Can eating behaviour traits be explained by underlying, latent factors? An exploratory and confirmatory factor analysis.

Eating Behaviour Traits (EBTs) are psychological constructs developed to explain patterns of eating behaviour, including factors that motivate people to (over or under) eat. There is a need to align and clarify their unique contributions and harmonise the understanding they offer for human eating behaviour. Therefore, the current study examined whether 18 commonly cited EBTs could be explained by underlying, latent factors (domains of eating behaviour). An exploratory factor analysis (EFA) was used to identify latent factors, and these factors were validated using a confirmatory factor analysis (CFA). 1279 participants including the general public and members of a weight management programme were included in the analysis (957 females, 317 males, 3 others, 2 prefer not to say), with a mean age of 54 years (median = 57 years, SD = 12.03) and a mean BMI of 31.93 kg/m2 (median = 30.86, SD = 6.00). The participants completed 8 questionnaires which included 18 commonly cited EBTs and the dataset was split at random with a 70/30 ratio to conduct the EFA (n = 893) and CFA (n = 383). The results supported a four-factor model which indicated that EBTs can be organised into four domains: reactive, restricted, emotional, and homeostatic eating. The four-factor model also significantly predicted self-reported BMI and weight change. Future research should test whether this factor structure is replicated in more diverse populations, and including other EBTs, to advance these domains of eating as a unifying framework for studying individual differences in human eating behaviour.

Are motivational and self-regulation factors associated with 12 months' weight regain prevention in the NoHoW study? An analysis of European adults.

PURPOSE: Preventing weight regain can only be achieved by sustained changes in energy balance-related behaviors that are associated with weight, such as diet and physical activity. Changes in motivation and self-regulatory skills can support long-term behavioral changes in the context of weight loss maintenance. We propose that experiencing a supportive climate care is associated with enhanced satisfaction of basic psychological needs, intrinsic goals, and autonomous motivation. These factors are expected to be associate with the utilization of self-regulation skills, leading to more sustained behavior changes and ultimately preventing weight regain. This hypothesis was tested in this ancillary analysis of the NoHoW trial, where the study arms were pooled and followed for 12 months. METHODS: The NoHoW was a three-center, large-scale weight regain prevention full factorial trial. In this longitudinal study, data were collected in adults who lost > 5% weight in the past year (N = 870, complete data only, 68.7% female, 44.10 ± 11.86 years, 84.47 ± 17.03 kg) during their participation in a 12-month digital behavior change intervention. Weight and validated measures of motivational- and self-regulatory skills-related variables were collected at baseline, six- and 12 months. Change variables were used in Mplus' path analytical models informed by NoHoW's logic model. RESULTS: The bivariate correlations confirmed key mediators' potential effect on weight outcomes in the expected causal direction. The primary analysis showed that a quarter of the variance (r2 = 23.5%) of weight regain prevention was achieved via the mechanisms of action predicted in the logic model. Specifically, our results show that supportive climate care is associated with needs satisfaction and intrinsic goal content leading to better weight regain prevention via improvements in self-regulatory skills and exercise-controlled motivation. The secondary analysis showed that more mechanisms of action are significant in participants who regained or maintained their weight. CONCLUSIONS: These results contribute to a better understanding of the mechanisms of action leading to behavior change in weight regain prevention. The most successful participants used only a few intrinsic motivation-related mechanisms of action, suggesting that habits may have been learned. While developing a digital behavior change intervention, researchers and practitioners should consider creating supportive climate care to improve needs satisfaction and intrinsic goal contents. TRIAL REGISTRATION: ISRCTN, ISRCTN88405328 , registered 12/22/2016.

A neurocognitive perspective on the relationship between exercise and reward: Implications for weight management and drug addiction.

The impact of exercise on food reward is increasingly being discussed as an interplay between executive function (EF), homeostasis and mechanisms promoting or undermining intentional behaviour change. Integrating current knowledge of neurocognitive processes encompassing cognitive and affective networks within an energy balance framework will provide a more comprehensive account. Reward circuitry affected by recreational drugs and food overlap. Therefore the underlying processes explaining changes in drug-taking behaviour may offer new insights into how exercise affects the reward value of recreational drugs and food. EF is important for successful self-regulation, and training EF may boost inhibitory control in relation to food- and drug-related reward. Preclinical and clinical observations suggest that reward-seeking can transfer within and between categories of reward. This may have clinical implications beyond exercise improving metabolic health in people with obesity to understanding therapeutic responses to exercise in people with neurocognitive deficits in non-food reward-based decision making such as drug dependence.

Exploratory analysis of reflective, reactive, and homeostatic eating behaviour traits on weight change during the 18-month NoHoW weight maintenance trial.

