Psychometric analysis of an eating behaviour questionnaire for an overweight and obese Chinese population in Singapore

Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study

BACKGROUND

Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults.

OBJECTIVE

This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition.

METHODS

University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points.

RESULTS

Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%).

CONCLUSIONS

The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56749.

Relation of preconception eating behaviours to dietary pattern trajectories and gestational weight gain from preconception to late pregnancy

Studies examining preconception eating behaviours with longitudinal dietary patterns from preconception to late pregnancy as well as gestational weight gain (GWG) are limited. We derived dietary pattern trajectories from preconception to late-pregnancy, and related preconception eating behaviours to these trajectories and GWG. Preconception eating behaviours were assessed using the Three-Factor Eating Questionnaire measuring cognitive restraint (CR) - conscious restriction of food intake, emotional eating (EE) - overeating in response to negative emotions, and uncontrolled eating (UE) - overeating with a feeling of lack of control. Dietary intakes were measured at preconception, 20-21 and 34-36 weeks' gestation with food frequency questionnaires. Dietary patterns were determined using factor analysis, and trajectories derived using group-based trajectory modelling. Inadequate and excessive GWG were defined according to Institute of Medicine guidelines based on weights at preconception and the last antenatal visit (median: 38 weeks' gestation). Two dietary patterns were derived: 'Fast Food, Fried Snacks and Desserts (FFD)' and 'Soup, Fish and Vegetables (SFV)'. Adherence trajectories from preconception to late-pregnancy were characterised as consistently high ("stable-high") and low ("stable-low"). Women with higher UE scores had higher odds of being in the "stable-high" trajectory (n = 34) of the FFD pattern [Odds Ratio (OR): 1.25, 95% Confidence Interval (CI): 1.03, 1.51], compared to "stable-low" (n = 260). Percentages of women with inadequate, adequate or excessive GWG were 21.7% (n = 70), 25.8% (n = 83), and 52.5% (n = 169), respectively; women with higher EE scores had a higher likelihood of excessive GWG [Relative Risk Ratio (RRR): 1.35, 95% CI: 1.02, 1.80], but this association was attenuated after adjusting for preconception body mass index. Eating behaviour interventions to improve dietary patterns among pregnant women may need to start as early as preconception, incorporating strategies to manage UE.

Psychometric evaluation of three-factor eating questionnaire -R18 in aging Finnish men with increased risk for type 2 diabetes

BACKGROUND

Deeper comprehension of eating-related behaviour (how and why people eat) can reveal new aspects to support health and prevent type 2 diabetes (T2D). However, such research is largely missing in aging men.

AIM

The aim was to investigate suitability of the Three-Factor Eating Questionnaire-R18 (TFEQ-R18) in Finnish aging men which is widely used to examine factors: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE).

METHODS

Study population consisted of 420 men aged 50-75, who completed the TFEQ-R18 at the baseline of the T2D-GENE lifestyle intervention study. Inclusion criteria were impaired fasting glucose (IFG) and body mass index ≥25 kg/m2. Confirmatory factor analysis was used to study psychometrics (reliability, validity, and model fit) and factor structure of TFEQ-R18.

RESULTS

The items loaded to the three factors (CR, UE, EE) as in previous studies, except two items at CR factor and one at UE factor, which were therefore omitted. UE was also discovered split into two sub factors (named as 'craving' and 'loss-of-control'), UE being a higher-order (h) factor. The resultant revised version was named as Three-Factor Eating Questionnaire Revised to 15-items with higher-order factor (TFEQ-R15h).

CONCLUSION

The original 18-item version of the TFEQ was not optimal in the population consisting of Finnish aging men with elevated T2D risk. A modified 15-item version of the TFEQ could be used to describe EB in this population instead.

