Metabolic equivalent: One size does not fit all

School of Human Movement Studies, Queensland Univ. of Technology, Victoria Park Rd., Kelvin Grove, Q4059, Brisbane, Queensland, Australia.
Journal of Applied Physiology (Impact Factor: 3.06). 10/2005; 99(3):1112-9. DOI: 10.1152/japplphysiol.00023.2004
Source: PubMed


The metabolic equivalent (MET) is a widely used physiological concept that represents a simple procedure for expressing energy cost of physical activities as multiples of resting metabolic rate (RMR). The value equating 1 MET (3.5 ml O2 x kg(-1) x min(-1) or 1 kcal x kg(-1) x h(-1)) was first derived from the resting O2 consumption (VO2) of one person, a 70-kg, 40-yr-old man. Given the extensive use of MET levels to quantify physical activity level or work output, we investigated the adequacy of this scientific convention. Subjects consisted of 642 women and 127 men, 18-74 yr of age, 35-186 kg in weight, who were weight stable and healthy, albeit obese in some cases. RMR was measured by indirect calorimetry using a ventilated hood system, and the energy cost of walking on a treadmill at 5.6 km/h was measured in a subsample of 49 men and 49 women (26-45 kg/m2; 29-47 yr). Average VO2 and energy cost corresponding with rest (2.6 +/- 0.4 ml O2 x kg(-1) x min(-1) and 0.84 +/- 0.16 kcal x kg(-1) x h(-1), respectively) were significantly lower than the commonly accepted 1-MET values of 3.5 ml O2 x kg(-1) x min(-1) and 1 kcal x kg(-1) x h(-1), respectively. Body composition (fat mass and fat-free mass) accounted for 62% of the variance in resting VO2 compared with age, which accounted for only 14%. For a large heterogeneous sample, the 1-MET value of 3.5 ml O2 x kg(-1) x min(-1) overestimates the actual resting VO2 value on average by 35%, and the 1-MET of 1 kcal/h overestimates resting energy expenditure by 20%. Using measured or predicted RMR (ml O2 x kg(-1) x min(-1) or kcal x kg(-1) x h(-1)) as a correction factor can appropriately adjust for individual differences when estimating the energy cost of moderate intensity walking (5.6 km/h).

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    • "Recommendations for exercise to provide health benefits are for at least 30 min of moderate intensity exercise five days a week (Garber et al., 2011; Thompson et al., 2003; Haskell et al., 2007). Exercise intensity can be quantified by the metabolic equivalent (MET); MET-values are calculated as multiples of average resting oxygen uptake of 3.5 ml@BULLETmin -1 @BULLETkg -1 (Byrne et al., 2005). In young adults, METs between 4.8 and 7.1 represent exercise of moderate intensity when compared to relative V̇ O2max (Garber et al., 2011). "
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    ABSTRACT: Regular moderate-intensity exercise provides health benefits. The aim of this study was to examine whether the selected exercise intensity and physiological responses during exergaming in a single and multiplayer mode in the same physical space were game-dependent. Ten males (mean ±SD, age: 23 ±5 years, body mass: 84.2 ±15.6 kg, body height: 180 ±7 cm, body mass index: 26.0 ±4.0 kg·m(-2)) played the games Kinect football, boxing and track & field (3 × ∼10 min, ∼ 2 min rest periods) in similar time sequence in two sessions. Physiological responses were measured with the portable Cosmed K4b(2) pulmonary gas exchange system. Single play demands were used to match with a competitive opponent in a multiplay mode. A within-subjects crossover design was used with one-way ANOVA and a post-hoc t-test for analysis (p<0.05). Minute ventilation, oxygen uptake and the heart rate were at least 18% higher during a multiplayer mode for Kinect football and boxing but not for track & field. Energy expenditure was 21% higher during multiplay football. Single play track & field had higher metabolic equivalent than single play football (5.7 ±1.6, range: 3.2-8.6 vs 4.1 ±1.0, range: 3.0-6.1, p<0.05). Exergaming in a multiplayer mode can provide higher physiological demands but the effects are game-dependent. It seems that exergaming with low intensity in a multiplayer mode may provide a greater physical challenge for participants than in a single play mode but may not consistently provide sufficient intensity to acquire health benefits when played regularly as part of a programme to promote and maintain health in young adults.
    Full-text · Article · Aug 2015 · Journal of Human Kinetics
    • "A distinction between different activities could be established, for instance, by the group of muscles activated by performing each of these activities. Another classification of physical activity could be determined by their metabolic equivalent (MET) or energy required to perform an activity, while the adequacy of this metric has been put into question [11]. Previous studies had shown that awareness about the benefits of physical activity and its relevance to the risk of heart disease was disappointing [24]. "
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    ABSTRACT: Physical activity is recognized as one of the key factors for a healthy life due to its beneficial effects. The range of physical activities is very broad, and not all of them require the same effort to be performed nor have the same effects on health. For this reason, automatically recognizing the physical activity performed by a user (or patient) turns out to be an interesting research field, mainly because of two reasons: (1) it increases personal awareness about the activity being performed and its consequences on health, allowing to receive proper credit (e.g. social recognition) for the effort; and (2) it allows doctors to perform continuous remote patient monitoring. This paper proposes a new approach for improving activity recognition by describing an activity recognition chain (ARC) that is optimized by means of genetic algorithms. This optimization process determines the most suitable and informative set of features that turns out into higher recognition accuracy while reducing the total number of sensors required to track the user activity. These improvements can be translated into lower costs in hardware and less intrusive devices for the patients. In this work, for the assessment of the proposed approach versus other techniques and for replication purposes, a publicly available dataset on physical activity (PAMAP2) has been used. Experiments are designed and conducted to evaluate the proposed ARC by using leave-one-subject-out cross validation and results are encouraging, reaching an average classification accuracy of about 94%.
    No preview · Conference Paper · Jul 2015
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    • "Les équivalences en MET sont des approximations, et il est évident que la congruence en (1) n'a pas la prétention de remplacer une mesure du métabolisme de base, ni son estimation à partir d'équations dédiées [24] [25]. En effet, appliquée strictement , elle conduit à une surestimation [26] surtout marquée chez les femmes et les personnes âgées qui présentent en moyenne une masse maigre réduite par rapport aux hommes et aux jeunes adultes. La principale raison est qu'elle ne se réfère qu'à la masse et que les facteurs âge, taille et sexe ne sont pas utilisés pour moduler l'évaluation (sauf dans certaines études où on utilise 0,95 kcal/kg/h chez la femme au lieu de (1)). "
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    ABSTRACT: For physical activity promotion to be effective from a public health view, adequate communication between the different actors is required. In this perspective, we propose to explicit the bioenergetic notions used to quantify and qualify intensity of physical activities, physical activity and sedentary behaviors, and lifestyles. Public health recommendations for physical activity in healthy adults from different authorities vary between 675 and 1350 METs/min per week, which, for example, is the equivalent of the energy spent with the participation 5 times per week in activities leading to a 4.5-times increase of the basal metabolic rate during 30 or 60 minutes for the low and high limit, respectively. For every population category, researchers in different scientific fields and all various responsible actors must work harder or better to reach successful physical activity promotion that would be evidenced by rarefaction of sedentary lifestyles. Very different lifestyles are compatible with energy expenditure large enough at a population scale to contribute to the prevention and control of many non-communicable diseases.
    Full-text · Article · May 2015 · Nutrition Clinique et Métabolisme
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