Behaviour change interventions for weight management have found varied effect sizes and frequent weight re-gain after weight loss. There is interest in exploring whether differences in eating behaviour can be used to develop tailored weight management programs. This secondary analysis of an 18-month weight maintenance randomised controlled trial (RCT) aimed to investigate the association between individual variability in weight maintenance success and change in eating behaviour traits (EBT). Data was analysed from the NoHoW trial (Scott et al., 2019), which was designed to measure processes of change after weight loss of ≥5% body weight in the previous year. The sample included 1627 participants (mean age = 44.0 years, SD = 11.9, mean body mass index (BMI) = 29.7 kg/m2, SD = 5.4, gender = 68.7% women/31.3% men). Measurements of weight (kg) and 7 EBTs belonging to domains of reflective, reactive, or homeostatic eating were taken at 4 time points up to 18-months. Increases in measures of 'reactive eating' (binge eating, p < .001), decreases in 'reflective eating' (restraint, p < .001) and changes in 'homeostatic eating' (unlimited permission to eat, p < .001 and reliance on hunger and satiety cues, p < .05) were significantly and independently associated with concomitant weight change. Differences in EBT change were observed between participants who lost, maintained, or re-gained weight for all EBTs (p < .001) except for one subscale of intuitive eating (eating for physical reasons, p = .715). Participants who lost weight (n = 322) exhibited lower levels of reactive eating and higher levels of reflective eating than participants who re-gained weight (n = 668). EBT domains can identify individuals who need greater support to progress in weight management interventions. Increasing reflective eating and reducing reactive eating may enhance weight management success.

Fat-Free Mass and Total Daily Energy Expenditure Estimated Using Doubly Labeled Water Predict Energy Intake in a Large Sample of Community-Dwelling Older Adults.

BACKGROUND: Up to 30% of community-based older adults report reduced appetite and energy intake (EI), but previous research examining the underlying physiological mechanisms has focused on the mechanisms that suppress eating rather than the hunger drive and EI. OBJECTIVES: We examined the associations between fat-free mass (FFM), physical activity (PA), total daily energy expenditure (TDEE), and self-reported EI in older adults. METHODS: The present study was a secondary analysis of the Interactive Diet and Activity Tracking in AARP study. Body composition (deuterium dilution), PA (accelerometry), and TDEE (doubly labeled water) were measured in 590 older adults (age, 63.1 ± 5.9 years; BMI, 28.1 ± 4.9 kg/m2). The total daily EI was estimated from a single 24-hour dietary recall (EIsingle; ±1 month of PA and TDEE measurement) and the mean of up to 6 recalls over a 12-month period (EImean), with misreporters classified using the 95% CIs between the EImean and TDEE. RESULTS: After controlling for age and sex, linear regression demonstrated that FFM and TDEE predicted EI when estimated from a single 24-hour dietary recall (P < 0.05), from the mean of up to 6 dietary recalls (P < 0.05), and after the removal of those classified as underreporters (P < 0.001). Age moderated the associations between FFM and EIsingle (P < 0.001), FFM and EImean (P < 0.001), and TDEE with EIsingle (P = 0.016), with associations becoming weaker across age quintiles. CONCLUSIONS: These data suggest that the total daily EI is proportional to the FFM and TDEE, but not fat mass, in older adults. These associations may reflect an underling drive to eat that influences the daily food intake. While the associations between FFM or TDEE and EI existed across all age quintiles, these associations weakened with increasing age.

Fat-Free Mass and Total Daily Energy Expenditure Estimated Using Doubly Labeled Water Predict Energy Intake in a Large Sample of Community-Dwelling Older Adults.

BACKGROUND: Up to 30% of community-based older adults report reduced appetite and energy intake (EI), but previous research examining the underlying physiological mechanisms has focused on the mechanisms that suppress eating rather than the hunger drive and EI. OBJECTIVES: We examined the associations between fat-free mass (FFM), physical activity (PA), total daily energy expenditure (TDEE), and self-reported EI in older adults. METHODS: The present study was a secondary analysis of the Interactive Diet and Activity Tracking in AARP study. Body composition (deuterium dilution), PA (accelerometry), and TDEE (doubly labeled water) were measured in 590 older adults (age, 63.1 ± 5.9 years; BMI, 28.1 ± 4.9 kg/m2). The total daily EI was estimated from a single 24-hour dietary recall (EIsingle; ±1 month of PA and TDEE measurement) and the mean of up to 6 recalls over a 12-month period (EImean), with misreporters classified using the 95% CIs between the EImean and TDEE. RESULTS: After controlling for age and sex, linear regression demonstrated that FFM and TDEE predicted EI when estimated from a single 24-hour dietary recall (P < 0.05), from the mean of up to 6 dietary recalls (P < 0.05), and after the removal of those classified as underreporters (P < 0.001). Age moderated the associations between FFM and EIsingle (P < 0.001), FFM and EImean (P < 0.001), and TDEE with EIsingle (P = 0.016), with associations becoming weaker across age quintiles. CONCLUSIONS: These data suggest that the total daily EI is proportional to the FFM and TDEE, but not fat mass, in older adults. These associations may reflect an underling drive to eat that influences the daily food intake. While the associations between FFM or TDEE and EI existed across all age quintiles, these associations weakened with increasing age.

