Visualising Combined Time Use Patterns of Children’s Activities and Their Association with Weight Status and Neighbourhood Context
Jinfeng Zhao,
Lisa Mackay,
Kevin Chang,
Suzanne Mavoa,
Tom Stewart,
Erika Ikeda,
Niamh Donnellan and
Melody Smith
Additional contact information
Jinfeng Zhao: School of Nursing, The University of Auckland, Auckland 1023, New Zealand
Lisa Mackay: School of Sport and Recreation, Auckland University of Technology, Auckland 0627, New Zealand
Kevin Chang: Department of Statistics, The University of Auckland, Auckland 1010, New Zealand
Suzanne Mavoa: Melbourne School of Population and Global Health, The University of Melbourne, Melbourne 3010, Australia
Tom Stewart: School of Sport and Recreation, Auckland University of Technology, Auckland 0627, New Zealand
Erika Ikeda: School of Sport and Recreation, Auckland University of Technology, Auckland 0627, New Zealand
Niamh Donnellan: School of Nursing, The University of Auckland, Auckland 1023, New Zealand
Melody Smith: School of Nursing, The University of Auckland, Auckland 1023, New Zealand
IJERPH, 2019, vol. 16, issue 5, 1-16
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 (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:16:y:2019:i:5:p:897-:d:213300
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