Predicting Future Weight Status From Measurements Made In Early Childhood: A Novel Longitudinal Approach Applied To Millennium Cohort Study Data

Emma Mead, Alan Batterham, Gregory Atkinson, Louisa Ells

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    Abstract

    Background/objective: There are reports that childhood obesity tracks into later life. Nevertheless, some tracking statistics, e.g. correlations, do not quantify individual agreement, while others, e.g. diagnostic test statistics, can be difficult to translate into practice. We aimed to employ a novel analytic approach, based on ordinal logistic regression, to predict weight status of 11-year-old children from measurements at age 5.
    Subjects/methods: UK 1990 growth references were used to generate clinical weight status categories of 12 076 children enrolled in the Millennium Cohort Study. Using ordinal regression, we derived the predicted probability (percent chances) of an 11-year-old child becoming underweight, normal weight, overweight, obese and severely obese from their weight status category at age 5.
    Results: The chances of becoming obese (including severely obese) at age 11 were 5.7% (95% CI: 5.2% to 6.2%) for a normal weight 5-year-old and 32.3% (29.8% to 34.8%) for an overweight 5-year-old. An obese 5-year-old child had a 68.1% (63.8% to 72.5%) chance of remaining obese at 11 years. Severely obese 5-year-old children had a 50.3% (43.1% to 57.4%) c 50 hance of remaining severely obese. There were no substantial differences between sexes. Non-deprived obese 5- year-old boys had a lower probability of remaining obese than deprived obese boys: -21.8% (-40.4% to -3.2%). This association was not observed in obese 5-year-old girls, in whom the non-deprived group had a probability of remaining obese 7% higher (-15.2% to 29.2%). The sex difference in this interaction of deprivation and baseline weight status was therefore -28.8% (-59.3% to 1.6%).
    Conclusions: We have demonstrated that ordinal logistic regression can be an informative approach to predict the chances of a child changing to, or from, an unhealthy weight status. This approach is easy to interpret and could be applied to any longitudinal dataset with an ordinal outcome.
    Original languageEnglish
    Pages (from-to)-
    JournalNutrition and Diabetes
    DOIs
    Publication statusPublished - 7 Mar 2016

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