Social Networking Site Use and Emotional Eating Behaviors among Chinese Adolescents: The Effects of Negative Social Comparisons and Perspective-Taking

Emotional eating has emerged as a significant disordered eating and public health concern among adolescents. Despite the widespread prevalence of social networking site (SNS) use among this population, research investigating the influence of SNS use on adolescent eating behaviors remains limited. This study is to examine the impact of SNS use on emotional eating among Chinese adolescents, with a specific focus on exploring the mediating role of negative social comparisons and the moderating effect of perspective-taking. Data were obtained through an online survey involving 778 middle school students in China. The findings indicate that SNS use exerts a positive influence on adolescents' engagement in emotional eating, with this association being mediated by the presence of negative social comparisons. Perspective-taking demonstrated a protective role in the context of adolescents' utilization of social media platforms. For individuals characterized by high levels of perspective-taking, the effects of SNS use on negative social comparisons are mitigated, subsequently reducing its impact on emotional eating.

Emotional Eating among Ghanaian University Students: Associations with Physical and Mental Health Measures

Eating behaviors are a set of cognitive processes that influence dietary decision making and, thus, overall health. Some of the most studied eating behaviors are those characterized by the Three Factor Eating Questionnaire-18 (TFEQ). The TFEQ examines three eating behaviors: emotional eating (EE), uncontrolled eating (UE), and restrained eating (RE). While frequently used, there is little information characterizing these eating behaviors in the Ghanaian population. This cross-sectional study describes EE, UE, and RE behaviors in a university student population (n = 129) in Ghana. Of the three behaviors, EE was the only one associated with any of the health outcomes in this study: BMI for males (r = 0.388, p = 0.002) and anxiety (r = 0.471, p < 0.001, higher score is less desirable), and sleep quality (r = 0.464, p < 0.001, higher score is less desirable) for females. Overweight and obese females reported significantly higher EE scores compared to healthy weight females (35.7 ± 23.7 vs. 11.9 ± 15.6, p = 0.002). No such observation was observed among overweight and obese males (p > 0.05). EE, UE, and RE scores did not differ between males and females. While this study provides important information about the eating behaviors of Ghanaian university students and allows for comparison to students from other cultures, future work must develop culturally relevant tools for the Ghanaian population.

Dietary Intakes and Eating Behavior between Metabolically Healthy and Unhealthy Obesity Phenotypes in Asian Children and Adolescents

Diet plays a critical role in the development of obesity and obesity-related morbidities. Our study aimed to evaluate the dietary food groups, nutrient intakes and eating behaviors of metabolically healthy and unhealthy obesity phenotypes in an Asian cohort of children and adolescents. Participants (n = 52) were asked to record their diet using a 3-day food diary and intakes were analyzed using a nutrient software. Eating behavior was assessed using a validated questionnaire. Metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) were defined based on criteria of metabolic syndrome. Children/adolescents with MUO consumed fewer whole grains (median: 0.00 (interquartile range: 0.00-0.00 g) vs. 18.5 g (0.00-69.8 g)) and less polyunsaturated fat (6.26% kcal (5.17-7.45% kcal) vs. 6.92% kcal (5.85-9.02% kcal)), and had lower cognitive dietary restraint (15.0 (13.0-17.0) vs. 16.0 (14.0-19.0)) compared to children/adolescents with MHO. Deep fried food, fast food and processed convenience food were positively associated with both systolic (β: 2.84, 95%CI: 0.95-6.62) and diastolic blood pressure (β: 4.83, 95%CI: 0.61-9.04). Higher polyunsaturated fat intake (OR: 0.529, 95%CI: 0.284-0.986) and cognitive dietary restraint (OR: 0.681, 95%CI: 0.472-0.984) were associated with a lower risk of the MUO phenotype. A healthier diet composition and positive eating behavior may contribute to favorable metabolic outcomes in children and adolescents with obesity.