Evaluation of the Immediate Effects of Web-Based Intervention Modules for Goals, Planning, and Coping Planning on Physical Activity: Secondary Analysis of a Randomized Controlled Trial on Weight Loss Maintenance.

BACKGROUND: The use of digital interventions can be accurately monitored via log files. However, monitoring engagement with intervention goals or enactment of the actual behaviors targeted by the intervention is more difficult and is usually evaluated based on pre-post measurements in a controlled trial. OBJECTIVE: The objective of this paper is to evaluate if engaging with 2 digital intervention modules focusing on (1) physical activity goals and action plans and (2) coping with barriers has immediate effects on the actual physical activity behavior. METHODS: The NoHoW Toolkit (TK), a digital intervention developed to support long-term weight loss maintenance, was evaluated in a 2 x 2 factorial randomized controlled trial. The TK contained various modules based on behavioral self-regulation and motivation theories, as well as contextual emotion regulation approaches, and involved continuous tracking of weight and physical activity through connected commercial devices (Fitbit Aria and Charge 2). Of the 4 trial arms, 2 had access to 2 modules directly targeting physical activity: a module for goal setting and action planning (Goal) and a module for identifying barriers and coping planning (Barriers). Module visits and completion were determined based on TK log files and time spent in the module web page. Seven physical activity metrics (steps; activity; energy expenditure; fairly active, very active and total active minutes; and distance) were compared before and after visiting and completing the modules to examine whether the modules had immediate or sustained effects on physical activity. Immediate effect was determined based on 7-day windows before and after the visit, and sustained effects were evaluated for 1 to 8 weeks after module completion. RESULTS: Out of the 811 participants, 498 (61.4%) visited the Goal module and 406 (50.1%) visited the Barriers module. The Barriers module had an immediate effect on very active and total active minutes (very active minutes: before median 24.2, IQR 10.4-43.0 vs after median 24.9, IQR 10.0-46.3; P=.047; total active minutes: before median 45.1, IQR 22.9-74.9 vs after median 46.9, IQR 22.4-78.4; P=.03). The differences were larger when only completed Barriers modules were considered. The Barriers module completion was also associated with sustained effects in fairly active and total active minutes for most of the 8 weeks following module completion and for 3 weeks in very active minutes. CONCLUSIONS: The Barriers module had small, significant, immediate, and sustained effects on active minutes measured by a wrist-worn activity tracker. Future interventions should pay attention to assessing barriers and planning coping mechanisms to overcome them. TRIAL REGISTRATION: ISRCTN Registry ISRCTN88405328; https://www.isrctn.com/ISRCTN88405328.

Users' Experiences With the NoHoW Web-Based Toolkit With Weight and Activity Tracking in Weight Loss Maintenance: Long-term Randomized Controlled Trial.

BACKGROUND: Digital behavior change interventions (DBCIs) offer a promising channel for providing health promotion services. However, user experience largely determines whether they are used, which is a precondition for effectiveness. OBJECTIVE: The primary aim of this study is to evaluate user experiences with the NoHoW Toolkit (TK)-a DBCI that targets weight loss maintenance-over a 12-month period by using a mixed methods approach and to identify the main strengths and weaknesses of the TK and the external factors affecting its adoption. The secondary aim is to objectively describe the measured use of the TK and its association with user experience. METHODS: An 18-month, 2×2 factorial randomized controlled trial was conducted. The trial included 3 intervention arms receiving an 18-week active intervention and a control arm. The user experience of the TK was assessed quantitatively through electronic questionnaires after 1, 3, 6, and 12 months of use. The questionnaires also included open-ended items that were thematically analyzed. Focus group interviews were conducted after 6 months of use and thematically analyzed to gain deeper insight into the user experience. Log files of the TK were used to evaluate the number of visits to the TK, the total duration of time spent in the TK, and information on intervention completion. RESULTS: The usability level of the TK was rated as satisfactory. User acceptance was rated as modest; this declined during the trial in all the arms, as did the objectively measured use of the TK. The most appreciated features were weekly emails, graphs, goal setting, and interactive exercises. The following 4 themes were identified in the qualitative data: engagement with features, decline in use, external factors affecting user experience, and suggestions for improvements. CONCLUSIONS: The long-term user experience of the TK highlighted the need to optimize the technical functioning, appearance, and content of the DBCI before and during the trial, similar to how a commercial app would be optimized. In a trial setting, the users should be made aware of how to use the intervention and what its requirements are, especially when there is more intensive intervention content. TRIAL REGISTRATION: ISRCTN Registry ISRCTN88405328; https://www.isrctn.com/ISRCTN88405328. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-029425.

