Objective
This study aimed to investigate the influence of body fatness on the associations of body composition and energy expenditure (EE) with energy intake (EI).
Methods
Data from 93 women (BMI = ...25.5 SD 4.2 kg/m2) recruited for two studies (Study 1, n = 48, BMI = 25.0‐34.9 kg/m2; Study 2, n = 45, BMI = 18.5‐24.9 kg/m2) were examined. Body composition, resting metabolic rate (RMR), and test meal EI were assessed during a laboratory probe day. Physical activity, total daily EE (TDEE), and self‐reported free‐living 24‐hour EI were collected during 7 days.
Results
In the whole sample, fat‐free mass (r = 0.45; P < 0.001), RMR (r = 0.41; P < 0.001), and TDEE (r = 0.39; P < 0.001), but not fat mass (r = 0.17; P = 0.11), were positively associated with free‐living 24‐hour EI. Body fat percentage moderated the associations of RMR (β = −1.88; P = 0.02) and TDEE (β = −1.91; P = 0.03) with mean free‐living 24‐hour EI. Fat mass was negatively associated with test meal EI only in the leaner group (r = −0.43; P = 0.004), and a weak nonlinear association was observed in the whole sample (r2 = 0.092; P = 0.04).
Conclusions
Body fat percentage appears to moderate the associations between EE and daily EI. Furthermore, the negative association between fat mass and test meal EI observed in leaner individuals was absent in those with higher body fatness. Therefore, higher levels of body fatness may weaken the coupling between EE and EI.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract Hunger is one of the main reasons given by people experiencing problems in managing their weight. Identifying the types and properties of foods that enhance satiety may help consumers ...improve appetite control and weight management. However the attributes of foods associated with their perceived satiety value have been largely unexamined. The current research examined a range of objective and subjective attributes of foods and sought to map them onto ratings of their perceived satiety value. Participants (n = 1127) rated 100 individual food images, through online surveys, based on subjective (e.g. perceived energy content, control over eating, healthiness, palatability) and objective (e.g. actual energy content, macronutrient composition, cost/kcal) attributes. Perceived satiety value was quantified from ratings of how filling each food was judged to be. Results showed that when controlling for perceived total energy content, perceived satiety value was associated with lower energy density (r = −.74), lower %fat (r = −.47), higher %protein (r = .31) and higher cost (r = .48). In terms of subjective attributes, perceived satiety value was associated with greater healthiness (r = .90), weight management (r = .91), frequency of consumption (r = .58) and greater control over eating (r = .76). Linear regression models indicated that the objective attributes of energy density, %fat, fibre content, %carbohydrate and cost (R2 = .69) and the subjective attribute of utility for weight management and frequency of consumption (R2 = .83) accounted for the most variance in the perceived satiety value of food. These findings may help towards a ‘satiety map’ of the diet with implications for public health promotion and the development of satiety enhancing foods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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.
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.
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.
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.
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.
ISRCTN Registry ISRCTN88405328; https://www.isrctn.com/ISRCTN88405328.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
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.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Objective
Weight regain prevention is a critical public health challenge. Digital behaviour change interventions provide a scalable platform for applying and testing behaviour change theories in this ...challenging context. This study's goal was to analyse reciprocal effects between psychosocial variables (i.e., needs satisfaction, eating regulation, self‐efficacy) and weight over 12 months using data from a large sample of participants engaged in a weight regain prevention trial.
Methods
The NoHoW study is a three‐centre, large‐scale weight regain prevention trial. Adults who lost >5% of their weight in the past year (N = 1627, 68.7% female, 44.10 ± 11.86 years, 84.47 ± 17.03 kg) participated in a 12‐month' digital behaviour change‐based intervention. Weight and validated measures of basic psychological needs satisfaction, eating regulation and self‐efficacy were collected at baseline, six‐ and 12 months. Correlational, latent growth models and cross‐lagged analysis were used to identify potential reciprocal effects.
Results
Baseline higher scores of needs satisfaction and self‐efficacy were associated with six‐ and 12‐month' weight loss. Baseline weight was linked to all psychosocial variables at six months, and six‐months weight was associated with needs satisfaction and self‐efficacy at 12 months. During the 12 months, increases in eating regulation, needs satisfaction and self‐efficacy were associated with weight loss over the same period, and reciprocal effects were observed between the variables, suggesting the existence of Weight Management Cycles.
Conclusions
While further studies are needed, during long‐term weight regain prevention, weight decrease, needs satisfaction and self‐efficacy may lead to Weight Management Cycles, which, if recurrent, may provide sustained prevention of weight regain.
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DOBA, FSPLJ, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
The aim of this study was to compare self-reported total energy intake (TEI) collected using an online multiple-pass 24-h dietary recall tool (Intake24) with total energy expenditure (TEE) estimated ...from Fitbit Charge 2-improved algorithms in adults from the NoHoW trial (12-mo weight maintenance after free-living weight loss).
Bland-Altman plots were used to assess the level of agreement between TEI and TEE at baseline and after 12 mo. The ratio of TEI to TEE was also calculated.
Data from 1323 participants (71% female) was included in the analysis (mean ± SD: age 45 ± 12 y, body mass index 29.7 ± 5.4 kg/m
, initial weight loss 11.5 ± 6.5 kg). The TEI was lower than TEE on average by 33%, with limits of agreement ranging from -91% to +25%. Men, younger individuals, those with higher body mass index, those with the greater weight loss before enrollment, and those who gained weight during the study underestimated to a greater extent.
These findings contribute to the ongoing research examining the validity of technology-based dietary assessment tools.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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