Use of Latent Profile Analysis to Identify Eating Disorder Phenotypes in an Adult Australian Twin Cohort

School of Psychology, Flinders University, PO Box 2100, Adelaide, SA 5001, Australia.
Archives of General Psychiatry (Impact Factor: 14.48). 01/2007; 63(12):1377-84. DOI: 10.1001/archpsyc.63.12.1377
Source: PubMed


The relationships among the different eating disorders that exist in the community are poorly understood, especially for residual disorders in which bingeing or purging occurs in the absence of other behaviors.
To examine a community sample for the number of mutually exclusive weight and eating profiles.
Data regarding lifetime eating disorder symptoms and weight range were submitted to a latent profile analysis. Profiles were compared regarding personality, current eating and weight, retrospectively reported life events, and lifetime depressive psychopathology.
Longitudinal study among female twins from the Australian Twin Registry in whom eating was assessed by a telephone interview.
A community sample of 1002 twins (individuals) who had participated in earlier waves of data collection.
Number and clinical character of latent profiles.
The best fit was a 5-profile solution with women who were (1) of normal weight with few lifetime eating disorders (4.3%), (2) overweight (10.6% had a lifetime eating disorder), (3) underweight and generally had no eating disorders except for 5.3% who had restricting anorexia nervosa, (4) of low to normal weight (89.0% had a lifetime eating disorder), and (5) obese (37.0% had a lifetime eating disorder). Each profile contained more than 1 type of lifetime eating disorder except for the third profile. Women in the first and third profiles had the best functioning, with women in the fourth and fifth profiles having similarly poorer functioning. The women in the fourth group had a symptom profile distinctive from the other 4 groups in terms of severity; they were also more likely to have had lifetime major depression and suicidality.
Lifetime weight ranges and the severity of eating disorder symptoms affected clustering more than the type of eating disorder symptom.

