adolescents aged 10-19 years.

RESULTS

The PAFQ strongly was correlated with both HRM (r = 0·70; 95% CI 0·62, 0·76) and 24h-R (r = 0·81; 95% CI 0·77, 0·84). It featured acceptable agreement with both criterion measures, slightly underestimating TEE compared with 24h-R (-2·8%, mean of individual differences -272·7 kJ/d; 95% CI -490·6, -57·4 kJ/d) and moderately overestimating it compared with HRM (+11·3%, mean of individual differences +1106·2 kJ/d; 95% CI 845·8, 1366·6 kJ/d). Reliability ranged from moderate to good (weighted kappa coefficients from 0·47 to 0·78 and intra-class correlation coefficients between 0·79 and 0·86 for energy expenditure by PA categories), indicating strong agreement between the two assessments.

CONCLUSIONS

This PAFQ could be useful in the description and surveillance of PA patterns or for the evaluation of population-based interventions directed at promoting PA in Tunisian children and adolescents.

Comparison of total energy expenditure assessed by two devices in controlled and free-living conditions

The objective of this study was to evaluate the validity of total energy expenditure (TEE) provided by Actiheart and Armband. Normal-weight adult volunteers wore both devices either for 17 hours in a calorimetric chamber (CC, n = 49) or for 10 days in free-living conditions (FLC) outside the laboratory (n = 41). The two devices and indirect calorimetry or doubly labelled water, respectively, were used to estimate TEE in the CC group and FLC group. In the CC, the relative value of TEE error was not significant (p > 0.05) for Actiheart but significantly different from zero for Armband, showing TEE underestimation (-4.9%, p < 0.0001). However, the mean absolute values of errors were significantly different between Actiheart and Armband: 8.6% and 6.7%, respectively (p = 0.05). Armband was more accurate for estimating TEE during sleeping, rest, recovery periods and sitting-standing. Actiheart provided better estimation during step and walking. In FLC, no significant error in relative value was detected. Nevertheless, Armband produced smaller errors in absolute value than Actiheart (8.6% vs. 12.8%). The distributions of differences were more scattered around the means, suggesting a higher inter-individual variability in TEE estimated by Actiheart than by Armband. Our results show that both monitors are appropriate for estimating TEE. Armband is more effective than Actiheart at the individual level for daily light-intensity activities.

Assessment of physical activity and energy expenditure: an overview of objective measures

The ability to assess energy expenditure (EE) and estimate physical activity (PA) in free-living individuals is extremely important in the global context of non-communicable diseases including malnutrition, overnutrition (obesity), and diabetes. It is also important to appreciate that PA and EE are different constructs with PA defined as any bodily movement that results in EE and accordingly, energy is expended as a result of PA. However, total energy expenditure, best assessed using the criterion doubly labeled water (DLW) technique, includes components in addition to physical activity energy expenditure, namely resting energy expenditure and the thermic effect of food. Given the large number of assessment techniques currently used to estimate PA in humans, it is imperative to understand the relative merits of each. The goal of this review is to provide information on the utility and limitations of a range of objective measures of PA and their relationship with EE. The measures discussed include those based on EE or oxygen uptake including DLW, activity energy expenditure, physical activity level, and metabolic equivalent; those based on heart rate monitoring and motion sensors; and because of their widespread use, selected subjective measures.

Elevated objectively measured but not self-reported energy intake predicts future weight gain in adolescents

BACKGROUND

Although obesity putatively occurs when individuals consume more calories than needed for metabolic needs, numerous risk factor studies have not observed significant positive relations between reported caloric intake and future weight gain, potentially because reported caloric intake is inaccurate.

OBJECTIVE

The present study tested the hypothesis that objectively measured habitual energy intake, estimated with doubly labeled water, would show a stronger positive relation to future weight gain than self-reported caloric intake based on a widely used food frequency measure.

DESIGN

Two hundred and fifty-three adolescents completed a doubly labeled water (DLW) assessment of energy intake (EI), a food frequency measure, and a resting metabolic rate (RMR) assessment at baseline, and had their body mass index (BMI) measured at baseline and at 1- and 2-year follow-ups.

RESULTS

Controlling for baseline RMR, elevated objectively measured EI, but not self-reported habitual caloric intake, predicted increases in BMI over a 2-year follow-up. On average, participants under-reported caloric intake by 35%.