Food Purchase Behavior during The First Wave of COVID-19: The Case of Hungary

Coronavirus disease (SARSCoV-2) appeared in 2019 was confirmed as pandemic by the WHO on 11 March 2020. Stay-at-home order had an impact on consumers’ food purchase habits, as people around the world were able to leave their homes solely in extremely severe or urgent cases. In our research, we delve into the impact of COVID-19 pandemic on consumers’ food purchase habits. The research involved 3000 consumers during the first wave of coronavirus. The sample represents the Hungarian population by gender and age. To achieve the research goals, we applied multivariate statistical tools. The findings suggest that the pandemic could not change consumer attitude significantly, but the order of factors influencing purchases changed. Consumer motivation factors were organized into four well-distinguished factors: Healthy, domestic, and environmentally friendly choice; Usual taste and quality; Reasonable price; Shelf life. Due to the lack of outstanding data during segmentation, we developed four segments by hierarchical cluster analysis: Health- and environment-conscious women; Price sensitive young people; Taste-oriented men; Quality-oriented intellectuals. The results confirm that food manufacturers and traders need to be prepared for further restrictions in the future.

Nagy-Pető D, Gál T, Soós M. Examination of the Eating Behavior of the Hungarian Population Based on the TFEQ-R21 Model

Several theories have emerged to study types of eating behavior leading to obesity, but most of the applied models are mainly related to food choice decisions and food consumer behavior. The purpose of this paper was to examine the eating attitudes of Hungarian consumers by applying the Three-Factor Eating Questionnaire (TFEQ-R21). The national representative questionnaire involved 1000 individuals in Hungary in 2019. Several multivariate statistical techniques were applied for the data analysis: exploratory and confirmatory factor analyses, multivariate data reduction techniques, and cluster analysis. This study successfully managed to distinguish the following factors: emotional eating, uncontrolled eating, and cognitive restraint. By using the factors, five clusters were identified: Uncontrolled Emotional Eaters; Overweight, Uncontrolled Eaters; Controlled, Conscious Eaters; the Uninterested; and the Rejecters; all of these could be addressed by public health policy with individually tailored messages. The empirical results led to rejection of the original Three-Factor Eating Questionnaire (TFEQ-R21), while the TFEQ-R16 model could be validated on a representative sample of adults, for the first time in Hungary.

Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks

The importance of eating behavior risk factors in the primary prevention of obesity has been established. Researchers mostly use the linear model to determine associations among these risk factors. However, in reality, the presence of nonlinearity among these factors causes a bias in the prediction models. The aim of this study was to explore the potential of a hybrid model to predict the eating behaviors. The hybrid model of structural equation modelling (SEM) and artificial neural networks (ANN) was applied to evaluate the prediction model. The SEM analysis was used to check the relationship of the emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) and their effect on different categories of eating behavior patterns (EBP). In the second step, the input and output required for ANN analysis were obtained from SEM analysis and were applied in the neural network model. 340 university students participated in this study. The hybrid model (SEM-ANN) was conducted using multilayer perceptron (MLP) with feed-forward network topology. Moreover, Levenberg–Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The tangent/sigmoid function was used for the input layer, while the linear function was applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) were calculated. Using the hybrid model, the optimal network happened at MLP 3-17-8. It was proved that the hybrid model was superior to SEM methods because the R² of the model was increased by 27%, while the MSE was decreased by 9.6%. Moreover, it was found that BSC, BAS, and EES significantly affected healthy and unhealthy eating behavior patterns. Thus, a hybrid approach could be suggested as a significant methodological contribution from a machine learning standpoint, and it can be implemented as software to predict models with the highest accuracy.

Eating behavior tendencies among Finnish adults in relation to previous weight loss attempts

BACKGROUND

The number of weight loss attempts may be associated with higher weight status and unfavorable health behaviors as well as dysfunctional eating behaviors. We aimed to study eating behavior tendencies, i.e., cognitive restraint, uncontrolled eating and emotional eating among a sample of Finnish adults who had engaged in a different number of attempts to lose weight during their lifetime.

