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Metabolic Equivalent

Diagnostics and Medical Technology · NLM MeSH · updated 2026-11-04 · version 1

Citations verified against PubMedNot yet clinician-reviewed9 referencesApproximately 5 min read

A measurement of oxygen uptake in a sitting, resting person (resting oxygen consumption), varying with age, sex, race, and other factors.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (921 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

A measurement of oxygen uptake in a sitting, resting person (resting oxygen consumption), varying with age, sex, race, and other factors. In normal adult men, one MET is approximately 3.5 ml O2/kg/min of body weight. Oxygen uptake during activities or work can be measured in METs which can be use to determine health status and exercise prescription.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Metabolic Equivalents.

Where it fits in the MeSH classification

Broader topics
Physical Examination; Oxygen Consumption

Related concepts

  • Oxygen

Research landscape

PubMed indexes 389 records tagged with the MeSH heading “Metabolic Equivalent” (counts retrieved 2026-10-31). 91 of them (23.4%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 284 records.

Reviews account for 22 records (5.7%) and meta-analyses for 6. Randomized controlled trials number 27 (6.9%) as a share of all records on the topic.

PubMed records by publication periodthrough 1999: 0 records; 2000-2009: 22 records; 2010-2019: 284 records; 2020 onward: 91 records0through 1999222000-20092842010-2019912020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 19990
2000-200922
2010-2019284
2020 onward91
Share of records by publication typeReviews: 5.7 percent; Meta-analyses: 1.5 percent; Randomized controlled trials: 6.9 percentReviews5.7% (22)Meta-analyses1.5% (6)Randomized controlled trials6.9% (27)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 389 PubMed records
TypeRecordsShare
Reviews225.7%
Meta-analyses61.5%
Randomized controlled trials276.9%

Method: PubMed query "Metabolic Equivalent"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.

Reading the evidence in diagnostics and medical technology

A test or device is judged by how well it detects a condition, how often it gives false alarms or misses cases, and whether using it improves outcomes for people. Accuracy depends on who is tested and how common the condition is, so a test that performs well in a specialist hospital can perform differently in the community. Check the reference standard, the population studied, the sensitivity and specificity and whether results were confirmed in a separate group.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Metabolic equivalent of task (METs) thresholds as an indicator of physical activity intensity
Mendes MA, da Silva I, Ramires V, Reichert F, Martins R, Ferreira R, et al.
2018Research article
Design not recorded in structured metadata
153cc by
PMID 30024953 · DOI · PMC6053180
Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults
Tudor-Locke C, Aguiar EJ, Han H, Ducharme SW, Schuna JM, Barreira TV, et al.
2019Research article
Design not recorded in structured metadata
125cc by
PMID 30654810 · DOI · PMC6337834
Criterion and concurrent validity of the activPAL™ professional physical activity monitor in adolescent females
Dowd KP, Harrington DM, Donnelly AE
2012Research article
Design not recorded in structured metadata
83cc by
PMID 23094069 · DOI · PMC3477132
From movement to METs: A validation of ActTrust® for energy expenditure estimation and physical activity classification in young adults
Dos Santos Batista E, Basilio Silva Gomes SR, de Morais Ferreira AB, França LGS, Fontenele Araújo J, Mortatti AL, et al.
2026Research article
Design not recorded in structured metadata
1cc by
PMID 42090415 · DOI · PMC13148694

Metabolic equivalent of task (METs) thresholds as an indicator of physical activity intensity [1]

Research article Mendes MA, da Silva I, Ramires V, Reichert F, Martins R, Ferreira R, et al. · · 2018 · cited 153 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
The purpose of the study was to identify and compare validity parameters of different absolute intensity thresholds in METs, using relative intensity classification as criterion measure.
Closing excerpt
Moreover, these parameters presented relatively high accuracy, even when applied to specific groups such as sex, age, nutritional status and physical fitness.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (177 words)

