Evidence map›Paper›PMID 31511063›Full record

ArticleBMC research notes2019

Deriving objectively-measured sedentary indices from free-living accelerometry data in rural and urban African settings: a cost effective approach.

Ian Cook

Abstract read
In one paragraph

Article in BMC research notes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

1 author.

Ian CookPhysical Activity Epidemiology Laboratory, Faculty of Humanities, University of Limpopo (Turfloop Campus), P.O. Box 459, Fauna Park, Polokwane, Limpopo Province, 0787, South Africa. ian.cook@ul.ac.za.ORCID http://orcid.org/0000-0001-5098-2936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the agreement between two data reduction approaches for detecting sedentary breaks from uni-axial accelerometry data collected in human participants. Free-living, uni-axial accelerometer data (n = 318) were examined for sedentary breaks using two different methods (Healy-Matthews; MAH/UFFE). The data were cleaned and reduced using MAH/UFFE Analyzer software and custom Microsoft Excel macro's, such that the average daily sedentary break number were calculated for each data record, for both methods.

resultsThe Healy-Matthews and MAH/UFFE average daily break number correlated closely (R

Indexed as

AlgorithmsSedentary BehaviorAccelerometryAdultCost-Benefit AnalysisExerciseFemaleHumansMaleMiddle AgedRegression AnalysisRural PopulationSoftwareUrban PopulationAccelerometerMeasurementMovement monitorSedentarism

Identifiers

PMID31511063
PMCPMC6739927

What OpenQuestion holds

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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.