Factor structure and psychometric properties of the German version of the Reward-based Eating Drive scale

doi:10.21203/rs.3.rs-5268393/v1

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Factor structure and psychometric properties of the German version of the Reward-based Eating Drive scale

https://doi.org/10.21203/rs.3.rs-5268393/v1

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Objective: The reward-based eating drive (RED) scales are well-established self-report scales that measure reward-related eating behavior. However, German versions of the RED has not yet been created and validated. Therefore, the aim of the present study was to develop and psychometrically evaluate a German version of the RED.

Method: A German university sample (N=311 medical undergraduates) completed a survey including the RED-9 and the RED-13, as well as several related measures, to test the established factor structure using a confirmatory factor analysis. Construct validity was assessed by correlation analysis with standardized and internationally established questionnaires measuring reward-related eating.

Results: The German 9-item RED (RED-9) with the 3-factor model showed the best psychometric properties in terms of fit indices with acceptable internal consistency, good item rest correlation, and good construct validity with other reward eating scales. There was also a positive association between the German RED-9 total score and BMI.

Conclusions: In conclusion, the German RED-9 is a valid and reliable instrument for the assessment of reward-related eating behavior in non-pathological populations. Further research is needed to better understand associations among reward-related eating, obesity, and diabetes in the German population.

reward-based eating

assessment

eating behavior

questionnaire

Chronic diseases like type 2 diabetes, cardiovascular disease, and obesity are strongly linked to dietary patterns, with poor eating behaviors acting as significant predictors of their development and progression [1]. Diets high in processed sugars, unhealthy fats, and low in fiber are associated with increased risk factors such as insulin resistance and high cholesterol, which contribute to these conditions [2]. Therefore, modifying eating behaviors can be a critical strategy in preventing and managing chronic diseases [3].

Food is an essential part of life and human eating behavior is complex and influenced by internal and external factors [4]. For example, stress has a major impact on the development of irregular eating patterns [5] and its effect on the control of food intake has long been neglected [6]. There is evidence that, individuals with a higher level of perceived stress showed higher tendency for reward-based eating [7]. Individuals with obesity experience many daily stressors [8], including their struggle with body weight loss and dieting [6], which may lead to pathologic emotional regulation coping strategy of overeating. There is evidence that obesity is associated with difficulties in emotional regulation [9], and obese individuals may be more vulnerable to developing stress-induced irregular eating patterns [10].

The reward-based eating drive is a crucial factor in understanding the mechanism of obesity-related irregular eating patterns [11]. In general, there is an association between higher BMI and greater sensitivity to reward-related processes [12, 13]. Consumption of high palatable food is a major factor in obesity-related irregular eating and stress-induced overeating [14, 15]. Reward pathways are also influenced by highly palatable food [16]. The "food addiction" hypothesis suggests that consumption of these foods may alter the brain's reward system, leading to addiction-like pattern of behavior characterized by compulsive overeating [17]. There is evidence that stress-induced negative emotions are likely to be counteracted by eating more food through activation of the reward system [11]. Palatable food activates reward pathways including dopamine and endocannabinoid release [18]. Furthermore, alteration in the mesolimibic dopamine circuit as a primary component of the reward system have been observed in overeating and obesity [17].

The RED scale assesses the self-reported reward-related eating behavior with its three dimensions lack of control, lack of satiation, and preoccupation with food [19]. The original 9-item RED-9 was developed by Epel et al. [19] and also exists in a 13-item version (RED-13 [20]) and 5-item short version (RED-X [21]). Compared to other questionnaires such as the Yale Food Addiction Scale (YFAS [22]), which focus on reward-based eating at pathological levels, the RED is designed to measure the reward-based eating drive in a non-pathological population. The presence of reward-based drive occurs long before the development of eating pathology and does not necessarily lead to food addiction [19]. For example, an association between higher RED score and higher intake of laboratory palatable foods was observed in a Canadian university sample [21].

In Germany, the prevalence of obesity, type 2 diabetes, and cardiovascular disease has significantly increased over recent decade [23–25]. Eating patterns are a major contributor to these chronic diseases, but also one of the modifiable risk factors in preventing and managing these conditions. Reward-based eating is a crucial factor in understanding the mechanism of irregular eating patterns [11]. For this reason, it is important to have a German version of the RED scale. We therefore, examined the factor structure and psychometric properties of two German versions of the reward-based eating drive (RED) scale, the German RED-9 and the German RED-13. We also aimed to replicate the original RED scale validation study by examining its association with BMI.

