Unlike other questionnaires, the AEBQ includes eight subscales within two categories of eating behaviors ( Food Approach: Food Responsiveness, Hunger, Emotional Overeating, and Enjoyment of Food Food Avoidance: Satiety Responsiveness, Food Fussiness, Emotional Undereating, and Slowness in Eating). The AEBQ is a 35-item questionnaire that assesses appetitive traits ( Hunot et al., 2016). Appetitive traits are conventionally assessed using questionnaires, such as Healthy Eating Index, Three-Factor Eating Questionnaire, and Self-Regulation of Eating Behavior Questionnaire ( Karlsson et al., 2000 Guenther et al., 2008 Kliemann et al., 2016).
While certain AEBQ subscales are associated with body weight and other measures of adiposity, studies in children have demonstrated that the traits captured by the tool are also associated with a range of other important factors such as food preferences ( Fildes et al., 2015), dietary patterns ( Carnell et al., 2016), sleep ( Miller et al., 2019), and cardiometabolic health ( Warkentin et al., 2020). For instance, subscales from the Adult Eating Behaviour Questionnaire (AEBQ) have been shown to be associated with BMI in the expected direction, such as higher Food Approach subscales and lower Food Avoidance subscales were positively associated with individuals living with higher BMIs ( Hunot et al., 2016).Įating behaviors are often described as appetitive traits, which are genetic predispositions towards food that interact with environmental factors to influence eating behaviors ( Carnell et al., 2013). Results from a previous review have shown that certain eating behaviors are positively associated with increased body mass index (BMI) and obesity ( French et al., 2012).
The prevalence and impact of weight and obesity indicate the importance of examining effective prevention and treatment strategies as they relate to health behaviors such as eating behaviors. Overweight and obesity conditions are risk factors for a variety of non-communicable diseases such as diabetes mellitus, cardiovascular diseases, hypertension, and certain types of cancer ( Nyberg et al., 2018). In Canada, it is estimated that the adult Canadian population has body mass indices (BMI) that classify 36% of them as living with an overweight condition and 27% of them living with obesity ( Government of Canada, 2018). Overweight and obesity remain a global public health concern ( World Health Organization, 2000). These results support the use of a seven-factor AEBQ for adults self-reporting eating behaviors, construct validity of the AEBQ against TFEB-R18, and provide further evidence for the association of these traits with BMI. Similarly, BMI correlated positively with Food Approach subscales (except Hunger) and negatively with Food Avoidance subscales (except Food Fussiness). All AEBQ Food Approach subscales positively correlated with that of the TFEQ-R18 Emotional Eating and Uncontrolled Eating subscales. Pearson’s correlations were used to inform the convergent and discriminant validation of AEBQ against the TFEQ-R18 and to examine the relationship between AEBQ and BMI. Cronbach’s alpha was used to assess the internal reliability of each subscale and resulted with α > 0.70 for all subscales except for Hunger (α = 0.68). Confirmatory factor analysis (CFA) revealed that a seven-factor AEBQ model, with the Hunger subscale removed, had better fit statistics than the original eight-factor structure. The current study aimed to test the factor structure of the Adult Eating Behavior Questionnaire (AEBQ), its construct validity against the Three-Factor Eating Questionnaire (TFEQ-R18) and its associations with body mass index (BMI) in Canadian adults ( n = 534, 76% female).
7Department of Behavioural Science and Health, University College London, London, United Kingdom.6Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.5Instituto de Nutrición Humana, Departamento de Reproducción Humana, Crecimiento y Desarrollo Infantil, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Mexico.4School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.3Department of Mathematics and Statistics, Concordia University, Montreal, QC, Canada.2PERFORM Centre, Concordia University, Montreal, QC, Canada.1Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada.Cohen 1,2*, Lisa Kakinami 2,3, Hugues Plourde 4, Claudia Hunot-Alexander 5† and Rebecca J.