Evidence map›Paper›PMID 26271677›Full record

Trial reportEuropean journal of applied physiology2016

Kids are not little adults: what MET threshold captures sedentary behavior in children?

Pedro F Saint-Maurice, Youngwon Kim, Gregory J Welk, Glenn A Gaesser

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in European journal of applied physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  18. Youth Metabolic Equivalents Differ Depending on Operational Definitions.Medicine and science in sports and exercise · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Pedro F Saint-MauriceDepartment of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. pedrosm@iastate.edu.
Youngwon KimDepartment of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. youngwon.kim@mrc-epid.cam.ac.uk.
Gregory J WelkDepartment of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. gwelk@iastate.edu.
Glenn A GaesserSchool of Nutrition and Health Promotion, Arizona State University, 550 N Third St, Phoenix, AZ, 85004, USA. glenn.gaesser@asu.edu.

Funding

A Wireless, Multimode, Artificial Neural Network-Based Physical Activity MonitorR01HL091006 · NHLBI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI GAESSER, GLENN A, PARKER, B EUGENE · 2008 to 2012
$2.2M
Medical Research Council MC_U106179473Medical Research Council MC_UU_12015/3NHLBI NIH HHS R01 HL091006
6 · The paper itself

Abstract

purposeThe study compares MET-defined cutpoints used to classify sedentary behaviors in children using a simulated free-living design.

methodsA sample of 102 children (54 boys and 48 girls; 7-13 years) completed a set of 12 activities (randomly selected from a pool of 24 activities) in a random order. Activities were predetermined and ranged from sedentary to vigorous intensities. Participant's energy expenditure was measured using a portable indirect calorimetry system, Oxycon mobile. Measured minute-by-minute VO2 values (i.e., ml/kg/min) were converted to an adult- or child-MET value using the standard 3.5 ml/kg/min or the estimated child resting metabolic rate, respectively. Classification agreement was examined for both the "standard" (1.5 adult-METs) and an "adjusted" (2.0 adult-METs) MET-derived threshold for classifying sedentary behavior. Alternatively, we also tested the classification accuracy of a 1.5 child-MET threshold. Classification accuracy of sedentary activities was evaluated relative to the predetermined intensity categorization using receiver operator characteristic curves.

resultsThere were clear improvements in the classification accuracy for sedentary activities when a threshold of 2.0 adult-METs was used instead of 1.5 METs (Se1.5 METs = 4.7%, Sp1.5 METs = 100.0%; Se2.0 METs = 36.9%, Sp2.0 METs = 100.0 %). The use of child-METs while maintaining the 1.5 threshold also resulted in improvements in classification (Se = 45.1%, Sp = 100.0%).

conclusionAdult-MET thresholds are not appropriate for children when classifying sedentary activities. Classification accuracy for identifying sedentary activities was improved when either an adult-MET of 2.0 or a child-MET of 1.5 was used.

Indexed as

Adolescent BehaviorChild BehaviorSedentary BehaviorAdolescentAdultAge FactorsBasal MetabolismCalorimetry, IndirectChildEnergy MetabolismFemaleHumansMaleMotor ActivityOxygen ConsumptionMeasurementPublic healthResting energy expenditureYouth

Identifiers

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Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.