Identification of psychological correlates of dietary misreporting under laboratory and free-living environments.

Errors inherent in self-reported measures of energy intake (EI) are substantial and well documented, but correlates of misreporting remain unclear. Therefore, potential predictors of misreporting were examined. In Study One, fifty-nine individuals (BMI = 26·1 (sd 3·8) kg/m2, age = 42·7 (sd 13·6) years, females = 29) completed a 14-d stay in a residential feeding behaviour suite where eating behaviour was continuously monitored. In Study Two, 182 individuals (BMI = 25·7 (sd 3·9) kg/m2, age = 42·4 (sd 12·2) years, females = 96) completed two consecutive days in a residential feeding suite and five consecutive days at home. Misreporting was directly quantified by comparing covertly measured laboratory weighed intakes (LWI) with self-reported EI (weighed dietary record (WDR), 24-h recall, 7-d diet history, FFQ). Personal (age, sex and %body fat) and psychological traits (personality, social desirability, body image, intelligence quotient and eating behaviour) were used as predictors of misreporting. In Study One, those with lower psychoticism (P = 0·009), openness to experience (P = 0·006) and higher agreeableness (P = 0·038) reduced EI on days participants knew EI was being measured to a greater extent than on covert days. Isolated associations existed between personality traits (psychoticism and openness to experience), eating behaviour (emotional eating) and differences between the LWI and self-reported EI, but these were inconsistent between dietary assessment techniques and typically became non-significant after accounting for multiplicity of comparisons. In Study Two, sex was associated with differences between LWI and the WDR (P = 0·009), 24-h recall (P = 0·002) and diet history (P = 0·050) in the laboratory, but not home environment. Personal and psychological correlates of misreporting identified displayed no clear pattern across studies or dietary assessment techniques and had little utility in predicting misreporting.

A Theory- and Evidence-Based Digital Intervention Tool for Weight Loss Maintenance (NoHoW Toolkit): Systematic Development and Refinement Study.

BACKGROUND: Many weight loss programs show short-term effectiveness, but subsequent weight loss maintenance is difficult to achieve. Digital technologies offer a promising means of delivering behavior change approaches at low costs and on a wide scale. The Navigating to a Healthy Weight (NoHoW) project, which was funded by the European Union's Horizon 2020 research and innovation program, aimed to develop, test, and evaluate a digital toolkit designed to promote successful long-term weight management. The toolkit was tested in an 18-month, large-scale, international, 2×2 factorial (motivation and self-regulation vs emotion regulation) randomized controlled trial that was conducted on adults with overweight or obesity who lost ≥5% of their body weight in the preceding 12 months before enrollment into the intervention. OBJECTIVE: This paper aims to describe the development of the NoHoW Toolkit, focusing on the logic models, content, and specifications, as well as the results from user testing. METHODS: The toolkit was developed by using a systematic approach, which included the development of the theory-based logic models, the selection of behavior change techniques, the translation of these techniques into a web-based app (NoHoW Toolkit components), technical development, and the user evaluation and refinement of the toolkit. RESULTS: The toolkit included a set of web-based tools and inputs from digital tracking devices (smart scales and activity trackers) and modules that targeted weight, physical activity, and dietary behaviors. The final toolkit comprised 34 sessions that were distributed through 15 modules and provided active content over a 4-month period. The motivation and self-regulation arm consisted of 8 modules (17 sessions), the emotion regulation arm was presented with 7 modules (17 sessions), and the combined arm received the full toolkit (15 modules; 34 sessions). The sessions included a range of implementations, such as videos, testimonies, and questionnaires. Furthermore, the toolkit contained 5 specific data tiles for monitoring weight, steps, healthy eating, mood, and sleep. CONCLUSIONS: A systematic approach to the development of digital solutions based on theory, evidence, and user testing may significantly contribute to the advancement of the science of behavior change and improve current solutions for sustained weight management. Testing the toolkit by using a 2×2 design provided a unique opportunity to examine the effect of motivation and self-regulation and emotion regulation separately, as well as the effect of their interaction in weight loss maintenance.

Development and cross-cultural validation of the Goal Content for Weight Maintenance Scale (GCWMS).