METHODS

Data were collected through a web-based survey. Participants completed a background questionnaire (including questions on weight, height, number of attempts to lose weight) and the Three-Factor Eating Questionnaire (TFEQ-R18). Out of 1985 individuals, 1679 with complete data were included in the study. The TFEQ-R18 was tested for its reliability and fit to our study population using Cronbach's alpha and Confirmatory Factor Analysis (CFA).

RESULTS

Subscales of the TFEQ-R18 had acceptable reliability except for that of 'cognitive restraint', which reached acceptable reliability when three items were deleted (items 15, 16, 18). The revised version of the questionnaire was designated as the TFEQ-R15, which showed good fit based on CFA fit indices. Participants who had attempted to lose weight during their lifetime (n = 1229), especially those with ≥3 weight loss attempts (n = 499), had greater cognitive restraint, uncontrolled eating, emotional eating, and higher body mass index (BMI) than those with no previous weight loss attempts (n = 132).

CONCLUSIONS

Our findings suggest that eating behavior tendencies, i.e., decreasing tendencies of uncontrolled and emotional eating should receive more emphasis to support successful weight management.

Maternal eating behaviour differs between ethnic groups: Considerations for research and practice

Maternal eating behaviours such as cognitive restraint, uncontrolled, and emotional eating styles can have important implications for both maternal own weight, and the weight and eating behaviour of her children. Maternal eating style can affect her feeding interactions with her child, which in turn can influence their weight and eating behaviour. However, despite a body of research examining these relationships, research examining differences in maternal eating behaviour between ethnic groups is sparse with much of the research, particularly in the UK, conducted with White British samples. The aim of the current research was therefore to explore how maternal eating behaviour may differ between ethnic groups in the UK; 659 UK mothers with a child aged 5-11 years completed a self-report questionnaire. Items included ethnicity, demographic data, and the 3-factor eating questionnaire to measure maternal cognitive restraint, uncontrolled, and emotional eating. Mothers from Chinese backgrounds were significantly higher in cognitive restraint and lower in emotional and uncontrolled eating compared with all groups. Conversely, mothers from South Asian backgrounds were the highest in emotional and uncontrolled eating and lower in cognitive restraint than all other groups. Black mothers were also higher in uncontrolled eating compared with White British and Chinese mothers. Variations in maternal eating behaviours vary between ethnic groups. Understanding how cultural factors may influence these variations is important, as maternal eating behaviours can influence her own and her child's weight. Maternal eating behaviour may therefore be a contributor to higher levels of overweight among South Asian and Black children living in the UK.

Exploring the Relationship between Body Composition and Eating Behavior Using the Three Factor Eating Questionnaire (TFEQ) in Young New Zealand Women

Obesity is a leading cause of morbidity and mortality, yet is preventable. This study aimed to investigate associations between body mass index, body fat percentage and obesity-related eating behaviors. Women (n = 116; 18–44 years) were measured for height, weight and body fat using air displacement plethysmography (BodPod). Women completed the validated Three Factor Eating Questionnaire to assess their eating behaviors using Restraint, Disinhibition and Hunger eating factor categories and sub-categories. The eating behavior data were analyzed for associations with body mass index and body fat percentage, and comparisons across body mass index and body fat percentage categories (< vs. ≥25 kg/m²; < vs. ≥30%, respectively). Women had a mean (standard deviation) body mass index of 23.4 (3.5) kg/m², and body fat percentage of 30.5 (7.6)%. Disinhibition was positively associated with both body mass index (p < 0.001) and body fat percentage (p < 0.001). Emotional Disinhibition was positively associated with body fat percentage (p < 0.028). Women with low Restraint and high Disinhibition had significantly higher body mass index and body fat percentage than women with high Restraint and low Disinhibition. Disinhibition seems likely to be an important contributor to obesity. Tailored intervention strategies focused on counteracting Disinhibition should be a key target area for managing weight/fat gain.