From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis

Mai J. Chinapaw, Xinhui Wang, Lars Bo Andersen, Teatske M. Altenburg

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Purpose To date, epidemiological studies have focused on the potential health effects of total volume of physical activity (PA) or sedentary behavior (SB). However, two persons may have the same volume of PA or SB but accumulated in a completely different sequence. The pattern of accumulating PA and SB might be more important for health effects than the total volume. Therefore, the aim was to develop a sophisticated algorithm translating accelerometer data into detailed sequence maps considering how PA and SB are accumulated throughout the day. Methods We developed a novel algorithm to convert accelerometer counts into a sequence map based on behavior states defined by a combination of intensity (SB, light, moderate, and vigorous intensity) and duration (sporadic accumulation or in bouts of different duration). In addition, hierarchical cluster analysis was applied to identify clusters of children with similar behavioral sequence maps. Results Clustering resulted in seven clusters of children with similar PA and SB sequence maps: an average cluster (33% of children); a cluster with relatively more SB, light, and moderate PA in bouts (SB and PA bouters, 31%); a cluster characterized by more sporadic SB and light PA (light activity breakers, 26%); and four smaller clusters with 7% of the children or less. Conclusion This novel algorithm is a next step in more sophisticated analyses of accelerometer data considering how PA and SB are accumulated throughout the day. The next step is identifying whether specific patterns of accumulating PA and SB are associated with improved health outcomes.
LanguageEnglish
Pages814-820
JournalMedicine and Science in Sports and Exercise
Volume51
Issue number4
DOIs
Publication statusPublished - 2019

Cite this

@article{0d4ce24684ca4c7e9b5a4c5b33f3ec42,
title = "From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis",
abstract = "Purpose To date, epidemiological studies have focused on the potential health effects of total volume of physical activity (PA) or sedentary behavior (SB). However, two persons may have the same volume of PA or SB but accumulated in a completely different sequence. The pattern of accumulating PA and SB might be more important for health effects than the total volume. Therefore, the aim was to develop a sophisticated algorithm translating accelerometer data into detailed sequence maps considering how PA and SB are accumulated throughout the day. Methods We developed a novel algorithm to convert accelerometer counts into a sequence map based on behavior states defined by a combination of intensity (SB, light, moderate, and vigorous intensity) and duration (sporadic accumulation or in bouts of different duration). In addition, hierarchical cluster analysis was applied to identify clusters of children with similar behavioral sequence maps. Results Clustering resulted in seven clusters of children with similar PA and SB sequence maps: an average cluster (33{\%} of children); a cluster with relatively more SB, light, and moderate PA in bouts (SB and PA bouters, 31{\%}); a cluster characterized by more sporadic SB and light PA (light activity breakers, 26{\%}); and four smaller clusters with 7{\%} of the children or less. Conclusion This novel algorithm is a next step in more sophisticated analyses of accelerometer data considering how PA and SB are accumulated throughout the day. The next step is identifying whether specific patterns of accumulating PA and SB are associated with improved health outcomes.",
author = "Chinapaw, {Mai J.} and Xinhui Wang and Andersen, {Lars Bo} and Altenburg, {Teatske M.}",
year = "2019",
doi = "10.1249/MSS.0000000000001849",
language = "English",
volume = "51",
pages = "814--820",
journal = "Medicine and Science in Sports and Exercise",
issn = "0195-9131",
publisher = "Lippincott Williams and Wilkins",
number = "4",

}

From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis. / Chinapaw, Mai J.; Wang, Xinhui; Andersen, Lars Bo; Altenburg, Teatske M.

In: Medicine and Science in Sports and Exercise, Vol. 51, No. 4, 2019, p. 814-820.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis

AU - Chinapaw, Mai J.

AU - Wang, Xinhui

AU - Andersen, Lars Bo

AU - Altenburg, Teatske M.

PY - 2019

Y1 - 2019

N2 - Purpose To date, epidemiological studies have focused on the potential health effects of total volume of physical activity (PA) or sedentary behavior (SB). However, two persons may have the same volume of PA or SB but accumulated in a completely different sequence. The pattern of accumulating PA and SB might be more important for health effects than the total volume. Therefore, the aim was to develop a sophisticated algorithm translating accelerometer data into detailed sequence maps considering how PA and SB are accumulated throughout the day. Methods We developed a novel algorithm to convert accelerometer counts into a sequence map based on behavior states defined by a combination of intensity (SB, light, moderate, and vigorous intensity) and duration (sporadic accumulation or in bouts of different duration). In addition, hierarchical cluster analysis was applied to identify clusters of children with similar behavioral sequence maps. Results Clustering resulted in seven clusters of children with similar PA and SB sequence maps: an average cluster (33% of children); a cluster with relatively more SB, light, and moderate PA in bouts (SB and PA bouters, 31%); a cluster characterized by more sporadic SB and light PA (light activity breakers, 26%); and four smaller clusters with 7% of the children or less. Conclusion This novel algorithm is a next step in more sophisticated analyses of accelerometer data considering how PA and SB are accumulated throughout the day. The next step is identifying whether specific patterns of accumulating PA and SB are associated with improved health outcomes.

AB - Purpose To date, epidemiological studies have focused on the potential health effects of total volume of physical activity (PA) or sedentary behavior (SB). However, two persons may have the same volume of PA or SB but accumulated in a completely different sequence. The pattern of accumulating PA and SB might be more important for health effects than the total volume. Therefore, the aim was to develop a sophisticated algorithm translating accelerometer data into detailed sequence maps considering how PA and SB are accumulated throughout the day. Methods We developed a novel algorithm to convert accelerometer counts into a sequence map based on behavior states defined by a combination of intensity (SB, light, moderate, and vigorous intensity) and duration (sporadic accumulation or in bouts of different duration). In addition, hierarchical cluster analysis was applied to identify clusters of children with similar behavioral sequence maps. Results Clustering resulted in seven clusters of children with similar PA and SB sequence maps: an average cluster (33% of children); a cluster with relatively more SB, light, and moderate PA in bouts (SB and PA bouters, 31%); a cluster characterized by more sporadic SB and light PA (light activity breakers, 26%); and four smaller clusters with 7% of the children or less. Conclusion This novel algorithm is a next step in more sophisticated analyses of accelerometer data considering how PA and SB are accumulated throughout the day. The next step is identifying whether specific patterns of accumulating PA and SB are associated with improved health outcomes.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85062959903&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30882752

U2 - 10.1249/MSS.0000000000001849

DO - 10.1249/MSS.0000000000001849

M3 - Article

VL - 51

SP - 814

EP - 820

JO - Medicine and Science in Sports and Exercise

T2 - Medicine and Science in Sports and Exercise

JF - Medicine and Science in Sports and Exercise

SN - 0195-9131

IS - 4

ER -