Design and participants

The translation process of the reward-based eating drive scales RED-9 and RED-13 developed by Epel et al. [19] and Mason et al. [20] from English to German was carried out in accordance with the International Test Commission (ITC) Guidelines for Translating and Adapting Tests [26]. Items were translated from German into English by one expert in translation with university teaching credentials, and then back-translated into German by bilingual persons as well as professional translator of questionnaires. Comparison and reconciliation of the original and back-translated items was carried out by a group of experts, followed by a second round of forward and back translation. After the translation process, data collection in this cross-sectional survey was conducted from October 2021 to October 2022 among medical undergraduates at the Johannes Gutenberg-University Mainz (Germany). All participants gave written informed consent and received a data protection declaration in accordance with the Helsinki Declaration. The study was approved by the Ethical Committee of the Landesärztekammer Rheinland-Pfalz (Germany) in accordance with ethical, medical-scientific, and legal guidelines (2019–14290). The mean age of the total sample (N = 311) was 23.29 ± 5.44 years and 28% of the participants were male (72% female). A detailed description of the sociodemographic data of the total sample is given in Table 1.

Table 1

Sociodemographic description of the study population (N = 311).
Age, M ± SD	23.29	± 5.44
Gender, N (%)
Female	222	(71.4%)
Male	89	(28.4%)
BMI, M ± SD	22.93	± 3.55
BMI-class, N (%)
Obesity	18	(5.8%)
Overweight	45	(14.5%)
Normal weight	195	(62.7%)
Underweight	53	(17%)
Smoking, N (%)	29	(9.3%)
Education, N (%)
Higher school-leaving certificate	304	(97.7%)
Secondary school-leaving certificate	1	(.3%)
Intermediate school-leaving certificate	2	(.6%)
Others	4	(1.3%)
Marital status, N (%)
Single	289	(92.9%)
Married	19	(6.1%)
Living separately	1	(.3%)
Divorced	2	(.6%)
Nationality, N (%)
German	262	(84.2%)
Austrian	7	(2.3%)
Greek	1	(.3%)
American	1	(.3%)
Turkish	2	(.6%)
Others	38	(12.2%)

Table 1

Questionnaires

Reward-based Eating Drive scale (RED; Epel et al. [19] and Mason et al. [20]): The RED scale assesses self-reported reward-related eating behaviour. The RED-9 was developed by Epel et al. [19] and also exists in a 13-item version (RED-13 [20]). Both versions measure the three dimensions of lack of control, lack of satiety and preoccupation with food. The lack of control dimension measuring loss of control over food. The lack of satiety dimension deal with not feeling full despite eating a sufficient amount of food. The third dimension, preoccupation with food, about how much time is spent thinking about food. The questionnaire consists of self-developed items and original items from the Food Craving Questionnaire (FCQ [27]), the Dutch Eating Behaviour Questionnaire (DEBQ [28]), the Binge Eating Scale (BES [29]), the Three Factor Eating Questionnaire (TFEQ [30]), and the Yale Food Addiction Scale (YFAS [22]) appear in the RED. A total score is calculated as the sum of all items and each of the three dimensions.

German version of the Yale Food Addiction Scale (YFAS [31]): The YFAS [22] contains 25 items that assess pathological levels of food addiction. The symptoms are based on the 7 symptoms of substance dependence listed in the DSM-IV-TR (e.g. withdrawal, tolerance, continued use despite problems [32]). Participants rate the items in dichotomous rating schemes, but also on frequency scales (e.g. from never to four or more times a day). A summed YFAS total score was calculated according to the continuous summed score method of dichotomous items (three items are 'primer' items and are not included in the total score; e.g. [33]), as well as a method a total symptom counting method, where total score ranges from 0 (0 symptoms of food addiction) to 7 (7 symptoms of food addiction). The YFAS has been translated into German and validated by Meule et al. [31].

German version of the Dutch Eating Behaviour Questionnaire (DEBQ [34]): This 33-item scale [28] consists of three subscales. The 10-item subscale "Restraint" (DEBQ-R) assesses restraint in eating, also known as cognitive restraint. The 10-item External Eating subscale (DEBQ-E) measures the tendency to eat in response to external food stimuli, such as the sight, taste and smell of attractive food. There is also a 13-item Emotional Eating subscale (DEBQ-Em), which measures eating triggered by specific and diffuse emotions such as anger, boredom, anxiety or fear. Participants respond to items on a scale from 1 (never) to 5 (very often). Nagl et al. [34] investigated the psychometric properties of the German version of the DEBQ.