12 Reads
  • Source
    • "As binge-eating and purging occur in many people with AN, the syndrome is further subdivided into " AN-restricting (AN-R) " and " AN-binge-eating/purging " (AN- BP) types, depending upon the presence or absence of binge-eating and purging behaviors. Individuals who binge and purge (whether they have AN-BP or BN) are noted to be more prone to behavioral disinhibition and affective instability than are those who solely restrict food intake (Rosval et al., 2006; Steiger et al., 2013; Wu et al., 2013), and various findings validate the concept that " restricting-only " and " binge-eating/purging " individuals, regardless of weight status, fall into separate classes (Keel et al., 2004; Williamson et al., 2005; Wade et al., 2006; Wildes and Marcus, 2013). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Eating disorder (ED) variants characterized by "binge-eating/purging" symptoms differ from "restricting-only" variants along diverse clinical dimensions, but few studies have compared people with these different eating-disorder phenotypes on measures of neurocognitive function and brain activation. We tested the performances of 19 women with "restricting-only" eating syndromes and 27 with "binge-eating/purging" variants on a modified n-back task, and used functional magnetic resonance imaging (fMRI) to examine task-induced brain activations in frontal regions of interest. When compared with "binge-eating/purging" participants, "restricting-only" participants showed superior performance. Furthermore, in an intermediate-demand condition, "binge-eating/purging" participants showed significantly less event-related activation than did "restricting-only" participants in a right posterior prefrontal region spanning Brodmann areas 6-8-a region that has been linked to planning of motor responses, working memory for sequential information, and management of uncertainty. Our findings suggest that working memory is poorer in eating-disordered individuals with binge-eating/purging behaviors than in those who solely restrict food intake, and that observed performance differences coincide with interpretable group-based activation differences in a frontal region thought to subserve planning and decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Psychiatry Research: Neuroimaging 02/2015; 232(1). DOI:10.1016/j.pscychresns.2015.01.022 · 2.42 Impact Factor
  • Source
    • "LPA is a so-called “person centered” approach, which means that observations are clustered on subject basis, unlike factor analysis, in which observations are clustered on item basis. LPA has been frequently used, also in the field of eating behavior, e.g. to identify eating disorder phenotypes in a twin cohort study in Australia [38]. We determined the number of latent profiles based on the minimization of Bayesian information criteria (BIC) [39] and Akaike information criteria (AIC) indices and a non-significant Lo-Mendell-Rubin Likelihood Ratio Test (LMR-LRT) [40] to test model fit. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Definitions and assessment methods of fussy/picky eating are heterogeneous and remain unclear.We aimed to identify an eating behavior profile reflecting fussy/picky eating in children and to describe characteristics of fussy eaters. Eating behavior was assessed with the Child Eating Behavior Questionnaire (CEBQ) in 4914 4-year olds in a population-based birth cohort study. Latent Profile Analysis (LPA) was used to identify eating behavior profiles based on CEBQ subscales. We found a "fussy" eating behavior profile (5.6% of children) characterized by high food fussiness, slowness in eating, and satiety responsiveness in combination with low enjoyment of food and food responsiveness. Fussy eaters were more often from families with low household income than non-fussy eaters (42% vs. 31.8% respectively; Chi2(1) = 9.97, p < .01). When they were 14 months old, fussy eaters had a lower intake of vegetables (t [3008] = 2.42, p < .05) and fish (t [169.77] = 2.40, p < .05) but higher intake of savory snacks (t [153.69] = -2.03, p < .05) and sweets (t [3008] = -2.30, p < .05) compared to non-fussy eaters. Also, fussy eaters were more likely to be underweight at 4 years of age (19.3%) than non-fussy eaters (12.3%; Chi2(1) = 7.71, p < .01). A distinct fussy eating behavior profile was identified by LPA, which was related to family and child characteristics, food intake, and BMI. This behavior profile might be used in future research and the development of interventions.
    International Journal of Behavioral Nutrition and Physical Activity 02/2014; 11(1):14. DOI:10.1186/1479-5868-11-14 · 4.11 Impact Factor
  • Source
    • "x Cain et al. (2010) [6] x Crosby et al. (2011) [7] x Crow et al. (2012) [8] x Dechartres et al. (2011) [9] x Duncan et al. (2007) [10] x Duncan et al. (2005) [11] x Eddy et al. (2009) [12] x Eddy et al. (2010) [13] x Jacobs et al. (2009) [14] x Keel et al. (2004) [15] x Keel et al. (2011) [16] x Krug et al. (2011) [17] x Mitchell et al. (2007) [18] x Myers et al. (2006) [19] x Olmsted et al. (2011) [20] x O'Toole et al. (2011) [21] x Peterson et al. (2011) [22] x Pinheiro et al. (2008) [23] x Richardson et al. (2008) [24] x Steiger et al. (2010) [25] x Steiger et al. (2009) [26] x Striegel-Moore et al. (2008) [27] x Striegel-Moore et al. (2005) [28] x Sullivan et al. (1998) [29] x Thomas et al. (2011) [30] x Wade et al. (2006) [31] x Wagner et al. (2006) [32] x Wildes et al. (2011) [33] x Wonderlich et al. (2007) [34] x Wonderlich et al. (2005) [35] "
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective: The purpose of this investigation was to compare the latent structures of the interview (EDE) and questionnaire (EDE-Q) versions of the Eating Disorder Examination. Methods: Participants were 280 children, adolescents, and young adults seeking eating disorder treatment. Two separate latent structure analyses (LSAs) were conducted; one used variables from the EDE as indicators and the other used the corresponding variables from the EDE-Q as indicators. Results: The EDE and EDE-Q models both yielded four-class solutions. Three of the four classes from the EDE-Q model demonstrated moderate to high concordance with their paired class from the EDE model. Using the EDE-Q to detect the EDE, the sensitivity and specificity of measuring certain classes varied from poor (18.6%) to excellent (93.7%). The overall concordance was moderate (κ=.49). Discussion: These data suggest that LSAs using the EDE and EDE-Q may be directly compared; however, differences between results may represent inconsistencies in response patterns rather than true differences in psychopathology.
    Comprehensive psychiatry 01/2013; 54(5). DOI:10.1016/j.comppsych.2012.12.006 · 2.25 Impact Factor
Show more

Similar Publications


12 Reads
Available from