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* Inserm, U258, Villejuif, France;
Nutrition Department, Hospital University, Lille, France;
** Observatoire des consommations alimentaires, AFSSA, Maisons-Alfort, France;
The Fleurbaix-Laventie Ville Santé Association, Laventie, France; and
Health Care Research Unit, Sahlgrenska University Hospital, University of Göteborg, Sweden
2To whom correspondence should be addressed. E-mail: delauzon{at}vjf.inserm.fr.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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KEY WORDS: • eating behavior • food intake • adult • teenager • epidemiology
To understand interactions between eating and health and to develop nutritional prevention programs in the context of the global obesity epidemic, better knowledge of the different eating behaviors and their prevalence in the general population would be helpful. Dietary restraint, which seems to be widespread in modern societies, is indeed suggested to play a causal role in the development of eating disorders and obesity (1,2). Other types of eating behaviors have been identified, such as the loss of control over intake and the tendency to overeat in the presence of emotional distress (3), but little is known about their prevalence in the general population.
Several questionnaires, the Restraint Scale (RS)3 (4), the Dutch Eating Behavior Questionnaire (DEBQ) (5), and the Three-Factor Eating Questionnaire (TFEQ) (6), have been used in the study of eating behavior. In healthy populations, components of eating behavior assessed by these questionnaires are related to energy and macronutrients intake or to specific food intake (sweet and fattening foods) (7–10). However, these questionnaires include many items (10 to 51 items) that limit their use in epidemiological studies of multifactorial disease, where a number of other questionnaires are required. Karlsson et al. (11) developed a reduced version of the Stunkard and Messick TFEQ, the Three-Factor Eating Questionnaire Revised 18-item version (TFEQ-R18), which comprises 3 different scales corresponding to cognitive restraint, emotional eating, and uncontrolled eating. Consisting of 18 items, the TFEQ-R18 is easier to use in epidemiological studies where subjects complete many questionnaires. The TFEQ-R18 scales were derived in obese subjects; however, identical factors were obtained by Hyland et al. in a student sample (12), indicating that the instrument is valid also in nonobese individuals. In fact, Hyland et al. (12) performed a psychometric analysis of the TFEQ and they compared their results to those obtained using the DEBQ structure. That psychometric analysis identified 3 factors similar to those used in the TFEQ-R18. We conducted the current study to determine whether these factors are associated with different eating patterns in a general population by studying the relationship among the 3 TFEQ-R18 scales and reported food intake, as measured by a food frequency questionnaire. Associations are described in terms of energy and macronutrient intakes and also in terms of food items. Analyses were performed separately in adults and in teenagers and young adults.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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For the purpose of this study, only adolescents (
14 y) and adults were considered. Among the 393 families invited to participate in the FLVS II study, 294 (75%) agreed to participate. Of the 887 subjects older than 14 y who participated in the study, 14 individuals were excluded due to missing sociodemographic or anthropometric data, and 19 individuals did not complete the food frequency questionnaire. Thus, a total of 31 subjects (3.5%) were excluded from the analysis. They were similar to the subjects remaining in the analysis with regard to gender (47.7 and 48.4% of men among respondents and nonrespondents, respectively, P = 0.94), age (mean = 33.0 and 28.3 y, P = 0.11), and body mass index (23.5 and 22.9 kg · m–2, P = 0.56).
Subjects were divided into 2 groups, the adult group, which comprised all the parents, and the teenagers and young adults group (the offspring). The sample for analysis was thus composed of 236 (45.4%) men and 284 (54.6%) women in the adult group (aged 30 to 67 y), and 171 (51.2%) boys and 163 (48.8%) girls in the teenagers and young adults group (aged 14 to 27 y).
Three-Factor Eating Questionnaire. Eating behavior was described using a French translation of TFEQ-R18 (11). The instrument is a shortened and revised version of the original 51-item TFEQ (6). The translation of the French version was accomplished using common procedures for cross-cultural adaptation, including back translation by a native English speaker. The questionnaire refers to current dietary practice and measures 3 different aspects of eating behavior: restrained eating (conscious restriction of food intake in order to control body weight or to promote weight loss), uncontrolled eating (tendency to eat more than usual due to a loss of control over intake accompanied by subjective feelings of hunger), and emotional eating (inability to resist emotional cues). The TFEQ-R18 consists of 18 items on a 4-point response scale (definitely true/mostly true/mostly false/definitely false). Responses to each of the 18 items are given a score between 1 and 4 and item scores are summated into scale scores for cognitive restraint, uncontrolled eating, and emotional eating (see the Appendix) (6,11). The raw scale scores are transformed to a 0–100 scale [((raw score – lowest possible raw score)/possible raw score range) x 100] and the commonly used "half-scale" method is utilized to compensate for missing data on some items. Higher scores in the respective scales are indicative of greater cognitive restraint, uncontrolled, or emotional eating. The mean number of missing values per subject was 0.06 (min–max: 0–2).
