Visualising combined time use patterns of children's activities and their association with weight status and neighbourhood context
Journal article
Zhao, Jinfeng, Mackay, Lisa, Chang, Kevin C.T., Mavoa, Suzanne, Stewart, Tom, Ikeda, Erika, Donnellan, Niamh and Smith, Melody. (2019). Visualising combined time use patterns of children's activities and their association with weight status and neighbourhood context. International Journal of Environmental Research and Public Health. 16(5), p. Article 897. https://doi.org/10.3390/ijerph16050897
Authors | Zhao, Jinfeng, Mackay, Lisa, Chang, Kevin C.T., Mavoa, Suzanne, Stewart, Tom, Ikeda, Erika, Donnellan, Niamh and Smith, Melody |
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Abstract | Compositional data techniques are an emerging method in physical activity research. These techniques account for the complexities of, and interrelationships between, behaviours that occur throughout a day (e.g., physical activity, sitting, and sleep). The field of health geography research is also developing rapidly. Novel spatial techniques and data visualisation approaches are increasingly being recognised for their utility in understanding health from a socio-ecological perspective. Linking compositional data approaches with geospatial datasets can yield insights into the role of environments in promoting or hindering the health implications of the daily time-use composition of behaviours. The 7-day behaviour data used in this study were derived from accelerometer data for 882 Auckland school children and linked to weight status and neighbourhood deprivation. We developed novel geospatial visualisation techniques to explore activity composition over a day and generated new insights into links between environments and child health behaviours and outcomes. Visualisation strategies that integrate compositional activities, time of day, weight status, and neighbourhood deprivation information were devised. They include a ringmap overview, small-multiple ringmaps, and individual and aggregated time–activity diagrams. Simultaneous visualisation of geospatial and compositional behaviour data can be useful for triangulating data from diverse disciplines, making sense of complex issues, and for effective knowledge translation. |
Keywords | time use; accelerometer data; physical activity; sedentary behaviour; sleep; neighbourhood context; weight status; school children; compositional analysis; visualisation |
Year | 2019 |
Journal | International Journal of Environmental Research and Public Health |
Journal citation | 16 (5), p. Article 897 |
Publisher | Multidisciplinary Digital Publishing Institute (MDPI AG) |
ISSN | 1661-7827 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/ijerph16050897 |
PubMed ID | 30871114 |
Scopus EID | 2-s2.0-85062957308 |
PubMed Central ID | PMC6427195 |
Open access | Published as ‘gold’ (paid) open access |
Research or scholarly | Research |
Page range | 1-16 |
Funder | National Health and Medical Research Council (NHMRC) |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 12 Mar 2019 |
Publication process dates | |
Accepted | 06 Mar 2019 |
Deposited | 13 Dec 2021 |
Grant ID | NHMRC/1121035 |
https://acuresearchbank.acu.edu.au/item/8x307/visualising-combined-time-use-patterns-of-children-s-activities-and-their-association-with-weight-status-and-neighbourhood-context
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Publisher's version
OA_Zhao_2019_Visualising_combined_time_use_patterns_of.pdf | |
License: CC BY 4.0 | |
File access level: Open |
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