The purpose of the study was to identify and compare validity parameters of different absolute intensity thresholds in METs, using relative intensity classification as criterion measure. Convenience sampling was used to recruit total of 112 adults. The participants carried out an incremental maximal cycle ergometer test and asked to perform nine free-living activities. The oxygen uptake was measured by a VO2000® gas analyser throughout the tests. The intensity thresholds were identified using Receiver Operator Characteristic (ROC) curve analysis, having relative intensity categories as criterion measure. A total of 103 participants attended the two visits. Among 54 men and 49 women, the mean (± SD) ages were 36.1 (± 11.1) and 33.9 (± 10.6) years, respectively. The intensity thresholds identified were 4.9 METs for moderate and 6.8 METs for vigorous physical activity. In conclusion, the physical activity thresholds, generated according to the entire sample, were higher and presented improved specificity when compared to thresholds currently recommended. Moreover, these parameters presented relatively high accuracy, even when applied to specific groups such as sex, age, nutritional status and physical fitness.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 30024953 · DOI · PMC6053180

Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults [2]

Research article Tudor-Locke C, Aguiar EJ, Han H, Ducharme SW, Schuna JM, Barreira TV, et al. · · 2019 · cited 125 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundPrevious studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities.
Closing excerpt
gov ( NCT02650258 ).
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (276 words)

BackgroundPrevious studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities.PurposeTo establish definitive heuristic (i.e., evidence-based, practical, rounded) thresholds linking cadence with absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity.MethodsIn this laboratory-based cross-sectional study, 76 healthy adults (10 men and 10 women representing each 5-year age-group category between 21 and 40 years, BMI = 24.8 ± 3.4 kg/m2) performed a series of 5-min treadmill bouts separated by 2-min rests. Bouts began at 0.5 mph and increased in 0.5 mph increments until participants: 1) chose to run, 2) achieved 75% of their predicted maximum heart rate, or 3) reported a Borg rating of perceived exertion > 13. Cadence was hand-tallied, and intensity (METs) was measured using a portable indirect calorimeter. Optimal cadence thresholds for moderate and vigorous ambulatory intensities were identified using a segmented regression model with random coefficients, as well as Receiver Operating Characteristic (ROC) models. Positive predictive values (PPV) of candidate heuristic thresholds were assessed to determine final heuristic values.ResultsOptimal cadence thresholds for 3 METs and 6 METs were 102 and 129 steps/min, respectively, using the regression model, and 96 and 120 steps/min, respectively, using ROC models. Heuristic values were set at 100 steps/min (PPV of 91.4%), and 130 steps/min (PPV of 70.7%), respectively.ConclusionsCadence thresholds of 100 and 130 steps/min can serve as reasonable heuristic thresholds representative of absolutely-defined moderate and vigorous ambulatory intensity, respectively, in 21-40 year olds. These values represent useful proxy values for recommending and modulating the intensity of ambulatory behavior and/or as measurement thresholds for processing accelerometer data.Trial registrationClinicaltrials.gov ( NCT02650258 ).

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 30654810 · DOI · PMC6337834

Criterion and concurrent validity of the activPAL™ professional physical activity monitor in adolescent females [3]

Research article Dowd KP, Harrington DM, Donnelly AE · · 2012 · cited 83 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundThe activPAL has been identified as an accurate and reliable measure of sedentary behaviour.
Closing excerpt
96, pConclusionsThese findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (236 words)

BackgroundThe activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer.MethodologiesThirty adolescent females (15 developmental; 15 cross-validation) aged 15-18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, pConclusionsThese findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 23094069 · DOI · PMC3477132

From movement to METs: A validation of ActTrust® for energy expenditure estimation and physical activity classification in young adults [4]

Research article Dos Santos Batista E, Basilio Silva Gomes SR, de Morais Ferreira AB, França LGS, Fontenele Araújo J, Mortatti AL, et al. · · 2026 · cited 1 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Estimating physical activity (PA) levels is a challenging and expensive task.
Closing excerpt
Our findings support the use of ActTrust® devices as simple, cost-effective tool for 24-hour assessments of EE.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (232 words)

Estimating physical activity (PA) levels is a challenging and expensive task. An alternative could be the use of actigraphy devices to estimate PA. This has been previously done to a number of devices, including ActiGraph® GT3X + . In this study, we validated ActTrust® against the widely used GT3X+ and compared activity counts to metabolic equivalents (METs) derived from indirect calorimetry during treadmill walking and running. Fifty-six young adults (34 men, 22 women) participated in controlled effort exercises including light, moderate, vigorous, and very vigorous activity intensities. We developed a linear model to estimate energy expenditure (EE) from movement count of combinations of devices placed at hip or wrist. We then estimated cut-off points for each intensity range. Our results showed correlations between treadmill speed and both METs (r = 0.95, p < 0.05) and movement counts from both GT3X+ and ActTrust devices placed either on the hip (r = 0.94, p < 0.05; r = 0.93, p < 0.05) or on the wrist (r = 0.88, p < 0.05; r = 0.88, p < 0.05), respectively. Our proposed model performed well with balanced accuracies above 0.77 for all intensity ranges and over 0.9 for light and moderate activity. This is the first study to model estimate and validate PA intensity thresholds on ActTrust® devices. Our findings support the use of ActTrust® devices as simple, cost-effective tool for 24-hour assessments of EE.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42090415 · DOI · PMC13148694

