Guy Plasqui

Physical activity assessment with accelerometers: an evaluation against doubly labeled water.

This review focuses on the ability of different accelerometers to assess daily physical activity as compared with the doubly labeled water (DLW) technique, which is considered the gold standard for measuring energy expenditure under free‐living conditions. The PubMed Central database (U.S. NIH free digital archive of biomedical and life sciences journal literature) was searched using the following key words: doubly or double labeled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. In total, 41 articles were identified, and screening the articles’ references resulted in one extra article. Of these, 28 contained sufficient and new data. Eight different accelerometers were identified: 3 uniaxial (the Lifecorder, the Caltrac, and the CSA/MTI/Actigraph), one biaxial (the Actiwatch AW16), 2 triaxial (the Tritrac‐R3D and the Tracmor), one device based on two position sensors and two motion sensors (ActiReg), and the foot‐ground contact pedometer. Many studies showed poor results. Only a few mentioned partial correlations for accelerometer counts or the increase in R2 caused by the accelerometer. The correlation between the two methods was often driven by subject characteristics such as body weight. In addition, standard errors or limits of agreement were often large or not presented. The CSA/MTI/Actigraph and the Tracmor were the two most extensively validated accelerometers. The best results were found for the Tracmor; however, this accelerometer is not yet commercially available. Of those commercially available, only the CSA/MTI/Actigraph has been proven to correlate reasonably with DLW‐derived energy expenditure.

Physical Inactivity and Obesity: A Vicious Circle

Objective: Physical activity (PA) begins to decline in adolescence with a concomitant increase in weight. We hypothesized that a vicious circle may arise between decreasing PA and weight gain from adolescence to early adulthood.

Daily physical activity assessment with accelerometers: new insights and validation studies.

The field of application of accelerometry is diverse and ever expanding. Because by definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) method as gold standard to assess total energy expenditure over longer periods of time is the method of choice to validate accelerometers in their ability to assess daily physical activities. The aim of this paper was to provide a systematic overview of all recent (2007–2011) accelerometer validation studies using DLW as the reference. The PubMed Central database was searched using the following keywords: doubly or double labelled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. Limits were set to include articles from 2007 to 2011, as earlier publications were covered in a previous review. In total, 38 articles were identified, of which 25 were selected to contain sufficient new data. Eighteen different accelerometers were validated. There was a large variability in accelerometer output and their validity to assess daily physical activity. Activity type recognition has great potential to improve the assessment of physical activity‐related health outcomes. So far, there is little evidence that adding other physiological measures such as heart rate significantly improves the estimation of energy expenditure.

Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer

Accelerometers are often used to quantify the acceleration of the body in arbitrary units (counts) to measure physical activity (PA) and to estimate energy expenditure. The present study investigated whether the identification of types of PA with one accelerometer could improve the estimation of energy expenditure compared with activity counts. Total energy expenditure (TEE) of 15 subjects was measured with the use of double-labeled water. The physical activity level (PAL) was derived by dividing TEE by sleeping metabolic rate. Simultaneously, PA was measured with one accelerometer. Accelerometer output was processed to calculate activity counts per day (AC(D)) and to determine the daily duration of six types of common activities identified with a classification tree model. A daily metabolic value (MET(D)) was calculated as mean of the MET compendium value of each activity type weighed by the daily duration. TEE was predicted by AC(D) and body weight and by AC(D) and fat-free mass, with a standard error of estimate (SEE) of 1.47 MJ/day, and 1.2 MJ/day, respectively. The replacement in these models of AC(D) with MET(D) increased the explained variation in TEE by 9%, decreasing SEE by 0.14 MJ/day and 0.18 MJ/day, respectively. The correlation between PAL and MET(D) (R(2) = 51%) was higher than that between PAL and AC(D) (R(2) = 46%). We conclude that identification of activity types combined with MET intensity values improves the assessment of energy expenditure compared with activity counts. Future studies could develop models to objectively assess activity type and intensity to further increase accuracy of the energy expenditure estimation.