Psychometric analysis procedure.
The TFEQ-R18 was constructed in a Swedish obese population and was used here in a French general population. Therefore, the internal validity of this tool in our sample had to be confirmed. We therefore performed a multitrait/multi-item analysis in both adult and teenager and young adult samples to test scaling assumptions underlying the construction and scoring of the TFEQ-R18. The aim of the analysis was to check that items were strongly correlated to their assigned scales (convergent validity) and more correlated to their assigned scale than to the other 2 (discriminant validity). A matrix of item-scale correlations was computed and the correlations for each item were compared across scales. Item convergent validity (Criterion 1) was indicated when each item correlated substantially with the scale that it was assumed to represent (r 0.40, corrected for overlap, i.e., the correlation was assessed between an item and a modified scale corresponding to its assigned scale excluding the studied item). Item-discriminant validity (Criterion 2) was supported when items correlated significantly higher with their assigned scale than with all other scales. A difference between 2 item-scale correlations was assumed to be significant when it was higher than 2 standard errors of the correlation matrix (1/
n). The scaling fulfillment was evaluated by the proportion of items in a scale that met both convergent and discriminant validity. The internal-consistency reliability of scale scores was estimated by Cronbach’s 
coefficients.
Food Frequency Questionnaire (FFQ). The dietary questionnaire used in the study was specifically developed for the FLVS subjects. It is a semiquantitative self-administered FFQ that relates to intake during the previous 12 mo and inquires about 124 different foods. The foods were chosen among those that contributed most to energy and macronutrients intake in the 3-d food records completed by the same population during the FLVS I study (14). From the same data, gender-specific standard portions were estimated as the mean consumption for each food and beverage. From the reported frequencies of foods and drinks and gender-specific portions, it was possible to estimate an average daily intake of foods, drinks, energy, and major nutrients. Estimations of the daily energy and macronutrients intakes were computed from a food composition database derived from the French food composition tables, "Répertoire général des aliments" (15), and the McCance and Widdowson food composition tables (16). In order to study differences in types of foods consumed by each group of subjects, intakes of foods and drinks were aggregated into 25 different food groups. The groups were offal (e.g., liver or guts), processed pork meat products (e.g., ham or sausages), eggs, meat, cooked dishes (e.g., pizza or lasagna), fish, cheese, yogurt, dairy desserts, sugar and confectionery, dietary fat, milk, bread, cereals and pasta, potatoes, French fries, cakes/pastries/biscuits, oleaginous fruits (e.g., peanuts), fruit, green vegetables, dry vegetables, fat-reduced foods, sweet beverages, alcoholic beverages, and water.
We assessed the reproducibility and validity of the FFQ. Ninety-four participants completed four 24-h dietary recalls over a 1-y period and a repeat administration of the FFQ. For energy, the attenuation-corrected Pearson correlation was 0.73 (P < 0.0001). For protein, fat, and carbohydrate intake, it was 0.47, 0.66, and 0.74, respectively (P < 0.0001 for all correlations). For foods, the same correlations were, for example, 0.76 for milk (P < 0.0001), 0.58 for fats (P = 0.0004), 0.38 for fruit (P = 0.0012), and 0.78 for green vegetables (P < 0.0001).
Statistical analysis. To test for associations, TFEQ-R18 and dietary variables were transformed into qualitative variables. For the TFEQ-R18 data, the respondents were grouped into gender- and group- (adults or teenagers and young adults)-specific tertiles, according to their relative position on each scale. With the same method, respondents to the FFQ were divided into "low" and "high" eater groups for each food group, according to the median intake of their gender and age subgroup.
Energy and macronutrient contributions to energy intake were used as continuous variables (energy intake was log-transformed).
Separate analyses were conducted in the adult group and in the teenager and young adult group. In the descriptive analysis, we used 
2 (for qualitative variables) and Kruskall-Wallis tests (for continuous variables). Multivariate analyses were performed by logistic regressions for qualitative data and analyses of variance-covariance for quantitative data, controlling for gender and age as continuous variables within each age group. When a significant interaction between a TFEQ-R18 factor and gender was detected, analyses were also conducted separately for men and for women. The Generalized Estimating Equations (SAS proc genmod) were used to take into account the familial correlation between individuals (17). A significance level of P < 0.05 was required for an explanatory variable to remain in the models.
The Statistical Analysis Systems statistical software package version 8.2 (SAS Institute) was used for the analyses.
