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  • The Dynamic Inter-Relationship between Obesity and School Performance: New Empirical Evidence from Australia

    Author(s)
    Nghiem, Son
    Viet-Ngu, Hoang
    Xuan-Binh, Vu
    Wilson, Clevo
    Griffith University Author(s)
    Vu, Benjamin
    Year published
    2018
    Metadata
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    Abstract
    This paper proposes a new empirical model for examining the relationship between obesity and school performance using the simultaneous equation modelling approach. The lagged effects of both learning and health outcomes were included to capture both the dynamic and inter-relational aspects of the relationship between obesity and school performance. The empirical application of this study used comprehensive data from the first five waves of the Longitudinal Study of Australian Children (LSAC), which commenced in 2004 (wave 1) and was repeated every two years until 2018. The study sample included 10,000 children, equally divided ...
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    This paper proposes a new empirical model for examining the relationship between obesity and school performance using the simultaneous equation modelling approach. The lagged effects of both learning and health outcomes were included to capture both the dynamic and inter-relational aspects of the relationship between obesity and school performance. The empirical application of this study used comprehensive data from the first five waves of the Longitudinal Study of Australian Children (LSAC), which commenced in 2004 (wave 1) and was repeated every two years until 2018. The study sample included 10,000 children, equally divided between two cohorts (infants and children) across Australia. The empirical results show that past learning and obesity status are strongly associated with most indicators of school outcomes, including reading, writing, spelling, grammar and numeracy national tests, and scores from the internationally standardized Peabody Picture Vocabulary Test and the Matrix Reasoning Test. The main findings of this study are robust due to the choice of obesity indicator and estimation methods.
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    Journal Title
    Journal of Biosocial Science
    DOI
    https://doi.org/10.1017/S0021932017000608
    Note
    This publication has been entered into Griffith Research Online as an Advanced Online Version.
    Subject
    Demography
    Demography not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/356063
    Collection
    • Journal articles

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