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Using cadence to study free-living ambulatory behaviour [5]
    Tudor-Locke C, Rowe DA · Sports Med · 2012 · cited 146 times (Europe PMC)
  • Research article Using Metabolic Equivalents in Clinical Practice [6]
    Franklin BA, Brinks J, Berra K, Lavie CJ, Gordon NF, Sperling LS · Am J Cardiol · 2018 · cited 60 times (Europe PMC)
  • Research article Oxygen Consumption and Metabolic Equivalents During Physical Activities in Stroke: A Systematic Review [7]
    Shimizu N, Kanai M, Ota T · Physiother Res Int · 2025 · cited 1 times (Europe PMC)
  • Research article Metabolic Equivalents as a Foundational Physical Activity Metric: Origins, Validity, and Challenges [8]
    Leal-Martín J, Sánchez-Martín C, Keadle SK, Mañas A, Alegre LM, Ara I · Curr Sports Med Rep · 2026 · cited 0 times (Europe PMC)
  • Research article Metabolic intensity and energy cost of Pilates exercises: an exploratory systematic review and meta-analysis of limited and heterogeneous evidence [9]
    Vitor GBB, de Oliveira LC, Pessôa RAG, Aguiar AF, de Oliveira RG · Syst Rev · 2026 · cited 0 times (Europe PMC)

References

  1. Mendes MA, da Silva I, Ramires V, Reichert F, Martins R, Ferreira R, et al.. Metabolic equivalent of task (METs) thresholds as an indicator of physical activity intensity. . 2018. PMID 30024953 · DOI · PMC6053180
  2. Tudor-Locke C, Aguiar EJ, Han H, Ducharme SW, Schuna JM, Barreira TV, et al.. Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults. . 2019. PMID 30654810 · DOI · PMC6337834
  3. Dowd KP, Harrington DM, Donnelly AE. Criterion and concurrent validity of the activPAL™ professional physical activity monitor in adolescent females. . 2012. PMID 23094069 · DOI · PMC3477132
  4. Dos Santos Batista E, Basilio Silva Gomes SR, de Morais Ferreira AB, França LGS, Fontenele Araújo J, Mortatti AL, et al.. From movement to METs: A validation of ActTrust® for energy expenditure estimation and physical activity classification in young adults. . 2026. PMID 42090415 · DOI · PMC13148694
  5. Tudor-Locke C, Rowe DA. Using cadence to study free-living ambulatory behaviour. Sports Med. 2012. PMID 22462794 · DOI
  6. Franklin BA, Brinks J, Berra K, Lavie CJ, Gordon NF, Sperling LS. Using Metabolic Equivalents in Clinical Practice. Am J Cardiol. 2018. PMID 29229271 · DOI
  7. Shimizu N, Kanai M, Ota T. Oxygen Consumption and Metabolic Equivalents During Physical Activities in Stroke: A Systematic Review. Physiother Res Int. 2025. PMID 39887852 · DOI
  8. Leal-Martín J, Sánchez-Martín C, Keadle SK, Mañas A, Alegre LM, Ara I. Metabolic Equivalents as a Foundational Physical Activity Metric: Origins, Validity, and Challenges. Curr Sports Med Rep. 2026. PMID 42385165 · DOI
  9. Vitor GBB, de Oliveira LC, Pessôa RAG, Aguiar AF, de Oliveira RG. Metabolic intensity and energy cost of Pilates exercises: an exploratory systematic review and meta-analysis of limited and heterogeneous evidence. Syst Rev. 2026. PMID 41495794 · DOI · PMC12869938

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-11-04.

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At a glance

389
PubMed records on this heading
23%
published since 2020
22
review articles
27
randomized trials
9
verified references below

Counts come from PubMed on 2026-10-31; they show how much has been written, not how strong the evidence is.

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