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

ABSTRACT: 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).

SUBMITTER: Larsen SC

PROVIDER: S-EPMC7365417 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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

Larsen Sofus C SC Horgan Graham G Mikkelsen Marie-Louise K MK Palmeira Antonio L AL Scott Sarah S Duarte Cristiana C Santos Inês I Encantado Jorge J O'Driscoll Ruairi R Turicchi Jake J Michalowska Joanna J Stubbs R James RJ Heitmann Berit L BL

PLoS medicine 20200716 7

<h4>Background</h4>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.<h4>Methods and findings</h4>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 ...[more]

PMID: 32673309

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Project description:Several cross-sectional studies have shown hair cortisol concentration to be associated with adiposity, but the relationship between hair cortisol concentration and longitudinal changes in measures of adiposity are largely unknown. We included 786 adults from the NoHoW trial, who had achieved a successful weight loss of ≥5% and had a body mass index of ≥25 kg/m2 prior to losing weight. Hair cortisol concentration (pg/mg hair) was measured at baseline and after 12 months. Body weight and body fat percentage were measured at baseline, 6-month, 12-month and 18-month visits. Participants weighed themselves at home ≥2 weekly using a Wi-Fi scale for the 18-month study duration, from which body weight variability was estimated using linear and non-linear approaches. Regression models were conducted to examine log hair cortisol concentration and change in log hair cortisol concentration as predictors of changes in body weight, change in body fat percentage and body weight variability. After adjustment for lifestyle and demographic factors, no associations between baseline log hair cortisol concentration and outcome measures were observed. Similar results were seen when analysing the association between 12-month concurrent development in log hair cortisol concentration and outcomes. However, an initial 12-month increase in log hair cortisol concentration was associated with a higher subsequent body weight variability between month 12 and 18, based on deviations from a nonlinear trend (β: 0.02% per unit increase in log hair cortisol concentration [95% CI: 0.00, 0.04]; P=0.016). Our data suggest that an association between hair cortisol concentration and subsequent change in body weight or body fat percentage is absent or marginal, but that an increase in hair cortisol concentration during a 12-month weight loss maintenance effort may predict a slightly higher subsequent 6-months body weight variability.Clinical trial registrationISRCTN registry, identifier ISRCTN88405328.

Project description:IntroductionObesity and associated diseases place a severe burden on healthcare systems. Behavioural interventions for weight loss (WL) are successful in the short term but often result in weight regain over time. Self-regulation of eating and activity behaviours may significantly enhance weight loss maintenance (WLM) and may be effectively augmented by contextual behavioural approaches to emotion regulation. The NoHoW trial tests the efficacy of a theoretically informed, evidence-based digital toolkit using a mobile-enabled website, activity trackers and Wi-Fi scales for WLM aiming to target (1) self-regulation and motivation, and (2) emotion regulation in adults who achieved clinically significant (≥5%) WL in the previous 12 months (initial body mass index (BMI) ≥25 kg/m2).Methods and analysisThe study is an 18-month, 3-centre, 2×2 factorial single-blind, randomised controlled trial, which recruited 1627 participants achieving ≥5% WL between March 2017 and March 2018. Participants are randomly allocated to one of four arms: (1) self-monitoring only (self-weighing and activity tracker), (2) self-regulation and motivation, (3) emotion regulation or (4) combined self-regulation, motivation and emotion regulation. Participants attend four clinical investigation days at 0, 6, 12 and 18 months and are instructed to use the digital toolkit for 18 weeks during the first 6 months and at their discretion for the remaining 12 months. The primary outcome is change in weight (kg) at 12 months from baseline. Secondary outcomes are body composition (eg, bioimpedance analysis), health biomarkers (glycated haemoglobin, lipids, blood pressure, hair cortisol), dietary intake, physical activity, sleep, motivational, self-regulatory, emotion regulatory moderators/mediators of WLM, engagement, user experience, acceptability and cost-effectiveness of the interventions.Ethics and disseminationEthical approval was granted by Institutional Ethics Committees at the Universities of Leeds (17-0082; 27 February 2017), Lisbon (17/2016; 20 February 2017) and Capital Region of Denmark (H-16030495, 8 March 2017). Results will be published in scientific journals.Trial registration numberISRCTN88405328.

Project description:BackgroundMany 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.ObjectiveThis 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.MethodsThe 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.ResultsThe 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.ConclusionsA 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.