CONCLUSIONS

RESULTS provide support for the thesis that self-reported caloric intake has not predicted future weight gain because it is less accurate than objectively measured habitual caloric intake, suggesting that food frequency measures can lead to misleading findings. However, even objectively measured caloric intake showed only a moderate relation to future weight gain, implying that habitual caloric intake fluctuates over time and that it may be necessary to conduct serial assessments of habitual intake to better reflect the time-varying effects of caloric intake on weight gain.

Bottlenose dolphins modify behavior to reduce metabolic effect of tag attachment

Attaching bio-telemetry or -logging devices ('tags') to marine animals for research and monitoring adds drag to streamlined bodies, affecting posture, swimming gaits and energy balance. These costs have never been measured in free-swimming cetaceans. To examine the effect of drag from a tag on metabolic rate, cost of transport, and swimming behavior, four captive male dolphins (Tursiops truncatus) were trained to swim a set course, either non-instrumented (n = 7) or instrumented with a tag (DTAG2; n = 12), and surface exclusively in a flow-through respirometer where oxygen consumption (V̇O2) and carbon dioxide production (V̇CO2; mL kg-1 min-1) rates were measured and respiratory exchange ratio (V̇O2/V̇CO2) was calculated. Tags did not significantly affect individual mass-specific oxygen consumption, Physical Activity Ratios (exercise V̇O2/resting V̇O2), total or net cost of transport (COT, J m-1 kg-1) or locomotor costs during swimming or two-minute recovery phases. However, individuals swam significantly slower when tagged (by ~11%; mean±s.d. 3.31±0.35 m s-1) compared to when non-instrumented (3.73±0.41 m s-1). A combined theoretical and Computational Fluid Dynamics (CFD) model estimating drag forces and power exertion during swimming suggests drag loading and energy consumption are reduced at lower swimming speeds. Bottlenose dolphins in the specific swimming task in this experiment slowed to the point where the tag yielded no increases in drag or power, while showing no difference in metabolic parameters when instrumented with a DTAG2. These results, and our observations, suggest that animals modify their behavior to maintain metabolic output and energy expenditure when faced with tag-induced drag.

Intensity of physical activity in the energy expenditure of older adults

This study examined the intensity of activity contributing to physical activity energy expenditure in older adults. In 57 men and women aged ≥ 65, total energy expenditure (TEE) was measured using doubly labeled water and resting metabolic rate was measured using indirect calorimetry to calculate a physical activity index (PAI). Sedentary time and physical activity of light and moderate to vigorous (mod/vig) intensity was measured using an accelerometer. The subjects were 75 ± 7 yrs (mean ± SD) of age and 79% female. Subjects spent 66 ± 8, 25 ± 5, and 9 ± 4% of monitor wear time in sedentary, light, and mod/vig activity per day, respectively. In a mixture regression model, both light (β = 29.6 [15.6-43.6, 95% CI]), p < .001) and mod/vig intensity activity (β = 28.7 [7.4-50.0, 95% CI]), p = .01) were strongly associated with PAI, suggesting that both light and mod/vig intensity activities are major determinants of their physical activity energy expenditure.

Improving physical activity in COPD: towards a new paradigm

Chronic obstructive pulmonary disease (COPD) is a debilitating disease affecting patients in daily life, both physically and emotionally. Symptoms such as dyspnea and muscle fatigue, lead to exercise intolerance, which, together with behavioral issues, trigger physical inactivity, a key feature of COPD. Physical inactivity is associated with adverse clinical outcomes, including hospitalization and all-cause mortality. Increasing activity levels is crucial for effective management strategies and could lead to improved long-term outcomes. In this review we summarize objective and subjective instruments for evaluating physical activity and focus on interventions such as pulmonary rehabilitation or bronchodilators aimed at increasing activity levels. To date, only limited evidence exists to support the effectiveness of these interventions. We suggest that a multimodal approach comprising pulmonary rehabilitation, pharmacotherapy, and counselling programs aimed at addressing emotional and behavioural aspects of COPD may be an effective way to increase physical activity and improve health status in the long term.