German Version of the Food Craving Questionnaire – Trait - Reduced (FCQTR [35]): One of the most commonly used instruments to assess specific food cravings is the trait version of the Food Cravings Questionnaire (FCQ-T [27]). Fifteen items with the highest item-total-correlations in the validation study of the German FCQ-T [36] were selected from the original 39 items. Items are scored from 1 to 6 (no inverted items). All items are summed to a total score.

Demographic questionnaire and body mass index: Further information on age, gender, BMI, smoking status, education, marital status, and nationality was collected using a standardized questionnaire. For a detailed specification of BMI, the participants were classified into four BMI classes: underweight (BMI < 20), normal weight (20 ≥ BMI < 25), overweight (25 ≥ BMI < 30), and obesity (BMI ≥ 30).

Statistical analysis

The software program used to analyze the data was R v3.5.0 [37], including the associated packages of Lavaan, psych, GPArotation, and ggplot2. First, mean values (M), standard deviation (SD), corrected item-rest correlations, skewness, kurtosis and Guttman’s λ were determined for the RED-13 and the RED-9. Second, CFA with 1-factor model and 3-factor model of the RED-13 and the RED-9 were performed. Goodness of fit was assessed by adjusted chi-square (χ2), comparative fit index (CFI), the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR). We used fit criteria of Hu & Bentler [38]: CFI > 0.95, RMSEA < 0.06, SRMR < 0.08. Third, the internal consistency of the RED was tested using Cronbach’s alpha and McDonald’s omega. Higher values of omega and alpha (.70 and above) reflect greater internal consistency [39, 40]. Fourth, Pearson correlations were used to test the extent to which the RED-13 and the RED-9 correlated with total scores on other questionnaires and with BMI.

Item descriptive statistics

A complete overview of the means, standard deviations and corrected item-rest correlations (Rit) for the RED-9 and the RED-13 appear in Table 2. The corrected item-test correlation for all items is greater than .5 indicating item discrimination. In addition, skewness, kurtosis and Guttman’s λ of all items are presented (see Table 2).

Table 2

Item characteristics of the German version RED.
Dimension	item	mean	SD	Item-rest correlation	S	K	λ
13-item RED
Loss of control	1	1.71	0.97	0.81	0.23	-0.71	0.84
Loss of control	2	1.20	0.96	0.81	0.68	-0.18	0.84
Loss of control	3	2.37	1.31	0.83	-0.50	-0.97	0.86
Loss of control	4	1.70	1.08	0.81	0.29	-0.70	0.84
Lack of Satiety	5	1.28	1.04	0.82	0.57	-0.49	0.85
Lack of Satiety	6	1.36	1.06	0.83	0.43	-0.74	0.86
Preoccupation with food	7	0.93	1.00	0.81	0.92	0.09	0.84
Preoccupation with food	8	0.72	0.99	0.82	1.36	0.86	0.84
Preoccupation with food	9	1.02	1.03	0.81	0.82	-0.15	0.84
Lack of Satiety	10	0.75	0.80	0.81	1.04	0.96	0.84
Preoccupation with food	11	0.45	0.69	0.81	1.90	4.93	0.84
Loss of control	12	1.84	1.18	0.82	-0.15	-1.16	0.85
Loss of control	13	3.06	0.84	0.82	-1.50	3.32	0.85
Total score		18.39	7.50		0.82	-0.15
9-item RED
Loss of control	1	1.71	0.97	0.74	0.23	-0.71	0.76
Loss of control	2	1.20	0.96	0.72	0.68	-0.18	0.75
Loss of control	3	2.37	1.31	0.77	-0.50	-0.97	0.79
Loss of control	4	1.70	1.08	0.73	0.29	-0.70	0.76
Lack of Satiety	5	1.28	1.04	0.75	0.57	-0.49	0.78
Lack of Satiety	6	1.36	1.06	0.76	0.43	-0.74	0.79
Preoccupation with food	7	0.93	1.00	0.74	0.92	0.09	0.75
Preoccupation with food	8	0.72	0.99	0.75	1.36	0.86	0.76
Preoccupation with food	9	1.02	1.03	0.74	0.82	-0.15	0.76
Total score		12.28	5.61		0.46	0.02
S = skew. K = kurtosis. λ = Guttman’s λ.

Confirmatory Factor Analysis (CFA)

The 1-factor model of the RED-13(x² = 410.718, df = 65, p ≤ 0.001, CFI = 0.710, RMSEA = 0.131, SRMR = 0.094) and RED-9 (x² = 218.052, df = 27, p ≤ 0.001, CFI = 0.720, RMSEA = 0.151, SRMR = 0.095) showed suboptimal fit indices. The 3-factor solution of the RED-9 (x² = 43.858, df = 24, p ≤ 0.01, CFI = 0.971, RMSEA = 0.052, SRMR = 0.041) indicated much better fit indices compared to the 3-factor solution of the RED-13 (x² = 172.882, df = 62, p ≤ 0.001, CFI = 0.907, RMSEA = 0.076, SRMR = 0.056). Table 3 presents the factor loadings of the four models.