PURPOSE: Long-term weight management requires sustained engagement with energy-balance-related behaviours. According to self-determination theory, behaviour goals can support or undermine motivation depending on the quality of their content (i.e., extrinsic and intrinsic motivation). This study aimed to develop and validate the goal content for weight loss maintenance scale (GCWMS). METHODS: The GCWMS was administered to 1511 participants who had achieved clinically significant weight losses and were taking part in a large weight loss maintenance study: the NoHoW Trial (ISRCTN88405328). The scale derived from two well-established questionnaires regarding exercise goals. Construct validity was examined for 4 theory-driven domains: Health Management, Challenge, Image, and Social Recognition. Split-sample confirmatory factor analysis was conducted to test the factorial validity and multi-group measurement invariance (configural, metric, scalar, and residual invariance). The reliability estimates were also assessed, and discriminant validity was evaluated using 2 conceptually related questionnaires. RESULTS: The first analysis showed a poor fit of the original factorial structure. Subsequent investigation with a new specified model indicated close fit to the data after removal of 3 items χ2(58) = 599.982; p < .001; χ2/df = 10.345; CFI = 0.940; GFI = 0.941; SRMR = 0.063; RMSEA = 0.079 (LL = 0.073; UL = .084). Good internal consistency was achieved in all subscales (α > .775), convergent and divergent validity were verified through associations with other theoretical related constructs. Findings from multi-group invariance test demonstrated that the specified model of GCWMS achieved full measurement invariance for gender but did not support residual invariance across countries. CONCLUSION: Findings support the hypothesised four-dimension structure of the GCWMS, confirming reliability and multi-group invariance in factor structure. Analysis also supports valid group means comparisons on latent factors at gender and at cross-cultural level. Ways to improve the quality of the scale are discussed. LEVEL OF EVIDENCE: Level V, cross-sectional descriptive.

Consistent sleep onset and maintenance of body weight after weight loss: An analysis of data from the NoHoW trial.

BACKGROUND: Several studies have suggested that reduced sleep duration and quality are associated with an increased risk of obesity and related metabolic disorders, but the role of sleep in long-term weight loss maintenance (WLM) has not been thoroughly explored using prospective data. METHODS AND FINDINGS: The present study is an ancillary study based on data collected on participants from the Navigating to a Healthy Weight (NoHoW) trial, for which the aim was to test the efficacy of an evidence-based digital toolkit, targeting self-regulation, motivation, and emotion regulation, on WLM among 1,627 British, Danish, and Portuguese adults. Before enrolment, participants had achieved a weight loss of ≥5% and had a BMI of ≥25 kg/m2 prior to losing weight. Participants were enrolled between March 2017 and March 2018 and followed during the subsequent 12-month period for change in weight (primary trial outcome), body composition, metabolic markers, diet, physical activity, sleep, and psychological mediators/moderators of WLM (secondary trial outcomes). For the present study, a total of 967 NoHoW participants were included, of which 69.6% were women, the mean age was 45.8 years (SD 11.5), the mean baseline BMI was 29.5 kg/m2 (SD 5.1), and the mean weight loss prior to baseline assessments was 11.4 kg (SD 6.4). Objectively measured sleep was collected using the Fitbit Charge 2 (FC2), from which sleep duration, sleep duration variability, sleep onset, and sleep onset variability were assessed across 14 days close to baseline examinations. The primary outcomes were 12-month changes in body weight (BW) and body fat percentage (BF%). The secondary outcomes were 12-month changes in obesity-related metabolic markers (blood pressure, low- and high-density lipoproteins [LDL and HDL], triglycerides [TGs], and glycated haemoglobin [HbA1c]). Analysis of covariance and multivariate linear regressions were conducted with sleep-related variables as explanatory and subsequent changes in BW, BF%, and metabolic markers as response variables. We found no evidence that sleep duration, sleep duration variability, or sleep onset were associated with 12-month weight regain or change in BF%. A higher between-day variability in sleep onset, assessed using the standard deviation across all nights recorded, was associated with weight regain (0.55 kg per hour [95% CI 0.10 to 0.99]; P = 0.016) and an increase in BF% (0.41% per hour [95% CI 0.04 to 0.78]; P = 0.031). Analyses of the secondary outcomes showed that a higher between-day variability in sleep duration was associated with an increase in HbA1c (0.02% per hour [95% CI 0.00 to 0.05]; P = 0.045). Participants with a sleep onset between 19:00 and 22:00 had the greatest reduction in diastolic blood pressure (DBP) (P = 0.02) but also the most pronounced increase in TGs (P = 0.03). The main limitation of this study is the observational design. Hence, the observed associations do not necessarily reflect causal effects. CONCLUSION: Our results suggest that maintaining a consistent sleep onset is associated with improved WLM and body composition. Sleep onset and variability in sleep duration may be associated with subsequent change in different obesity-related metabolic markers, but due to multiple-testing, the secondary exploratory outcomes should be interpreted cautiously. TRIAL REGISTRATION: The trial was registered with the ISRCTN registry (ISRCTN88405328).