Ethnic differences in body composition and the associated metabolic profile: A comparative study between Asians and Caucasians

It is estimated that Asia will be the home of more than 100 million people with type 2 diabetes by the year of 2025. This region combines a high proportion of the worlds population with rapidly rising diabetes prevalence rates. The increase in diabetes in Asia differs from that reported in other parts of the world: it has developed in a shorter time, in a younger age group, and in people with lower body-mass index (BMI). Studies reported that for the same BMI, Asians have a higher body fat percentage, a prominent abdominal obesity, a higher intramyocellular lipid and/or a higher liver fat content compared to Caucasians. These characteristics may contribute to a higher predisposition to insulin resistance at a lesser degree of obesity than Caucasians. The differences in body composition are more pronounced depending on the region. For the same BMI, among three major ethnic groups in Asia, Asian Indians have the highest body fat, followed by Malay and Chinese. Lower insulin sensitivity is already observed in Asian Indian adolescents with a higher body fat and abdominal obesity compared to Caucasian adolescents. In general, Asian adolescents share the same feature of body composition such as higher body subcutaneous fat, lower appendicular skeletal muscle and lower gynoid fat compared to Caucasian adolescents. This unfavourable body composition may predispose to the development of insulin resistance at later age. Genetics may play a role and the interaction with environmental factors (changes in lifestyle) could increase the risk of developing the metabolic syndrome.

Physical activity and human energy expenditure

Purpose of reviewThis is a review on the measurement of physical activity under daily life conditions. The focus is on the doubly labelled water method and accelerometry. Doubly labelled water is a gold standard and the reference for the validation of field methods to assess physical activity. Accelerometry is the most objective and precise technique to assess activity patterns in terms of frequency, duration and intensity. Applications of the two techniques are illustrated with the limits of physical activity and energy expenditure and with activity intensity as a determinant of the physical activity level. Recent findingsThe upper limit of the physical activity index (total energy expenditure as a multiple of basal metabolic rate) of 2.5, as derived from cross-sectional data, is confirmed by training intervention studies. Exercise training, in which total energy expenditure was measured before and at the end of the training programme, showed no increase in physical activity index when training was combined with an energy restricted diet and in elderly subjects. In children, the distribution of time spent at activities with low and high intensity determines the physical activity index while in adults moderate-intensity activities are the main determinant. SummaryIn adults, within the normal physical activity index range, the distribution of time spent at activities with low and moderate intensity determines the physical activity level. High-intensity activity does not have much impact on daily energy expenditure. High-intensity activity is not required to increase the activity energy expenditure.

The role of physical activity in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory auto-immune disease, causing progressive damage to the musculoskeletal system. Many patients with RA also suffer from accelerated muscle loss or cachexia, which contributes to the loss of physical function and quality of life. Physical activity plays a central role in the management of the disease as it is essential to maintain muscle strength and endurance, range of motion and the ability to perform activities of daily life. On the other hand, given the nature of the disease, there is always an increased risk for injury. There is a large amount of literature investigating the effect of exercise interventions on muscle function and disease activity. These studies show that exercise clearly improves muscle function without affecting disease activity. Studies including radiographic evaluation of joint damage as an endpoint also show that there is no evidence that exercise, even high-intensity exercise, increases inflammation or joint damage, although care should be taken with patients with severe baseline damage. Regarding daily physical activity (exercise is only one component of physical activity) there is hardly any research done showing either that physical activity is indeed decreased in patients or whether or not there is a relation between daily physical activity and disease activity. The results from studies looking at the effect of exercise on muscle mass or the ability to prevent or reverse cachexia are somewhat contradictory, but it seems that when the training dose is sufficiently large, gains in muscle mass can be achieved.

Estimation of free-living energy expenditure using a novel activity monitor designed to minimize obtrusiveness.

The aim of this study was to investigate the ability of a novel activity monitor designed to be minimally obtrusive in predicting free‐living energy expenditure. Subjects were 18 men and 12 women (age: 41 ± 11 years, BMI: 24.4 ± 3 kg/m2). The habitual physical activity was monitored for 14 days using a DirectLife triaxial accelerometer for movement registration (TracmorD) (Philips New Wellness Solutions, Lifestyle Incubator, the Netherlands). TracmorD output was expressed as activity counts per day (Cnts/d). Simultaneously, total energy expenditure (TEE) was measured in free living conditions using doubly labeled water (DLW). Activity energy expenditure (AEE) and the physical activity level (PAL) were determined from TEE and sleeping metabolic rate (SMR). A multiple‐linear regression model predicted 76% of the variance in TEE, using as independent variables SMR (partial‐r2 = 0.55, P < 0.001), and Cnts/d (partial r2 = 0.21, P < 0.001). The s.e. of TEE estimates was 0.9 MJ/day or 7.4% of the average TEE. A model based on body mass (partial‐r2 = 0.31, P < 0.001) and Cnts/d (partial‐r2 = 0.23, P < 0.001) predicted 54% of the variance in TEE. Cnts/d were significantly and positively associated with AEE (r = 0.54, P < 0.01), PAL (r = 0.68, P < 0.001), and AEE corrected by body mass (r = 0.71, P < 0.001). This study showed that the TracmorD is a highly accurate instrument for predicting free‐living energy expenditure. The miniaturized design did not harm the ability of the instrument in measuring physical activity and in determining outcome parameters of physical activity such as TEE, AEE, and PAL.