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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0.40, corrected for overlap) for items convergent validity. Item-scale correlations (corrected for overlap) showed, therefore, a very good item internal consistency. Correlations between items assigned to cognitive restraint and the other 2 scales were low (r < 0.35) and therefore all cognitive restraint items succeeded in the discriminant validity test. Only 1 uncontrolled eating item failed in the discriminant validity test; this was in the adult group. In summary, 5 of 6 cognitive restraint items in each age group, 8 of 9 uncontrolled eating items in adults, and 9 of 9 uncontrolled eating items in teenagers and young adults, and 3 of 3 emotional eating items in each age group met the criteria for both convergent and discriminant validity. Internal-consistency reliability coefficients (Cronbach’s ) for each of the 3 scales were above the 0.70 standard and below the 0.90 limit recommended for individual assessment. These coefficients were similar to those found in the Swedish Obese Subjects study (11).
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Relationships between eating behavior and food intake. The association among the 3 TFEQ-R18 scores and reported food intake was quite different in the 2 age groups.
In adults (Table 3), CR score was positively associated in both sexes with healthy food groups like fat-reduced food or green vegetables and negatively associated with French fries and sugar and confectionery. Uncontrolled eating was positively associated with energy-dense foods like fat or potatoes and, only in men, with fruit. Finally, subjects with a high emotional eating score had a higher consumption of snacking foods such as oleaginous fruits and cakes/pastries/biscuits.
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In adults, for the food groups which were associated with 2 TFEQ-R18 scores, a multivariate logistic regression was performed to assess whether these associations were independent or explained by the correlations between the 2 TFEQ-R18 scores. The odds ratio for yogurt intake decreased from 1.75 for cognitive restraint (P = 0.047) and 1.87 for uncontrolled eating (P = 0.026) to 1.53 (P = 0.21) and 1.68 (P = 0.10), respectively, when both scores were included in the model. Alcoholic beverage intake remained independently and negatively associated with both cognitive restraint (P = 0.015) and emotional eating (P = 0.027) scores. For cognitive restraint, the association with alcoholic beverages was not linear but only due to a high tertile of cognitive restraint, compared to the 2 lower levels of cognitive restraint.
In teenagers and young adults, there were fewer associations between reported intake of specific food groups and TFEQ-R18 scores (Table 4). Most relationships were found with the cognitive restraint score. The food groups associated with cognitive restraint were different from those found in adults: the consumption of energy-dense foods like sugar, French fries, or processed pork meat products was negatively associated with CR in teenagers and young adults. Only alcoholic beverages intake was positively related to uncontrolled eating; fruit and yogurt among men were negatively and positively related to emotional eating, respectively.
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For any score, results did not differ before and after adjustment for the other 2 TFEQ-R18 factors.
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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In our population, the TFEQ-R18 was able to distinguish among different eating patterns as assessed by reported food intake. In addition, it highlights specific differences between genders and between "teenagers and young adults" and adults. The comparison between genders showed higher cognitive restraint and emotional eating scores in women. These results were consistent with several studies that include both sexes (7,18–20). It is, however, notable that most of the studies about eating behavior were conducted only among women (1,10,21–25). The higher cognitive restraint scores in women might be related to a greater propensity for dieting (26–28). Our study also showed that associations between reported food intake and TFEQ-R18 scores were similar in both genders, except for a few relations. The influence of eating behavior on specific choices appears therefore to be mostly independent of gender (8).
In adults, the 3 different eating behaviors identified by the TFEQ-R18 were associated with different patterns of reported food intake. High restrainers reported preferentially "healthy" food, such as fish, vegetables, and fat-reduced food. Emotional eating was associated with snack foods, such as cakes, biscuits, and oleaginous fruits, and uncontrolled eaters reported eating more fatty and salty foods. Sunday et al. (29) reported that restrained eaters displayed different attitudes toward commonly encountered foods from unrestrained eaters, with a preference for low-fat foodstuffs. While several researchers have suggested a specific avoidance of fat in restrained eaters (10,19,30), the trend to avoid animal products and instead to select "healthy" foods, such as fruit and vegetables, was less consistent (7,8,30). As reported by others (7–9,20,23), high female restrainers were also found to have a lower energy intake, a lower contribution of fat to energy intake, and a higher part of energy derived from protein. Concerning emotional and uncontrolled eating, our findings were consistent with a previous paper (10), which suggested that uncontrolled and emotional eating affected positively the preference for "sweet" and "fattening" foods. In our study, a high uncontrolled eating score was associated with a high energy intake. This is in line with previous observations that the disinhibition and hunger scales of Stunkard and Messick TFEQ were positively associated with energy intake (20,23,31). Indeed, items of the TFEQ-R18 uncontrolled and emotional eating scales were derived from the TFEQ disinhibition and hunger scales.
