Evidence map›Paper›PMID 36806337›Full record

ArticleScientific reports2023

Comparison of different software for processing physical activity measurements with accelerometry.

Sanne Verhoog, Cédric Gubelmann, Arjola Bano, Taulant Muka, Oscar H Franco, Pedro Marques-Vidal

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

6 authors.

Sanne VerhoogInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Cédric GubelmannDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Office BH10-642, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
Arjola BanoInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Taulant MukaInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Oscar H FrancoInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Pedro Marques-VidalDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Office BH10-642, Rue du Bugnon 46, 1011, Lausanne, Switzerland. pedro-manuel.marques-vidal@chuv.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several raw-data processing software for accelerometer-measured physical activity (PA) exist, but whether results agree has not been assessed. We examined the agreement between three different software for raw accelerometer data, and associated their results with cardiovascular risk. A cross-sectional analysis conducted between 2014 and 2017 in 2693 adults (53.4% female, 45-86 years) living in Lausanne, Switzerland was used. Participants wore the wrist-worn GENEActive accelerometer for 14 days. Data was processed with the GENEActiv manufacturer software, the Pampro package in Python and the GGIR package in R. For the latter, two sets of thresholds "White" and "MRC" defining levels of PA and two versions (1.5-9 and 1.11-1) for the "MRC" threshold were used. Cardiovascular risk was assessed using the SCORE risk score. Time spent (mins/day) in stationary, light, moderate and vigorous PA ranged from 633 (GGIR-MRC) to 1147 (Pampro); 93 (GGIR-White) to 196 (GGIR-MRC); 19 (GGIR-White) to 161 (GENEActiv) and 1 (GENEActiv) to 26 (Pampro), respectively. Spearman correlations between results ranged between 0.317 and 0.995, while concordance coefficients ranged between 0.035 and 0.968. With some exceptions, the line of perfect agreement was not in the 95% confidence interval of the Bland-Altman plots. Compliance to PA guidelines varied considerably: 99.8%, 98.7%, 76.3%, 72.6% and 50.2% for Pampro, GENEActiv, GGIR-MRC v.1.11-1, GGIR-MRC v.1.4-9 and GGIR-White, respectively. Cardiovascular risk decreased with increasing time spent in PA across most software packages. We found large differences in PA estimation between software and thresholds used, which makes comparability between studies challenging.

Indexed as

AccelerometryExerciseAdultCross-Sectional StudiesFemaleHeart Disease Risk FactorsHumansMaleSoftware

Identifiers

PMID36806337
PMCPMC9938888

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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.