Improved physical activity in patients treated for chronic pain by spinal cord stimulation

The objective of this study was to objectively assess the physical activity of daily living in chronic pain patients treated with spinal cord stimulation (SCS). Changes in pain and spontaneous physical activity following SCS were evaluated under real life conditions. Five series of measurements were performed before the implant (baseline) and at one, three, six, and 12 months after the implantation of an SCS system. Compared to baseline values, physical activity increased consistently during the entire follow-up period. The time spent walking and standing was statistically increased after six months (p < 0.01) and the time spent lying decreased significantly (p < 0.001) at the same time. The average total walking distance increased up to 389% at 12 months, reaching statistical significance (p < 0.05) after three months. The stride length and the speed increased (p < 0.01) at all times. We conclude that the reduction in pain intensity due to SCS is associated with a progressive and sustained improvement in physical activity. j.

Elevated energy intake is correlated with hyperresponsivity in attentional, gustatory, and reward brain regions while anticipating palatable food receipt

BACKGROUND

Obese compared with lean individuals show greater attention-, gustatory-, and reward-region responsivity to food cues but reduced reward-region responsivity during food intake. However, to our knowledge, research has not tested whether an objectively measured caloric intake is positively associated with neural responsivity independent of excess adipose tissue.

OBJECTIVE

We tested the hypothesis that objectively measured energy intake, which accounts for basal needs and the percentage of body fat, correlates positively with the neural response to anticipated palatable food intake but negatively with a response to food intake in healthy-weight adolescents.

DESIGN

Participants (n = 155; mean ± SD age: 15.9 ± 1.1 y) completed functional magnetic resonance imaging scans while anticipating and receiving palatable food compared with a tasteless solution, a doubly labeled water assessment of energy intake, and assessments of resting metabolic rate and body composition.

RESULTS

Energy intake correlated positively with activation in the lateral visual and anterior cingulate cortices (visual processing and attention), frontal operculum (primary gustatory cortex) when anticipating palatable food, and greater striatal activation when anticipating palatable food in a more-sensitive region of interest analysis. Energy intake was not significantly related to neural responsivity during palatable food intake.

CONCLUSIONS

Results indicate that objectively measured energy intake that accounts for basal needs and adipose tissue correlates positively with activity in attentional, gustatory, and reward regions when anticipating palatable food. Although hyperresponsivity of these regions may increase risk of overeating, it is unclear whether this is an initial vulnerability factor or a result of previous overeating. This trial was registered at clinicaltrials.gov as NCT01807572.

Effect of BMI on prediction of accelerometry-based energy expenditure in youth

PURPOSE

The objective of this study is to determine the effect of body mass index (BMI) on level of agreement between six previously established prediction equations for three commonly used accelerometers to predict summary measures of energy expenditure (EE) in youth.

METHODS

One hundred and thirty-one youth between the ages of 10-17 yr and BMI from 15 to 44 kg·m were outfitted with hip-worn ActiGraph GT1M (Pensacola, FL), Actical (MiniMiter/Respironics, Bend, OR), and RT3 (StayHealthy, Monrovia, CA) accelerometers and spent approximately 24 h in a whole-room indirect calorimeter while performing structured and self-selected activities. Five commonly used regression and one propriety equations for each device were used to predict the minute-to-minute EE (normalized to METs), daily physical activity level (PAL), and time spent in sedentary, light, moderate, and vigorous physical activity intensity categories. The calculated values were compared with criterion measurements obtained from the room calorimeter.

RESULTS

All predictive equations, except RT3, significantly over- or underpredicted daily PAL (P < 0.001), with large discrepancies observed in the estimate of sedentary and light activity. Discrepancies between actual and estimated PAL ranged from 0.05 to 0.68. In addition, BMI represented a modifier for two ActiGraph predictive equations (AG1 and AG2), affecting the accuracy of physical activity-related EE predictions.

CONCLUSION

ActiGraph (AG3) and the RT3 closely predicted overall PAL (within 4.2% and 6.8%, respectively) as a group. When adjusting for age, sex, and ethnicity, Actical (AC1 and AC2) and ActiGraph (AG3) were not influenced by BMI. However, a gap between some hip-worn accelerometer predictive and regression equations was demonstrated compared with both criterion measurement and each other, which poses a potential difficulty for interstudy (e.g., different accelerometers) and intrastudy (e.g., BMI and adiposity) comparisons.