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73 results

Page 1 of 4

  • Body size and weight, and the nutrition and activity behaviours of sexual and gender minority youth: findings and implications from New Zealand
  • Mathijs FG Lucassen, Aravinda Meera Guntupalli, Terryann Clark, John Fenaughty, Simon Denny, Theresa Fleming, Melody Smith, Jennifer Utter
  • Journal: Public Health Nutrition , First View
  • Published online by Cambridge University Press: 04 June 2019, pp. 1-11
  • View abstract
    Objective:

    To describe the body size and weight, and the nutrition and activity behaviours of sexual and gender minority (SGM) students and compare them with those of exclusively opposite-sex-attracted cisgender students. Male and female SGM students were also compared.

    Design:

    Data were from a nationally representative health survey.

    Setting:

    Secondary schools in New Zealand, 2012.

    Participants:

    A total of 7769 students, 9 % were SGM individuals.

    Results:

    Overall, weight-control behaviours, poor nutrition and inactivity were common and, in many cases, more so for SGM students. Specifically, male SGM students (adjusted OR; 95 % CI) were significantly more likely to have tried to lose weight (1·95; 1·47, 2·59), engage in unhealthy weight control (2·17; 1·48, 3·19), consume fast food/takeaways (2·89; 2·01, 4·15) and be physically inactive (2·54; 1·65, 3·92), and were less likely to participate in a school sports team (0·57; 0·44, 0·75), compared with other males. Female SGM students (adjusted OR; 95 % CI) were significantly more likely to engage in unhealthy weight control (1·58; 1·20, 2·08), be overweight or obese (1·24; 1·01, 1·53) and consume fast food/takeaways (2·19; 1·59, 3·03), and were less likely to participate in a school sports team (0·62; 0·50, 0·76), compared with other females. Generally, female SGM students were more negatively affected than comparable males, except they were less likely to consume fast food/takeaways frequently (adjusted OR; 95 % CI: 0·62; 0·40, 0·96).

    Conclusions:

    SGM students reported increased weight-control behaviours, poor nutrition and inactivity. Professionals, including public health nutritionists, must recognize and help to address the challenges facing sexual and gender minorities.

Predictive Statistics
  • Predictive Statistics
  • Analysis and Inference beyond Models
  • Bertrand S. Clarke, Jennifer L. Clarke
  • Published online: 27 April 2018
  • Print publication: 12 April 2018
  • View description
    All scientific disciplines prize predictive success. Conventional statistical analyses, however, treat prediction as secondary, instead focusing on modeling and hence estimation, testing, and detailed physical interpretation, tackling these tasks before the predictive adequacy of a model is established. This book outlines a fully predictive approach to statistical problems based on studying predictors; the approach does not require predictors correspond to a model although this important special case is included in the general approach. Throughout, the point is to examine predictive performance before considering conventional inference. These ideas are traced through five traditional subfields of statistics, helping readers to refocus and adopt a directly predictive outlook. The book also considers prediction via contemporary 'black box' techniques and emerging data types and methodologies where conventional modeling is so difficult that good prediction is the main criterion available for evaluating the performance of a statistical method. Well-documented open-source R code in a Github repository allows readers to replicate examples and apply techniques to other investigations.

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