Table 3

Factor loadings for items tested in RED-13 and RED-9.
		RED-13				RED-9
Item	# on RED Scale	Single-Factor	LOC	PO	LOS	Single-Factor	LOC	PO	LOS
Ich fühle mich angesichts leckerem Essen außer Kontrolle. (I feel out of control in presence of delicious food)	1	0.58	0.67			0.63	0.72
Wenn ich anfange zu essen, kann ich scheinbar nicht aufhören (When I start eating, I just can't seem to stop)	2	0.65	0.78			0.72	0.76
Es fällt mir schwer, Essensreste auf meinem Teller übrig zu lassen. (It is difficult for me to leave food on my plate)	3	0.34	0.39			0.35	0.34
Wenn es um Speisen geht, die ich liebe, habe ich keine Willenskraft. (When it comes to food I love, I have no wilpower)	4	0.57	0.69			0.66	0.72
Ich werde so hungrig, dass mir mein Magen oft wie ein Fass ohne Boden erscheint. (I get so hungry that my stomach often seems like a bottomless pit)	5	0.43			0.47	0.44			0.56
Ich werde nicht leicht satt. (I don't get full easily)	6	0.36			0.43	0.34			0.42
Es scheint, als ob die meisten meiner Wachstunden mit Gedanken über essen oder nicht essen beschäftigt sind. (It seems like most of my waking hours are preoccupied by thoughts about eating or not eating)	7	0.62		0.71		0.55		0.78
Ich habe Tage, an denen ich an nichts anderes als an Essen denken kann. (I have days when I can't seem to think about anything else but food)	8	0.59		0.72		0.49		0.72
Essen habe ich immer im Kopf. (Food is always on my mind)	9	0.66		0.75		0.54		0.72
Ich habe die ganze Zeit Hunger. (I feel hungry all the time)	10	0.59			0.69
Ich kann nicht aufhören, ans Essen zu denken, egal, wie sehr ich es versuche. (I can't stop thinking about eating no matter how hard I try)	11	0.67		0.75
Ich konsumiere weiterhin bestimmte Speisen, obwohl ich keinen Hunger mehr habe. (I find myself continuing to consume certain foods even though I am no longer hungry)	12	0.49	0.59
Wenn mir das Essen gut schmeckt, esse ich mehr als gewöhnlich. (If food tastes good to me, I eat more than usual)	13	0.42	0.47
RED label = Number of item on RED scale; Single-Factor = Loading onto single-factor solution; LOC = Loss of control; PO = Preoccupation with food; LOS = Lack of Satiety.

Internal Inconsistency

Cronbach’s alpha and McDonald’s omega of the total score and the three dimensions of the RED-13 and the RED-9 indicated good internal consistency (see Table 4), with the exception of the dimension Preoccupation with food in the RED-13 (α = .54; ω = .55).

Table 4

RED scale internal consistencies.
	RED-13		RED-9
	α	ω	α	ω
Total	0.84	0.87	0.78	0.83
Loss of control	0.77	0.85	0.72	0.77
Preoccupation with food	0.54	0.55	0.88	0.95
Lack of Satiety	0.82	0.85	0.78	0.78
α = Cronbach’s alpha, ω = McDonald’s omega.

Construct Validity

The RED-13 and the RED-9 were positively correlated with all other scales (see Table 5), indicating convergent validity. However, the correlations were in the moderate range (.21-.67), indicating divergent validity. Both versions of the RED were also positively associated with BMI (RED-13: r = .23, p ≤ .001; RED-9: .26, p ≤ .001).