Determinants of Stunting and Overweight among Young Children and Adolescents in Sub-Saharan Africa

Background Stunting and overweight are nutritional problems affecting most of sub-Saharan Africa. The region now has the worlds highest rate of stunting among children (43%), while overweight and obesity are becoming a global epidemic, and Africa is not spared. The past two decades have seen a dramatic increase in obesity in sub-Saharan Africa. Objective The purpose of this systematic review is to explore the determinants of stunting and overweight in sub-Saharan Africa. Methods A literature search was conducted in PubMed using the key words stunting, overweight, obesity, Africa, sub-Saharan Africa, determinants, and prevalence. Limits were set to include articles published between 1990 and 2012. The systematic review resulted in 38 studies, and after selection based on title, content, and country of the study, 18 studies were eligible for this review. Data were analyzed by the chi-square test. Results The prevalence rates of stunting and over-weight were dependent on socioeconomic, demographic, and environmental factors. Many studies indicate that male children and those living in a rural setting are more likely to be stunted, whereas overweight among children depends more on age, household composition, occupation of the mother, and the mothers body mass index. Stunting occurred together with overweight among both boys and girls from 1 to 5 years of age. Stunting was more prevalent among boys than among girls. Indicators of socioeconomic status, such as mothers education, mothers occupation, and household income, were some of the determinants directly linked to stunting, whereas environmental factors, such as rural or urban setting and sanitation, influenced both stunting and overweight. Concurrent stunting and overweight is influenced by maternal and household factors, such as maternal height, age, and education, large household size, and lower socioeconomic status. Conclusions Although socioeconomic, demographic, and environmental factors were significant in determining stunting and overweight, other factors, such as nutrition and lifestyle, were important risk factors. Stunting in childhood is a risk factor that may result in overweight and obesity later in adolescence and adulthood, indicating the need to screen children below 1 year of age to identify stunting early in life. Promoting exclusive breastfeeding is reported to be important in preventing both stunting and overweight among children. More research is needed to explore the relationship between stunting and overweight and to explore policy guidelines to address the phenomenon.

Accelerometry and heart rate as a measure of physical fitness: proof of concept.

PURPOSE This study focused on developing a new method to assess VO2max outside laboratory conditions and without the need for maximal exertion. We hypothesized that the combined use of accelerometry and HR monitoring, under daily life conditions, could provide a good estimate of physical fitness. METHODS Twenty-six healthy subjects (15 women, 11 men), aged 28 +/- 7 yr, performed a maximal incremental test on a bicycle ergometer to determine VO2max. Body composition was measured with underwater weighing and deuterium dilution using a three-compartment model. A triaxial accelerometer (Tracmor) and an HR monitor were worn for seven consecutive days under free-living conditions. The ratio of HR to activity counts per minute (ACM) was used as a fitness index (HR.ACM(-1)). RESULTS As hypothesized, HR.ACM(-1) was significantly correlated with VO2max. Using fat-free mass (FFM) (P < 0.0001), age (P = 0.025), and HR.ACM(-1) (P = 0.021) as the independent variables, the explained variation in VO2max was 76% (P < 0.0001, SEE = 363 mL x min(-1)). In order to generate a prediction formula that is applicable in the field when no data on body composition are available, the same analysis was done with body mass and gender in the model instead of FFM. HR.ACM(-1) was significantly (P = 0.023) correlated with VO2max. The total explained variation of the model was 71%, with a SEE of 409 mL x min(-1), or 13.7% of the average VO2max. CONCLUSION After correction for body composition, VO2max was significantly related to HR.ACM(-1). It is, to our knowledge, the first tool that yields a measure of VO2max by monitoring people in their daily life activities without the need for a specific protocol or for maximal exertion, and therefore is applicable to a large variety of subjects.