Metabolic equivalent: one size does not fit all.
ABSTRACT 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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ABSTRACT: The purposes of this study were: 1) to show the item difficulty hierarchy of walking/moving construct of the International Classification of Functioning, Disability and Health-Activity Measure (ICF-AM), 2) to evaluate the item-level psychometrics for model fit, 3) to describe the relevant physical activity defined by level of activity intensity expressed as Metabolic Equivalent of Tasks (MET), and 4) to explore what extent the empirical activity hierarchy of the ICF-AM is linked to the conceptual model based on the level of energy expenditure described as MET. One hundred and eight participants with lower extremity impairments were examined for the present study. A newly created activity measure, the ICF-AM using an item response theory (IRT) model and computer adaptive testing (CAT) method, has a construct on walking/moving construct. Based on the ICF category of walking and moving, the instrument comprised items corresponding to: walking short distances, walking long distances, walking on different surfaces, walking around objects, climbing, and running. The item difficulty hierarchy was created using Winstep software for 20 items. The Rasch analyses (1-parameter IRT model) were performed on participants with lower extremity injuries who completed the paper and pencil version of walking/moving construct of the ICF-AM. The classification of physical activity can also be performed by the use of METs that is often preferred to determine the level of physical activity. The empirical item hierarchy of walking, climbing, running activities of the ICF-AM instrument was similar to the conceptual activity hierarchy based on the METs. The empirically derived item difficulty hierarchy of the ICF-AM may be useful in developing MET-based activity measure questionnaires. In addition to convenience of applying items to questionnaires, implications of the finding could lead to the use of CAT method without sacrificing the objectivity of physiologic measures.09/2013; 20(3). DOI:10.12674/ptk.2013.20.3.089
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ABSTRACT: Scientific evidence for the primary prevention of cancer caused by physical activity of regular moderate-intensity or greater is rapidly accumulating in this field. About 300 epidemiologic studies on the association between physical activity and cancer risk have been conducted worldwide. The objectives of this paper were three-fold: (i) to describe briefly the components of physical activity and its quantification; (ii) to summarize the most important conclusions available from comprehensive reports, and reviews of the epidemiologic individual and intervention studies on a role physical activity in cancer prevention; (iii) to present proposed biological mechanisms accounting for effects of activity on cancer risk. The evidence of causal linked physical activity and cancer risk is found to be strong for colon cancer - convincing; weaker for postmenopausal breast and endometrium cancers - probable; and limited suggestive for premenopausal breast, lung, prostate, ovary, gastric and pancreatic cancers. The average risk reductions were reported to be 20-30%. The protective effects of physical activity on cancer risk are hypothesized to be through multiple interrelated pathways: decrease in adiposity, decrease in sexual and metabolic hormones, changes in biomarkers and insulin resistance, improvement of immune function, and reduction of inflammation. As there are several gaps in the literature for associations between activity and cancer risk, additional studies are needed. Future research should include studies dealing with limitations in precise estimates of physical activity and of a lack of consensus on what defines sedentary behavior of individuals and those linked with the proposed biomarkers to cancer risk and controlled exercise intervention trials.Asian Pacific journal of cancer prevention: APJCP 07/2013; 14(7):3993-4003. DOI:10.7314/APJCP.2013.14.7.3993 · 1.50 Impact Factor
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ABSTRACT: To understand the impact of physical activity (PA) on health, valid accelerometer count cut points must be applied to measure PA. Because cut points may be population specific, we aimed to establish accelerometer cut points for moderate PA (MPA) and vigorous PA (VPA) (defined as ≥3 and ≥6 metabolic equivalents, resp.) in young-to-middle-aged obese-to-severely obese subjects. Data from 42 subjects (11 men; body mass index 39.8 ± 5.7; age 43.2 ± 9.2 years) who performed a treadmill calibration using the Actigraph GT1M, were analyzed using ordinary linear regression (OLR), linear mixed model regression (MIX), and receiver operating characteristics curves (ROC 1; ROC 2). Cut points obtained from the models were quite different (612 to 1646 counts/min for MPA; 3061 to 7220 counts/min for VPA). We argue that the MIX approach, which resulted in cut points of 612 and 4980 counts/min for MPA and VPA, respectively, is the most appropriate method to establish accelerometer cut points in this setting. We conclude that accelerometer cut points are lower in young-to-middle-aged obese-to-severely obese subjects compared to young normal-weight subjects and that care should be taken when analyzing PA level in groups that vary in age and degree of obesity.Journal of obesity 11/2012; 2012:318176. DOI:10.1155/2012/318176