Biological and psychological mediators of the relationships between fat mass, fat-free mass and energy intake.

BACKGROUND: While recent studies in humans indicate that fat-free mass (FFM) is closely associated with energy intake (EI) when in energy balance, associations between fat mass (FM) and EI are inconsistent. OBJECTIVES: The present study used a cross-sectional design to examine the indirect and direct effects of FFM, FM and resting metabolic rate (RMR) on EI in individuals at or close to energy balance. METHODS: Data for 242 individuals (114 males; 128 females; BMI = 25.7 ± 4.9 kg/m2) were collated from the non-intervention baseline conditions of five studies employing common measures of body composition (air-displacement plethysmography), RMR (indirect calorimetry) and psychometric measures of eating behaviours (Dutch Eating Behaviour Questionnaire). Daily EI (weighed dietary records) and energy expenditure (flex heart rate) were measured for 6-7 days. Sub-analyses were conducted in 71 individuals who had additional measures of body composition (dual-energy X-ray absorptiometry) and fasting glucose, insulin and leptin. RESULTS: After adjusting for age, sex and study, linear regression and mediation analyses indicated that the effect of FFM on EI was mediated by RMR (P < 0.05). FM also independently predicted EI, with path analysis indicating a positive indirect association (mediated by RMR; P < 0.05), and a stronger direct negative association (P < 0.05). Leptin, insulin and insulin resistance failed to predict EI, but cognitive restraint was a determinant of EI and partially mediated the association between FM and EI (P < 0.05). CONCLUSIONS: While the association between FFM and EI was mediated by RMR, FM influenced EI via two separate and opposing pathways; an indirect 'excitatory' effect (again, mediated by RMR), and a stronger direct 'inhibitory' effect. Psychological factors such as cognitive restraint remain robust predictors of EI when considered alongside physiological determinants of EI, and indeed, have the potential to play a mediating role in the overall expression of EI.

Activity energy expenditure is an independent predictor of energy intake in humans.

BACKGROUND: There is evidence that the energetic demand of metabolically active tissue is associated with day-to-day food intake (EI). However, the extent to which behavioural components of total daily energy expenditure (EE) such as activity energy expenditure (AEE) are also associated with EI is unknown. Therefore, the present study examined the cross-sectional associations between body composition, resting metabolic rate (RMR), AEE and EI. METHODS: Data for 242 individuals (114 males; 128 females; BMI = 25.7 ± 4.9 kg/m2) were collated from the baseline control conditions of five studies employing common measures of body composition (air displacement plethysmography) and RMR (indirect calorimetry). Daily EI (weighed-dietary records) and EE (FLEX heart rate) were measured over 6-7 days, and AEE was calculated as total daily EE minus RMR. RESULTS: Linear regression indicated that RMR (ß = 0.39; P < 0.001), fat mass (ß = -0.26; P < 0.001) and AEE (ß = 0.18; P = 0.002) were independent predictors of mean daily EI, with AEE adding ≈3% of variance to the model after controlling for age, sex and study (F(10, 231) = 18.532, P < 0.001; R2 = 0.445). Path analyses indicated that the effect of FFM on mean daily EI was mediated by RMR (P < 0.05), while direct (ß = 0.19; P < 0.001) and indirect (ß = 0.20; P = 0.001) associations between AEE and mean daily EI were observed. CONCLUSIONS: When physical activity was allowed to vary under free-living conditions, AEE was associated with mean daily EI independently of other biological determinants of EI arising from body composition and RMR. These data suggest that EE per se exerts influence over daily food intake, with both metabolic (RMR) and behavioral (AEE) components of total daily EE potentially influencing EI via their contribution to daily energy requirements.

Women with a low-satiety phenotype show impaired appetite control and greater resistance to weight loss.

This trial compared weight loss outcomes over 14 weeks in women showing low- or high-satiety responsiveness (low- or high-satiety phenotype (LSP, HSP)) measured by a standardised protocol. Food preferences and energy intake (EI) after low and high energy-density (LED, HED) meals were also assessed. Ninety-six women (n 52 analysed; 41·24 (SD 12·54) years; 34·02 (sd 3·58) kg/m2) engaged in one of two weight loss programmes underwent LED and HED laboratory test days during weeks 3 and 12. Preferences for LED and HED food (Leeds Food Preference Questionnaire) and ad libitum evening meal and snack EI were assessed in response to equienergetic LED and HED breakfasts and lunches. Weekly questionnaires assessed control over eating and ease of adherence to the programme. Satiety quotients based on subjective fullness ratings post LED and HED breakfasts determined LSP (n 26) and HSP (n 26) by tertile splits. Results showed that the LSP lost less weight and had smaller reductions in waist circumference compared with HSP. The LSP showed greater preferences for HED foods, and under HED conditions, consumed more snacks (kJ) compared with HSP. Snack EI did not differ under LED conditions. LSP reported less control over eating and reported more difficulty with programme adherence. In conclusion, low-satiety responsiveness is detrimental for weight loss. LED meals can improve self-regulation of EI in the LSP, which may be beneficial for longer-term weight control.

