Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity

Detalhes bibliográficos
Autor(a) principal: Soares, Andrew
Data de Publicação: 2022
Outros Autores: Pancoti, Barbara Moço, Oliveira, Aldair José de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Journal of Physical Education (Maringá)
Texto Completo: https://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/59805
Resumo: The use of accelerometers to measure physical activity in epidemiological research presents challenges to increase comparability between studies that use this equipment. In this sense, the objective of this work is to compare time estimates in MVPA for adults from different data processing methods, using the Actigraph GT3X+ accelerometer. This is a cross-sectional study, from the baseline of the pilot study of the Longitudinal Study of the Determinants of Physical Activity. Sample had 31 outsourced employees of both genders, with an average age of 47.05 years (SD=9.35). Participants used GT3X+ model accelerometers for seven consecutive days. The MVPA time estimate was generated using Actilife and R-package GGIR software. Descriptive statistical analyses, ANOVA and Bonferroni post-hoc for comparability were performed in the R software. Bland-Altman analysis was performed in SigmaPlot to assess bias and agreement. There was a significant difference in the mean time of MVPA between count-based data and raw data (p<0.001). The average time in MVPA was shorter from processing by raw data than in counts (-264.81 min/day; p<0.001). Concluding that the findings suggest that there is no statistically equivalence between the methods compared to estimate MVPA time.
id UEM-9_69f21ccb5eb9d9a3ae8dbe974a9c8a32
oai_identifier_str oai:periodicos.uem.br/ojs:article/59805
network_acronym_str UEM-9
network_name_str Journal of Physical Education (Maringá)
repository_id_str
spelling Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activityComparação entre processamentos de dados do acelerômetro GT3X+ para atividade física moderada E vigorosa.ActiGraphGGIRAccelerometerPhysical activityAdults.ActiGraphGGIRAcelerômetroAtividade físicaAdultosThe use of accelerometers to measure physical activity in epidemiological research presents challenges to increase comparability between studies that use this equipment. In this sense, the objective of this work is to compare time estimates in MVPA for adults from different data processing methods, using the Actigraph GT3X+ accelerometer. This is a cross-sectional study, from the baseline of the pilot study of the Longitudinal Study of the Determinants of Physical Activity. Sample had 31 outsourced employees of both genders, with an average age of 47.05 years (SD=9.35). Participants used GT3X+ model accelerometers for seven consecutive days. The MVPA time estimate was generated using Actilife and R-package GGIR software. Descriptive statistical analyses, ANOVA and Bonferroni post-hoc for comparability were performed in the R software. Bland-Altman analysis was performed in SigmaPlot to assess bias and agreement. There was a significant difference in the mean time of MVPA between count-based data and raw data (p<0.001). The average time in MVPA was shorter from processing by raw data than in counts (-264.81 min/day; p<0.001). Concluding that the findings suggest that there is no statistically equivalence between the methods compared to estimate MVPA time.O uso do acelerômetro para mensurar a atividade física em pesquisas epidemiológicas, apresenta desafios para aumentar a comparabilidade entre os estudos que utilizam esse equipamento. Nesse sentido o objetivo deste trabalho é comparar estimativas de tempo em AFMV para adultos provenientes de diferentes métodos de processamentos de dados, através do acelerômetro Actigraph GT3X+. Trata-se de um estudo transversal, da linha de base do estudo piloto do Estudo Longitudinal dos Determinantes da Atividade Física. Amostra contou com 31 funcionários terceirizados de ambos os sexos, com idade média de 47.05anos (DP=9.35). Os participantes utilizaram acelerômetros do modelo GT3X+ durante sete dias consecutivos. A estimativa de tempo de AFMV foi gerada através de software Actilife e R-package GGIR. Análises estatísticas descritivas, ANOVA e pos-hoc de Bonferroni para comparabilidade foram realizadas no software R. Análise de Bland-Altman foi realizado no SigmaPlot para avaliação de viés e concordância. Houve diferença significativa no tempo médio de AFMV entre os dados baseados em counts e dados brutos (p<0,001). O tempo médio em AFMV foi menor a partir do processamento por dados brutos do que o em counts (-264,81min/dia; p<0,001). Concluindo que os achados sugerem não haver, estatisticamente, equivalência entre os métodos comparados para estimar tempo de AFMV.Department of Physical Education - State University of Maringá (UEM), Maringá-PR, Brazil2022-07-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/5980510.4025/jphyseduc.v33i1.3344Journal of Physical Education; Vol 33 No 1 (2022): Journal of Physical Education; e-3344Journal of Physical Education; Vol. 33 Núm. 1 (2022): Journal of Physical Education; e-3344Journal of Physical Education; v. 33 n. 1 (2022): Journal of Physical Education; e-33442448-2455reponame:Journal of Physical Education (Maringá)instname:Universidade Estadual de Maringá (UEM)instacron:UEMporhttps://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/59805/751375154538Copyright (c) 2022 Soares et alhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSoares, AndrewPancoti, Barbara MoçoOliveira, Aldair José de2022-07-14T11:22:06Zoai:periodicos.uem.br/ojs:article/59805Revistahttp://periodicos.uem.br/ojs/index.php/RevEducFis/indexPUBhttps://old.scielo.br/oai/scielo-oai.php||revdef@uem.br2448-24552448-2455opendoar:2022-07-14T11:22:06Journal of Physical Education (Maringá) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
Comparação entre processamentos de dados do acelerômetro GT3X+ para atividade física moderada E vigorosa.
title Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
spellingShingle Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
Soares, Andrew
ActiGraph
GGIR
Accelerometer
Physical activity
Adults.
ActiGraph
GGIR
Acelerômetro
Atividade física
Adultos
title_short Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
title_full Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
title_fullStr Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
title_full_unstemmed Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
title_sort Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
author Soares, Andrew
author_facet Soares, Andrew
Pancoti, Barbara Moço
Oliveira, Aldair José de
author_role author
author2 Pancoti, Barbara Moço
Oliveira, Aldair José de
author2_role author
author
dc.contributor.author.fl_str_mv Soares, Andrew
Pancoti, Barbara Moço
Oliveira, Aldair José de
dc.subject.por.fl_str_mv ActiGraph
GGIR
Accelerometer
Physical activity
Adults.
ActiGraph
GGIR
Acelerômetro
Atividade física
Adultos
topic ActiGraph
GGIR
Accelerometer
Physical activity
Adults.
ActiGraph
GGIR
Acelerômetro
Atividade física
Adultos
description The use of accelerometers to measure physical activity in epidemiological research presents challenges to increase comparability between studies that use this equipment. In this sense, the objective of this work is to compare time estimates in MVPA for adults from different data processing methods, using the Actigraph GT3X+ accelerometer. This is a cross-sectional study, from the baseline of the pilot study of the Longitudinal Study of the Determinants of Physical Activity. Sample had 31 outsourced employees of both genders, with an average age of 47.05 years (SD=9.35). Participants used GT3X+ model accelerometers for seven consecutive days. The MVPA time estimate was generated using Actilife and R-package GGIR software. Descriptive statistical analyses, ANOVA and Bonferroni post-hoc for comparability were performed in the R software. Bland-Altman analysis was performed in SigmaPlot to assess bias and agreement. There was a significant difference in the mean time of MVPA between count-based data and raw data (p<0.001). The average time in MVPA was shorter from processing by raw data than in counts (-264.81 min/day; p<0.001). Concluding that the findings suggest that there is no statistically equivalence between the methods compared to estimate MVPA time.
publishDate 2022
dc.date.none.fl_str_mv 2022-07-14
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/59805
10.4025/jphyseduc.v33i1.3344
url https://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/59805
identifier_str_mv 10.4025/jphyseduc.v33i1.3344
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.uem.br/ojs/index.php/RevEducFis/article/view/59805/751375154538
dc.rights.driver.fl_str_mv Copyright (c) 2022 Soares et al
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Soares et al
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Department of Physical Education - State University of Maringá (UEM), Maringá-PR, Brazil
publisher.none.fl_str_mv Department of Physical Education - State University of Maringá (UEM), Maringá-PR, Brazil
dc.source.none.fl_str_mv Journal of Physical Education; Vol 33 No 1 (2022): Journal of Physical Education; e-3344
Journal of Physical Education; Vol. 33 Núm. 1 (2022): Journal of Physical Education; e-3344
Journal of Physical Education; v. 33 n. 1 (2022): Journal of Physical Education; e-3344
2448-2455
reponame:Journal of Physical Education (Maringá)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Journal of Physical Education (Maringá)
collection Journal of Physical Education (Maringá)
repository.name.fl_str_mv Journal of Physical Education (Maringá) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv ||revdef@uem.br
_version_ 1754732546587885568