Reported food intake was differently affected by the 3 TFEQ-R18 factors among the teenager and young adult and the adult groups. Especially, cognitive restraint was predominately associated with a higher consumption of healthy foods (fat-reduced foods, green vegetables, fish, yogurt) among the adult group, whereas it was associated with a lower consumption of fat and sweet foods (French fries, sugar and confectionery, processed pork meat products, fat, sweet beverages) among the teenagers and young adults group. UE and EE scores were less able to differentiate specific food attitudes in teenagers and young adults compared with adults. This may be due to a specificity of these eating behaviors in teenagers and young adults or to our measurement tools, which may be less understood by teenagers and young adults. Indeed, the TFEQ-R18 questionnaire was developed among middle-age subjects. TFEQ-R18 items would thus refer to specific behavior, which could be more confusing for teenagers and young adults. Teenagers and young adults may also be less able to assess their own eating behavior. Children’s eating behaviors were examined in several other studies, especially for the impact of parents’ eating behavior on children’s eating patterns (32,33). However, in studies that reported the relationships between eating behavior and reported food intake, teenagers were not examined as a distinct group. Indeed, they were often included either in the adult group (10,26,28,34) or in the child group (9,35). Differences between middle-age adults and teenagers or young adults regarding eating behavior and food intake were not underlined. In the teenagers and young adults group, higher uncontrolled eaters reported a higher alcoholic beverage intake than medium uncontrolled eaters [OR = 1.38 (0.77–2.48), OR = 0.68 (0.37–1.25), respectively, for the higher vs. lower UE tertile and for the medium vs. lower UE tertile; P = 0.04]. Thus, uncontrolled eating, which expresses inability to limit food intake and an extreme sensitivity to external stimuli, may detect behaviors, which could lead to excessive alcoholic beverage intake. On the other hand, an excessive alcohol intake can disregulate food intake and may therefore lead to an excessive food intake.
The FFQ measures a reported food intake. It would therefore be greatly important to identify underreporters. Unfortunately, current methods for assessing underreporting were not usable with a food intake measured from a FFQ. Consequently, it would be impossible to directly evaluate underreporting in our study. However, a previous study (36) defined specificity of underreporters’ eating patterns in our adult sample. In that study, 2 kinds of food groups were affected by underreporting. First, like cognitive restrainers, underreporters had a lower reported intake of potatoes, French fries, and sugar and confectionery, and they were characterized by a higher intake of vegetables and a larger part of protein to energy intake. Second, contrary to uncontrolled eaters, they eat less dietary fat and processed pork meat products, and consequently their contribution of fat to energy intake was lower. Few relations were found between underreporters’ and emotional eaters’ food patterns. Asbeck et al. (37) previously underlined the associations between eating behavior (restraint and disinhibition) and underreporting. Cognitive restraint could be a tool to help us to identify subjects who are likely to underreport their intake in a food frequency questionnaire (in which underreporting cannot be directly evaluated). However, further research would be needed to understand the impact of eating behaviors on underreporting to improve food intake assessment. Understanding the association between eating behavior and reported food intake may prove helpful in the analyses of the relations between health and diet.
The associations between reported food intake and eating behavior were adjusted here for age and gender. Because health awareness and access to healthy foods were partially linked to socioeconomic level, it would be of great interest in further analyses to evaluate the impact of these confounders on eating behavior and reported food intake. Unfortunately, income assessment was not possible with our data. However, adjustment for education level did not change our results.
Several studies about eating behavior were previously conducted in a general population in Quebec (20) and in France (9). The consistency of our results on food intake with those studies, especially concerning restraint or disinhibition/UE, although different eating questionnaires were used, is in favor of the suitability of the TFEQ-R18 use in the general population.
In conclusion, the TFEQ-R18 appeared to be an easy self-administered questionnaire, able to distinguish among varied eating behaviors in a general population, especially in adults. In teenagers and young adults, cognitive restraint was the most identifiable behavior.
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APPENDIX |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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The cognitive restraint scale was composed of items 2, 11, 12, 15, 16, and 18. The uncontrolled eating scale was composed of items 1, 4, 5, 7, 8, 9, 13, 14, and 17. The emotional eating scale was composed of items 3, 6, and 10.
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FOOTNOTES |
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3 Abbreviations used: CR, cognitive restraint; DEBQ, Dutch Eating Behavior Questionnaire; EE, emotional eating; FLVS, Fleurbaix-Laventie Ville Santé; RS, restraint scale; TFEQ, Three-Factor Eating Questionnaire; TFEQ-R18, Three-Factor Eating Questionnaire-Revised 18 items; UE, uncontrolled eating.
Manuscript received 23 March 2004. Initial review completed 15 April 2004. Revision accepted 29 May 2004.
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LITERATURE CITED |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIXLITERATURE CITED |
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