Attribution of weight regain to emotional reasons amongst European adults with overweight and obesity who regained weight following a weight loss attempt.

PURPOSE: Despite the wide availability of effective weight loss programmes, maintenance of weight loss remains challenging. Difficulties in emotion regulation are associated with binge eating and may represent one barrier to long-term intervention effectiveness in obesity. The purpose of this study was to determine the relationship between emotion regulation difficulties and the extent of weight regain in a sample of adults who had lost, and then regained, weight, and to examine the characteristics associated with emotional difficulties. METHODS: 2000 adults from three European countries (UK, Portugal, and Denmark) completed an online survey assessing self-reported weight loss and regain following their most recent weight loss attempt. They also completed a binge eating disorder screening questionnaire and, if they had regained weight, were asked if they attributed it to any emotional factors (a proxy for emotion regulation difficulties). Spearman's correlations and logistic regression were used to assess the associations between emotion regulation, weight regain, and strategy use. RESULTS: Emotion regulation difficulties were associated with greater weight regain (N = 1594 who lost and regained weight). Attribution to emotional reasons was associated with younger age, female gender, loss of control and binge eating, lower perceptions of success at maintenance, using more dietary and self-regulatory strategies in weight loss, and fewer dietary strategies in maintenance. CONCLUSIONS: Weight-related emotion regulation difficulties are common amongst regainers and are associated with regaining more weight. Affected individuals are already making frequent use of behavioural strategies during weight loss, but do not apply these consistently beyond active attempts. Simply encouraging the use of more numerous strategies, without concurrently teaching emotion regulation skills, may not be an effective means to improving weight outcomes in this group. LEVEL OF EVIDENCE: Level V, descriptive (cross-sectional) study.

A Low Energy-Dense Diet in the Context of a Weight-Management Program Affects Appetite Control in Overweight and Obese Women.

Background: Low energy-dense (LED) foods reduce energy intake (EI); whether this effect is sustained over time and during weight loss is unknown. Objective: This trial examined the effects of LED compared with high energy-dense (HED) meals on appetite, EI, and control over eating in the laboratory and during a weight-management program that encourages unrestricted intake of LED foods [Slimming World, UK (SW)] compared with a self-led Standard Care program [NHS weight-loss plan (SC)]. Methods: Overweight and obese women [n = 96; mean ± SD age: 41.03 ± 12.61 y; mean ± SD body mass index (in kg/m2): 34.00 ± 3.61] were recruited from the SW or SC programs. Primary outcomes included appetite, food preferences (liking and wanting for LED and HED foods), cravings, and evening meal EI (LED, HED) in response to calorie-matched LED (≤0.8 kcal/g) and HED (≥2.5 kcal/g) breakfast and lunch meals. Probe-day tests were conducted at weeks 3 and 4 and repeated at weeks 12 and 13 in a within-day crossover design. Secondary outcomes, including body weight and program experience, were measured from weeks 1 to 14 in a parallel-group design. Dietary compliance was monitored with the use of weighed food diaries at weeks 3 and 12. Results: Intention-to-treat (ITT) and completers analyses showed that the SW group lost more weight than the SC group [ITT: -5.9% (95% CI: -4.7%, -7.2%) compared with -3.5% (-2.3%, -4.8%), P < 0.05; completers: -6.2% (-4.8%, -7.6%) compared with 3.9% (-2.5%, -5.2%), P < 0.05]. The SW group reported greater control over eating and more motivation to continue the program compared with the SC group. LED meals increased sensations of fullness and reduced hunger on probe days (P < 0.001). Total-day EI was 1057 ± 73 kcal less (95% CI: 912, 1203 kcal; 36%) under LED compared with HED conditions (P < .001). Liking for LED and HED foods and wanting for HED foods were lower before lunch under LED compared with HED conditions, and liking decreased to a greater extent after the LED lunch. The SW group reported fewer cravings under LED compared with HED conditions (P < 0.05). On probe days, appetite and EI outcomes did not differ between weeks 3 and 12 or between the SW and SC groups. Conclusion: LED meals improve appetite control in women attempting weight loss and the effect is sustainable. Consumption of LED meals likely contributed to weight loss in the SW program. This study was registered at clinicaltrials.gov as NCT02012426.