Project description:In this secondary analysis of the DiOGenes study, we investigated whether physical activity (PA) contributes to diet-induced weight loss and helps to reduce subsequent regain. We also studied the associations of PA with changes in cardiometabolic variables. Adults with overweight were included and followed an 8-week low-calorie diet (LCD). When successful (>8% weight loss), participants were randomized to different ad libitum diet groups and were advised to maintain their weight loss over the 6-month intervention period. Body weight (BW), body composition, cardiometabolic variables and subjectively-assessed PA were measured at baseline, at the end of weight loss and at the end of the intervention. BW was reduced by the LCD (from 99.8 ± 16.7 to 88.4 ± 14.9 kg; P < 0.001). This reduction was maintained during the weight maintenance period (89.2 ± 16.0 kg). Total PA (sum score of the three subscales of the Baecke questionnaire) increased during the weight loss period (from 8.16 ± 0.83 to 8.39 ± 0.78; P < 0.001) and this increase was subsequently maintained (8.42 ± 0.90). We found no evidence that baseline PA predicted weight loss. However, a higher level of baseline PA predicted a larger weight-loss-induced improvement in total cholesterol, triglycerides, glucose and CRP, and in post-prandial insulin sensitivity (Matsuda index). Subsequent weight and fat mass maintenance were predicted by the post-weight loss level of PA and associated with changes in PA during the weight maintenance phase. In conclusion, despite the fact that higher baseline levels of PA did not predict more weight loss during the LCD, nor that an increase in PA during the LCD was associated with more weight loss, higher PA levels were associated with more improvements in several cardiometabolic variables. The positive effect of higher PA on weight loss maintenance seems in contrast to randomized controlled trials that have not been able to confirm a positive effect of exercise training programmes on weight loss maintenance. This analysis supports the notion that higher self-imposed levels of PA may improve the cardiometabolic risk profile during weight loss and help to maintain weight loss afterwards.

Project description:BackgroundObesity is an urgent public health problem, yet only a few clinical trials have systematically tested the efficacy of long-term weight-loss maintenance interventions. This randomized clinical trial tested the efficacy of a novel mind and body technique for weight-loss maintenance.MethodsParticipants were obese adults who had completed a six-month behavioral weight-loss program prior to randomization. Those who successfully lost weight were randomized into either an experimental weight-loss maintenance intervention, Tapas Acupressure Technique (TAT®), or a control intervention comprised of social-support group meetings (SS) led by professional facilitators. TAT combines self-applied light pressure to specific acupressure points accompanied by a prescribed sequence of mental steps. Participants in both maintenance conditions attended eight group sessions over six months of active weight loss maintenance intervention, followed by an additional 6 months of no intervention. The main outcome measure was change in weight from the beginning of the weight loss maintenance intervention to 12 months later. Secondary outcomes were change in depression, stress, insomnia, and quality of life. We used analysis of covariance as the primary analysis method. Missing values were replaced using multiple imputation.ResultsAmong 285 randomized participants, 79% were female, mean age was 56 (standard deviation (sd) = 11), mean BMI at randomization was 34 (sd = 5), and mean initial weight loss was 9.8 kg (sd = 5). In the primary outcome model, there was no significant difference in weight regain between the two arms (1.72 kg (se 0.85) weight regain for TAT and 2.96 kg (se 0.96) weight regain for SS, p < 0.097) Tests of between- arm differences for secondary outcomes were also not significant. A secondary analysis showed a significant interaction between treatment and initial weight loss (p < .036), with exploratory post hoc tests showing that greater initial weight loss was associated with more weight regain for SS but less weight regain for TAT.ConclusionsThe primary analysis showed no significant difference in weight regain between TAT and SS, while secondary and post hoc analyses indicate direction for future research.

Project description:To examine associations between sleep disturbance and changes in weight and body composition and the mediating role of changes of appetite and food cravings in the Preventing Overweight Using Novel Dietary Strategies (POUNDS Lost) 2-year weight-loss diet intervention trial, this study included 810 overweight or obese individuals with baseline sleep disturbance assessment who were randomly assigned one of four diets varying in macronutrient composition. Changes in body weight and fat distribution were assessed by DEXA and computed tomography during the 2-year intervention. Participants were asked to provide sleep disturbance levels (no, slight, moderate, or great) at baseline and to recall their sleep disturbances since last visit at 6, 12, 18, and 24 months. Weight loss during the first 6 months was followed by 1.5 years of steady weight regain. Participants with greater sleep disturbance from baseline to 6 months showed significant losses of body weight (Ptrend <0.001) and waist circumference (Ptrend = 0.002) at 6 months, after multivariate adjustment. Compared with individuals without sleep disturbance at all from baseline to 6 months, those with slight, moderate, or great sleep disturbance showed an elevated risk of failure to lose weight (-5% or more loss) at 6 months, when the maximum weight loss was achieved, with an odds ratio of 1.24 (95% CI 0.87, 1.78), 1.27 (95% CI 0.75, 2.13), or 3.12 (95% CI 1.61, 6.03), respectively. In addition, we observed that the repeatedly measured levels of sleep disturbance over 2 years were inversely associated with the overall weight loss rate (weight changes per 6 months) (Ptrend <0.001). Further, sleep disturbances during weight loss from baseline to 6 months and weight regain from 6 months to 24 months were significantly predictive of total fat, total fat mass percent, and trunk fat percent changes during the 2 years. Our results also indicated that food cravings for carbohydrates/starches, fast food fats, and sweets; cravings, prospective consumption, hunger of appetite measurements; and dietary restraint, disinhibition, and hunger subscales measured at 6 months significantly mediated the effects of sleep disturbance on weight loss. In conclusion, our results suggested that more severe sleep disturbance during weight loss was associated with an elevated risk of failure to lose weight during the dietary intervention. Food cravings and eating behaviors may partly mediate these associations.

Dataset Information

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

Publications

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

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