Evidence map›Paper›PMID 27270210›Full record

Trial reportApplied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme2016

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

John B Correa, John W Apolzan, Desti N Shepard, Daniel P Heil, Jennifer C Rood, Corby K Martin

Abstract readClinical Trial
In one paragraph

Trial report in Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
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

6 authors.

John B Correaa Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
John W Apolzana Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
Desti N Sheparda Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
Daniel P Heilb Montana State University, Bozeman, MT 59717, USA.
Jennifer C Rooda Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
Corby K Martina Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.

Funding

Tracking & Evaluation CoreU54GM104940 · NIGMS · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI Peter Todd Katzmarzyk · 2012 to 2026
$69.1M
Research BaseP30DK072476 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI Leanne Maree Redman · 2005 to 2026
$26.5M
Validation of innovative technology to measure the energy intake of free-living hR21AG032231 · NIA · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI MARTIN, CORBY K · 2007 to 2009
$664k
Energy Expenditure: Relation with Body Mass Over TimeK23DK068052 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI MARTIN, CORBY K · 2006 to 2009
$300k
NIA NIH HHS R21 AG032231NIDDK NIH HHS K23 DK068052NIDDK NIH HHS P30 DK072476NIGMS NIH HHS U54 GM104940
6 · The paper itself

Abstract

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity.

Indexed as

Body WeightEnergy MetabolismExerciseFitness TrackersPostureAdultBody Mass IndexCaloric RestrictionFemaleHumansLinear ModelsMaleMiddle AgedWalkingaccélérométrieaccelerometryActicalactivity energy expenditureassignation posturaldépense énergétique durant une activitédépense énergétique totaledoubly labeled watereau doublement marquéeIDEEAposture allocationSenseweartotal energy expenditure

Identifiers

PMID27270210
PMCPMC4936932

What OpenQuestion holds

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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.