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Visualising Combined Time Use Patterns of Children’s Activities and Their Association with Weight Status and Neighbourhood Context

Author

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  • 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)

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.

Suggested Citation

  • Jinfeng Zhao & Lisa Mackay & Kevin Chang & Suzanne Mavoa & Tom Stewart & Erika Ikeda & Niamh Donnellan & Melody Smith, 2019. "Visualising Combined Time Use Patterns of Children’s Activities and Their Association with Weight Status and Neighbourhood Context," IJERPH, MDPI, vol. 16(5), pages 1-16, March.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:5:p:897-:d:213300
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    References listed on IDEAS

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    1. Jean-Philippe Chaput & Valerie Carson & Casey E. Gray & Mark S. Tremblay, 2014. "Importance of All Movement Behaviors in a 24 Hour Period for Overall Health," IJERPH, MDPI, vol. 11(12), pages 1-7, December.
    2. Daniel John Exeter & Jinfeng Zhao & Sue Crengle & Arier Lee & Michael Browne, 2017. "The New Zealand Indices of Multiple Deprivation (IMD): A new suite of indicators for social and health research in Aotearoa, New Zealand," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-19, August.
    3. Ikeda, Erika & Mavoa, Suzanne & Hinckson, Erica & Witten, Karen & Donnellan, Niamh & Smith, Melody, 2018. "Differences in child-drawn and GIS-modelled routes to school: Impact on space and exposure to the built environment in Auckland, New Zealand," Journal of Transport Geography, Elsevier, vol. 71(C), pages 103-115.
    4. Andrew Harvey, 1993. "Time-use studies: A tool for macro and micro economic and social analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 30(2), pages 1-1, November.
    5. Weimann, Amy & Dai, Dajun & Oni, Tolu, 2016. "A cross-sectional and spatial analysis of the prevalence of multimorbidity and its association with socioeconomic disadvantage in South Africa: A comparison between 2008 and 2012," Social Science & Medicine, Elsevier, vol. 163(C), pages 144-156.
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    1. Rahel Mathews & Danielle Nadorff, 2022. "Too Many Treats or Not Enough to Eat? The Impact of Caregiving Grandparents on Child Food Security and Nutrition," IJERPH, MDPI, vol. 19(10), pages 1-10, May.

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