Eating Behaviour among Multi-Ethnic Adolescents in a Middle-Income Country as Measured by the Self-Reported Children’s Eating Behaviour Questionnaire

Abstract

BackgroundEscalating weight gain among the Malaysian paediatric population necessitates identifying modifiable behaviours in the obesity pathway.ObjectivesThis study describes the adaptation and validation of the Children’s Eating Behaviour Questionnaire (CEBQ) as a self-report for adolescents, investigates gender and ethnic differences in eating behaviour and examines associations between eating behaviour and body mass index (BMI) z-scores among multi-ethnic Malaysian adolescents. MethodologyThis two-phase study involved validation of the Malay self-reported CEBQ in Phase 1 (n = 362). Principal Axis Factoring with Promax rotation, confirmatory factor analysis and reliability tests were performed. In Phase 2, adolescents completed the questionnaire (n = 646). Weight and height were measured. Gender and ethnic differences in eating behaviour were investigated. Associations between eating behaviour and BMI z-scores were examined with complex samples general linear model (GLM) analyses, adjusted for gender, ethnicity and maternal educational level. ResultsExploratory factor analysis revealed a 35-item, 9-factor structure with ‘food fussiness’ scale split into two. In confirmatory factor analysis, a 30-item, 8-factor structure yielded an improved model fit. Reliability estimates of the eight factors were acceptable. Eating behaviours did not differ between genders. Malay adolescents reported higher Food Responsiveness, Enjoyment of Food, Emotional Overeating, Slowness in Eating, Emotional Undereating and Food Fussiness 1 scores (p<0.05) compared to Chinese and Indians. A significant negative association was observed between BMI z-scores and Food Fussiness 1 (‘dislike towards food’) when adjusted for confounders.ConclusionAlthough CEBQ is a valuable psychometric instrument, adjustments were required due to age and cultural differences in our sample. With the self-report, our findings present that gender, ethnic and weight status influenced eating behaviours. Obese adolescents were found to display a lack of dislike towards food. Future longitudinal and qualitative studies are warranted to further understand behavioural phenotypes of obesity to guide prevention and intervention strategies.

Prospective associations of appetitive traits at 3 and 12 months of age with body mass index and weight gain in the first 2 years of life

“…Items of the original enjoyment of food and food fussiness subscale loaded into the same factor and were thus combined into one subscale termed enjoyment of food (Additional file 2 : Table S2). This could be due to the cultural differences in our population influencing the interpretation of the CEBQ items and is not dissimilar to studies in Malaysia [ 32 ] and Sweden [ 9 ]which revealed a nine and seven-factor structure respectively. To enable appetitive traits captured at both time points in our study to be comparable, we chose to focus our analyses on the subscales that are found in both the BEBQ and CEBQ.…”

Depression, Anxiety, and Severity of Obesity in Adolescents

“…18 The CEBQ was originally designed as a parent report of child eating behavior, yet precedent has been made for using a modified version of the CEBQ as an adolescent self-report measure. 19 As such, prefix statements were modified from “My child…” to “I…” The four items comprising the Emotional Over-Eating subscale are: “eat more when anxious,” “eat more when annoyed,” “eat more when worried,” and “eat more when nothing else to do.” Each item was rated on a 5-point Likert scale (1=never to 5=always). The mean of the four items was used as the emotional eating score.…”

Association of Picky Eating and Food Neophobia with Weight: A Systematic Review

“…Of the 41 studies reviewed, 17 found no association between picky eating or food neophobia and weight sta-tus 16,17,19,20,25,26,30,34,36,[40][41][42]45,[47][48][49]51 ; 2 found that picky eating or food neophobia had a positive association with overweight 13,39 ; 5 found a negative association with overweight or obesity 27,28,32,46,53 ; 6 found a positive association with underweight 11,12,21,31,35,50 ; and 11 found a decreased association with BMI or BMI z-score (but did not specify if underweight or decreased risk of overweight) 18,[22][23][24]29,33,37,38,43,44,52 (Table 2). These results are depicted in Figure 2.…”