Compassionate Attention and Regulation of Eating Behaviour: A pilot study of a brief low-intensity intervention for binge eating.

A low-intensity 4-week intervention that included components of compassion, mindfulness, and acceptance was delivered to women diagnosed with binge eating disorder. Participants were randomly assigned to 1 of 2 conditions: intervention (n = 11) or waiting list control (n = 9). Participants in the intervention condition were invited to practise mindfulness, soothing rhythm breathing, and compassionate imagery practices with a focus on awareness and acceptance of emotional states and triggers to binge eating and engagement in helpful actions. Results revealed that, in the intervention group, there were significant reductions in eating psychopathology symptoms, binge eating symptoms, self-criticism, and indicators of psychological distress; there were significant increases in compassionate actions and body image-related psychological flexibility. Data suggest that developing compassion and acceptance competencies may improve eating behaviour and psychological well-being in individuals with binge eating disorder.

Weight outcomes audit in 1.3 million adults during their first 3 months' attendance in a commercial weight management programme.

BACKGROUND: Over sixty percent of adults in the UK are now overweight/obese. Weight management on a national scale requires behavioural and lifestyle solutions that are accessible to large numbers of people. Evidence suggests commercial weight management programmes help people manage their weight but there is little research examining those that pay to attend such programmes rather than being referred by primary care. The objective of this analysis was to evaluate the effectiveness of a UK commercial weight management programme in self-referred, fee-paying participants. METHODS: Electronic weekly weight records were collated for self-referred, fee-paying participants of Slimming World groups joining between January 2010 and April 2012. This analysis reports weight outcomes in 1,356,105 adult, non-pregnant participants during their first 3 months' attendance. Data were analysed by regression, ANOVA and for binomial outcomes, chi-squared tests using the R statistical program. RESULTS: Mean (SD) age was 42.3 (13.6) years, height 1.65 m (0.08) and start weight was 88.4 kg (18.8). Mean start BMI was 32.6 kg/m(2) (6.3 kg/m(2)) and 5 % of participants were men. Mean weight change of all participants was -3.9 kg (3.6), percent weight change -4.4 (3.8), and BMI change was -1.4 kg/m(2) (1.3). Mean attendance was 7.8 (4.3) sessions in their first 3 months. For participants attending at least 75 % of possible weekly sessions (n = 478,772), mean BMI change was -2.5 kg/m(2) (1.3), weight change -6.8 kg (3.7) and percent weight change -7.5 % (3.5). Weight loss was greater in men than women absolutely (-6.5 (5.3) kg vs -3.8 (3.4) kg) and as a percentage (5.7 % (4.4) vs 4.3 % (3.7)), respectively. All comparisons were significant (p < 0.001). Level of attendance and percent weight loss in the first week of attendance together accounted for 55 % of the variability in weight lost during the study period. CONCLUSIONS: A large-scale commercial lifestyle-based weight management programme had a significant impact on weight loss outcomes over 3 months. Higher levels of attendance led to levels of weight loss known to be associated with significant clinical benefits, which on this scale may have an impact on public health.

Measuring the difference between actual and reported food intakes in the context of energy balance under laboratory conditions.

To date, no study has directly and simultaneously measured the discrepancy between what people actually eat and what they report eating under observation in the context of energy balance (EB). The present study aimed to objectively measure the 'extent' and 'nature' of misreporting of dietary intakes under conditions in which EB and feeding behaviour were continuously monitored. For this purpose, a total of fifty-nine adults were recruited for 12 d, involving two 3 d overt phases and two 3 d covert phases of food intake measurement in a randomised cross-over design. Subjects had ad libitum access to a variety of familiar foods. Food intake was covertly measured using a feeding behaviour suite to establish actual energy and nutrient intakes. During the overt phases, subjects were instructed to self-report food intake using widely accepted methods. Misreporting comprised two separate and synchronous phenomena. Subjects decreased energy intake (EI) when asked to record their food intake (observation effect). The effect was significant in women ( - 8 %, P< 0·001) but not in men ( - 3 %, P< 0·277). The reported EI was 5 to 21 % lower (reporting effect) than the actual intake, depending on the reporting method used. Semi-quantitative techniques gave larger discrepancies. These discrepancies were identical in men and women and non-macronutrient specific. The 'observation' and 'reporting' effects combined to constitute total misreporting, which ranged from 10 to 25 %, depending on the intake measurement assessed. When studied in a laboratory environment and EB was closely monitored, subjects under-reported their food intake and decreased the actual intake when they were aware that their intake was being monitored.