A graduated food addiction classification approach significantly differentiates obesity among people with type 2 diabetes

Karren Lee Raymond, Lee Kannis-Dymand, Geoff P. Lovell

Research output: Contribution to journalJournal Article

1 Citation (Scopus)

Abstract

This study examined a graduated severity level approach to food addiction classification against associations with World Health Organization obesity classifications (body mass index, kg/m 2 ) among 408 people with type 2 diabetes. A survey including the Yale Food Addiction Scale and several demographic questions demonstrated four distinct Yale Food Addiction Scale symptom severity groups (in line with Diagnostic and Statistical Manual of Mental Disorders (5th ed.) severity indicators): non-food addiction, mild food addiction, moderate food addiction and severe food addiction. Analysis of variance with post hoc tests demonstrated each severity classification group was significantly different in body mass index, with each grouping being associated with increased World Health Organization obesity classifications. These findings have implications for diagnosing food addiction and implementing treatment and prevention methodologies of obesity among people with type 2 diabetes.
Original languageEnglish
Pages (from-to)1781-1789
Number of pages9
JournalJournal of Health Psychology
Volume23
Issue number14
Early online date9 Oct 2016
DOIs
Publication statusPublished - 1 Dec 2018
Externally publishedYes

Fingerprint

Type 2 Diabetes Mellitus
Obesity
Food
Body Mass Index
Diagnostic and Statistical Manual of Mental Disorders
Analysis of Variance
Demography

Keywords

  • food addiction
  • obesity
  • processed food use disorder
  • severity levels
  • type 2 diabetes

Cite this

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A graduated food addiction classification approach significantly differentiates obesity among people with type 2 diabetes. / Raymond, Karren Lee; Kannis-Dymand, Lee; Lovell, Geoff P.

In: Journal of Health Psychology, Vol. 23, No. 14, 01.12.2018, p. 1781-1789.

Research output: Contribution to journalJournal Article

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