Table 5

Correlations among RED-13, RED-9 and other scales.
Scale	RED-13	RED-9	DEBQ-E	DEBQ-Em	DEBQ-R	YFAS-Sum	YFAS-SXS	TFEQ-R	BMI
Mean (SD)	18.39 (7.5)	12.28 (5.61)	2.82 (.54)	2.04 (.76)	2.44 (.87)	18.03 (9.33)	1.11 (.75)	29.77 (10.53)	22.93 (3.55
RED-13	1.00
RED-9	.97, p ≤ .001	1.00
DEBQ-E	.41, p ≤ .001	.37, p ≤ .001	1.00
DEBQ-Em	.45, p ≤ .001	.43, p ≤ .001	.43, p ≤ .001	1.00
DEBQ-R	.27, p ≤ .001	.29, p ≤ .001	.24, p ≤ .001	.35, p ≤ .001	1.00
YFAS-Sum	.52, p ≤ .001	.49, p ≤ .001	.27, p ≤ .001	.46, p ≤ .001	.34, p ≤ .001	1.00
YFAS-SXS	.21, p ≤ .001	.19, p ≤ .001	.18, p ≤ .01	.32, p ≤ .001	.23, p ≤ .001	.53, p ≤ .001	1.00
TFEQ-R	.67, p ≤ .001	.64, p ≤ .001	.42, p ≤ .001	.66, p ≤ .001	.37, p ≤ .001	.68, p ≤ .001	.38, p ≤ .001	1.00
BMI	.23, p ≤ .001	.26, p ≤ .001	.07, p = .22	.28, p ≤ .001	.29, p ≤ .001	.25, p ≤ .001	.18, p ≤ .01	.22, p ≤ .001	1.00
BMI = body mass index; DEBQ = Dutch Eating Behaviour Questionnaire; E = subscale external; Em = subscale emotional; FCQT-R = Food Craving Questionnaire; R = subscale restraint; RED = Reward-based eating drive scale; Sum = summed score; SXS = symptom count; YFAS = Yale Food Addiction Scale.

The Reward-based Eating Drive (RED) scales are widely used and well-established self-report scales that measure reward-related eating behavior along the three dimensions of lack of control, lack of satiation, and preoccupation with food. In these analyses, we psychometrically evaluated a German version of the reward-based eating drive (RED) questionnaire.

In addition to the original RED-9 by Epel et al. [19], there is also a 13-item version (RED-13 [20]) and a 5-item short version (RED-X [21]). We investigated the factor structure and psychometric properties of the translated German version of the 13-item RED and the 9-item RED. Consistent with the original RED validation paper by Epel et al. [19], the results support the 3-factor model with its three dimensions lack of control, lack of satiation, and preoccupation with food. The 3-factor solution of the 13-item RED and the 9-item RED showed better indices of fit than the 1-factor solution of the RED-13 and the RED-9. Both versions of the RED showed acceptable internal consistency, good item rest correlation, and good construct validity with other reward eating scales. The RED-13 and the RED-9 also show a significant correlation with BMI, replicating the original RED scale development paper. The 9-item RED with the 3-factor model showed the best psychometric properties in terms of fit indices and was in line with the recommendation by Hu & Bentler [38] regarding the cut-off value for CFI, RMSEA and SRMR.

The RED is designed to measure reward-based eating drive in a non-pathological population. In the current study, there was a positive association between BMI and the RED. This is consistent with the findings of other studies in different countries [19–21]. The RED total score is also a predicting factor of changes in BMI over the course of one’s lifetime and earlier onset of obesity [19]. In addition, recent data have shown that the RED is also associated with self-reported type 2 diabetes [20, 21]. There is an association between alterations in food reward processing and both obesity and type 2 diabetes [41]. Therefore, the RED may help to identify individuals who are more vulnerable to overeating behaviors and at risk of adverse metabolic health outcomes [19]. Furthermore, an intervention based on mindfulness skills has demonstrated weight-loss by reducing reward-related eating [42].

To the authors’ knowledge this is the first study to create and evaluate the psychometric properties of a German version of the RED. A major strength of this study is the adequate sample size, which is comparable to other validation studies of the RED [20]. Another strength is the use of the standardized, internationally established and reliable questionnaires to measure reward-related eating. Limitations need to be considered. The present data are limited to young medical undergraduates. Thus, further research is needed to validate our findings in middle-aged and older adults and to look more closely at diabetes status. Current body weight and height were self-reported for the calculation of BMI, which can be inaccurate in young adults [43].

In conclusion, the German RED-9 is a valid and reliable instrument for the assessment of reward-related eating behavior. The scale can be generally used in non-pathological population young adult populations and is related to BMI. Further research is needed to improve the understanding of the relationship between reward-related eating and obesity and diabetes and other diet-related chronic diseases in the German population.

Funding: None.

Ethical Statement: The study was approved by the Ethical Committee of the Landesärztekammer Rheinland-Pfalz (Germany) in accordance with ethical, medical-scientific, and legal guidelines (2019-14290).

Declaration of competing interest: None.

Data availability: Data will be made available on request

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No competing interests reported.

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Factor structure and psychometric properties of the German version of the Reward-based Eating Drive scale

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