Dataset Information

Assessing the factor structure and measurement invariance of the eating attitude test (EAT-26) across language and BMI in young Arab women.

ABSTRACT:

Background

The objective of the study was to determine the factorial structure and test the measurement invariance of the EAT-26 in a large probability sample of young female university students in Qatar (n?=?2692), a Muslim country in the Middle East.

Methods

The maximum number of factors was derived based on results from initial exploratory factor analysis (EFA) in the first-half of the randomly split sample (Sample 1). A subsequent EFA and Exploratory Structural Equation Models (ESEM) were conducted to identify the number of valid factors. A five-factor model with 19 items was identified as the optimal factor structure. This structure was further replicated using ESEM in the second-half of the sample (Sample 2). Multi-group Confirmatory Factor Analyses (CFAs) were conducted at this stage and their fit was evaluated with and without further sub-grouping by language (Arabic and English) and BMI (underweight, normal weight, and overweight/obese). Finally, measurement invariance tests were conducted in the entire sample assessing equivalence across language and BMI within the final five-factor model.

Results

The five-factor structure of the new EAT-19 [fear of getting fat (FGF), eating-related control (ERC), food preoccupation (FP), vomiting-purging behavior (VPB), and social pressure to gain weight (SP)] provided the best fit: CFI?=?0.976, TLI?=?0.952, RMSEA?=?0.045 (90%CI 0.039-0.051), SRMR?=?0.018, CD =1.000. CFAs supported metric invariance for language and for BMI. Language and BMI-based population heterogeneity comparisons provided modest and small-to-moderate evidence for differential factor means, respectively.

Conclusion

Although the five-factor model of the EAT-19 demonstrated good item characteristics and reliability in this young female population, the lack of scalar invariance across language and BMI-categories pose measurement challenges for use of this scale for screening purposes. Future studies should develop culture- and BMI-specific cut-offs when using the EAT as a screening instrument for disordered eating in non-clinical populations.

SUBMITTER: Khaled SM

PROVIDER: S-EPMC6001056 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Assessing the factor structure and measurement invariance of the eating attitude test (EAT-26) across language and BMI in young Arab women.

Khaled Salma M SM Kimmel Linda L Le Trung Kien K

Journal of eating disorders 20180614

<h4>Background</h4>The objective of the study was to determine the factorial structure and test the measurement invariance of the EAT-26 in a large probability sample of young female university students in Qatar (<i>n</i> = 2692), a Muslim country in the Middle East.<h4>Methods</h4>The maximum number of factors was derived based on results from initial exploratory factor analysis (EFA) in the first-half of the randomly split sample (Sample 1). A subsequent EFA and Exploratory Structural Equation ...[more]

PMID: 29946466

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Project description:BACKGROUND:Why do we eat? Our motives for eating are diverse, ranging from hunger and liking to social norms and affect regulation. Although eating motives can vary from eating event to eating event, which implies substantial moment-to-moment differences, current ways of measuring eating motives rely on single timepoint questionnaires that assess eating motives as situation-stable dispositions (traits). However, mobile technologies including smartphones allow eating events and motives to be captured in real time and real life, thus capturing experienced eating motives in-the-moment (states). OBJECTIVE:This study aimed to examine differences between why people think they eat (trait motives) and why they eat in the moment of consumption (state motives) by comparing a dispositional (trait) and an in-the-moment (state) assessment of eating motives. METHODS:A total of 15 basic eating motives included in The Eating Motivation Survey (ie, liking, habit, need and hunger, health, convenience, pleasure, traditional eating, natural concerns, sociability, price, visual appeal, weight control, affect regulation, social norms, and social image) were assessed in 35 participants using 2 methodological approaches: (1) a single timepoint dispositional assessment and (2) a smartphone-based ecological momentary assessment (EMA) across 8 days (N=888 meals) capturing eating motives in the moment of eating. Similarities between dispositional and in-the-moment eating motive profiles were assessed according to 4 different indices of profile similarity, that is, overall fit, shape, scatter, and elevation. Moreover, a visualized person × motive data matrix was created to visualize and analyze between- and within-person differences in trait and state eating motives. RESULTS:Similarity analyses yielded a good overall fit between the trait and state eating motive profiles across participants, indicated by a double-entry intraclass correlation of 0.52 (P<.001). However, although trait and state motives revealed a comparable rank order (r=0.65; P<.001), trait motives overestimated 12 of 15 state motives (P<.001; d=1.97). Specifically, the participants assumed that 6 motives (need and hunger, price, habit, sociability, traditional eating, and natural concerns) are more essential for eating than they actually were in the moment (d>0.8). Furthermore, the visualized person × motive data matrix revealed substantial interindividual differences in intraindividual motive profiles. CONCLUSIONS:For a comprehensive understanding of why we eat what we eat, dispositional assessments need to be extended by in-the-moment assessments of eating motives. Smartphone-based EMAs reveal considerable intra- and interindividual differences in eating motives, which are not captured by single timepoint dispositional assessments. Targeting these differences between why people think they eat what they eat and why they actually eat in the moment may hold great promise for tailored mobile health interventions facilitating behavior changes.

Dataset Information

Assessing the factor structure and measurement invariance of the eating attitude test (EAT-26) across language and BMI in young Arab women.

Background

Methods

Results

Conclusion

Publications

Assessing the factor structure and measurement invariance of the eating attitude test (EAT-26) across language and BMI in young Arab women.

Similar Datasets

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