Comparison between data processing from GT3X+ accelerometer for vigorous moderate physical activity
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , |
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 |