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Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis
BACKGROUND: Determining patterns of physical activity throughout the day could assist in developing more personalized interventions or physical activity guidelines in general and, in particular, for women who are less likely to be physically active than men. OBJECTIVE: The aims of this report are to...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5814604/ https://www.ncbi.nlm.nih.gov/pubmed/29391341 http://dx.doi.org/10.2196/publichealth.9138 |
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author | Fukuoka, Yoshimi Zhou, Mo Vittinghoff, Eric Haskell, William Goldberg, Ken Aswani, Anil |
author_facet | Fukuoka, Yoshimi Zhou, Mo Vittinghoff, Eric Haskell, William Goldberg, Ken Aswani, Anil |
author_sort | Fukuoka, Yoshimi |
collection | PubMed |
description | BACKGROUND: Determining patterns of physical activity throughout the day could assist in developing more personalized interventions or physical activity guidelines in general and, in particular, for women who are less likely to be physically active than men. OBJECTIVE: The aims of this report are to identify clusters of women based on accelerometer-measured baseline raw metabolic equivalent of task (MET) values and a normalized version of the METs ≥3 data, and to compare sociodemographic and cardiometabolic risks among these identified clusters. METHODS: A total of 215 women who were enrolled in the Mobile Phone Based Physical Activity Education (mPED) trial and wore an accelerometer for at least 8 hours per day for the 7 days prior to the randomization visit were analyzed. The k-means clustering method and the Lloyd algorithm were used on the data. We used the elbow method to choose the number of clusters, looking at the percentage of variance explained as a function of the number of clusters. RESULTS: The results of the k-means cluster analyses of raw METs revealed three different clusters. The unengaged group (n=102) had the highest depressive symptoms score compared with the afternoon engaged (n=65) and morning engaged (n=48) groups (overall P<.001). Based on a normalized version of the METs ≥3 data, the moderate-to-vigorous physical activity (MVPA) evening peak group (n=108) had a higher body mass index (P=.03), waist circumference (P=.02), and hip circumference (P=.03) than the MVPA noon peak group (n=61). CONCLUSIONS: Categorizing physically inactive individuals into more specific activity patterns could aid in creating timing, frequency, duration, and intensity of physical activity interventions for women. Further research is needed to confirm these cluster groups using a large national dataset. TRIAL REGISTRATION: ClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/6vVyLzwft) |
format | Online Article Text |
id | pubmed-5814604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-58146042018-02-23 Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis Fukuoka, Yoshimi Zhou, Mo Vittinghoff, Eric Haskell, William Goldberg, Ken Aswani, Anil JMIR Public Health Surveill Original Paper BACKGROUND: Determining patterns of physical activity throughout the day could assist in developing more personalized interventions or physical activity guidelines in general and, in particular, for women who are less likely to be physically active than men. OBJECTIVE: The aims of this report are to identify clusters of women based on accelerometer-measured baseline raw metabolic equivalent of task (MET) values and a normalized version of the METs ≥3 data, and to compare sociodemographic and cardiometabolic risks among these identified clusters. METHODS: A total of 215 women who were enrolled in the Mobile Phone Based Physical Activity Education (mPED) trial and wore an accelerometer for at least 8 hours per day for the 7 days prior to the randomization visit were analyzed. The k-means clustering method and the Lloyd algorithm were used on the data. We used the elbow method to choose the number of clusters, looking at the percentage of variance explained as a function of the number of clusters. RESULTS: The results of the k-means cluster analyses of raw METs revealed three different clusters. The unengaged group (n=102) had the highest depressive symptoms score compared with the afternoon engaged (n=65) and morning engaged (n=48) groups (overall P<.001). Based on a normalized version of the METs ≥3 data, the moderate-to-vigorous physical activity (MVPA) evening peak group (n=108) had a higher body mass index (P=.03), waist circumference (P=.02), and hip circumference (P=.03) than the MVPA noon peak group (n=61). CONCLUSIONS: Categorizing physically inactive individuals into more specific activity patterns could aid in creating timing, frequency, duration, and intensity of physical activity interventions for women. Further research is needed to confirm these cluster groups using a large national dataset. TRIAL REGISTRATION: ClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/6vVyLzwft) JMIR Publications 2018-02-01 /pmc/articles/PMC5814604/ /pubmed/29391341 http://dx.doi.org/10.2196/publichealth.9138 Text en ©Yoshimi Fukuoka, Mo Zhou, Eric Vittinghoff, William Haskell, Ken Goldberg, Anil Aswani. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 01.02.2018. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Fukuoka, Yoshimi Zhou, Mo Vittinghoff, Eric Haskell, William Goldberg, Ken Aswani, Anil Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title | Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title_full | Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title_fullStr | Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title_full_unstemmed | Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title_short | Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis |
title_sort | objectively measured baseline physical activity patterns in women in the mped trial: cluster analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5814604/ https://www.ncbi.nlm.nih.gov/pubmed/29391341 http://dx.doi.org/10.2196/publichealth.9138 |
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