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Aim: This qualitative study aimed to explore the experiences of participants who were enrolled in 6‐month controlled weight loss interventions with 2‐month follow‐up to better understand the process of behaviour change and maintenance. Methods: Fifteen participants who completed or dropped out from either a daily energy restriction or intermittent fasting group were recruited using maximum variation purposive sampling. In‐depth, semi‐structured interviews were conducted at the 2‐month follow‐up phase. All interviews were transcribed and analysed using thematic analysis, guided by behaviour change models including transtheoretical model, social cognitive theory and integrated model of change. Results: Participants following both diets showed similar behaviour change patterns. Their first motivations were mostly external and relied on 'accountability' to adhere to the diet when initiating the dietary changes. Participants highlighted the importance of frequent reviews and monitoring in assisting their adherence. This feedback system promoted the development of self‐efficacy and internalised motivation to encourage an 'ownership'. Participants who transitioned successfully from relying on accountability to take 'ownership' of the intervention were more capable of tackling challenges and tailoring their diet to form a new routine for long‐term maintenance. Conclusion: External motivations were key to initiate while internalised motivations were more important to sustain the behaviour change. Health professionals can assist this process through routine monitoring and feedback processes in clinical practice. [ABSTRACT FROM AUTHOR]

Background:e-Health refers to any health care service delivered through the internet or related technologies, to improve quality of life. Despite the increasing use of e-health interventions to manage type 2 diabetes (T2D), there is a lack of evidence about the effectiveness on diabetes distress and depression, which are common issues in those living with T2D. Purpose:To synthesize and determine the effects of e-health interventions on diabetes distress and depression among patients with T2D. Methods:We systematically searched PubMed, Scopus, Cochrane CENTRAL, and Web of Science for randomized controlled trials (RCTs), non-RCTs and observational cohort studies for the effects of e-health interventions on diabetes distress and depression in patients with T2D up to September 14, 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 recommendations were followed. The risk of bias was assessed according to the Risk-of-Bias 2 tool (RCTs), the Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I) (non-RCTs) and the National Institute of Health tool (observational). The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) were estimated with the DerSimonian–Laird method through random-effect models. A pooled raw mean difference (MD) meta-analysis was conducted for RCTs comparing the effects of e-health versus control on diabetes distress screening to display the clinical impact. Results:A total of 41 studies (24 RCTs, 14 non-RCTs, and 3 observational) involving 8,667 individuals were included. The pooled SMD for the effect of e-health versus the control group on diabetes distress was −0.14 (95% CI = −0.24 to −0.04; I2 = 23.9%; n = 10 studies), being -0.06 (95% CI = −0.15 to 0.02; I2 = 7.8%; n = 16 studies) for depression. The pooled raw MD on diabetes distress screening showed a reduction of −0.54 points (95% CI = −0.81 to −0.27; I2 = 85.1%; n = 7 studies). Conclusion:e-Health interventions are effective in diminishing diabetes distress among adults with T2D, inducing clinically meaningful reductions. [ABSTRACT FROM AUTHOR]

Accumulating evidence supports the benefits of intermittent fasting (IF) as a dietary strategy for cardiometabolic health and weight control. However, little is known about the potential implications of IF on mental disorders. The aim of this review was to synthesize evidence regarding the effects of IF on mental disorders (depression, anxiety, and mood state) in the general population. We conducted a systematic search in five databases from inception to January 2022. Randomized and nonrandomized clinical trials (RCTs/nonRCTs) were included. A random effects method was used to pool standardized mean differences (SMDs) and 95% CIs. A total of 14 studies involving 562 individuals were included, of which 8 were RCTs and 6 were nonRCTs. IF showed a moderate and positive effect on depression scores when compared to control groups (SMD: 0.41; 95%CI: 0.05 to 0.76; I2=45%; n = 4). Conversely, within-group analyses did not show any significant effect of IF on anxiety (SMD: 0.10; 95%CI: −0.09 to 0.30; I2=0%; n = 5) or mood state (SMD: 0.14; 95%CI: −0.09 to 0.37; I2=59%; n = 7). IF modalities did not negatively impact mental disorders in the general population. In fact, IF showed a positive influence on diminishing depression scores, and did not modify anxiety or mood. [ABSTRACT FROM AUTHOR]

Aim: To determine whether a digital nudge soon after dinner reduces after‐dinner snacking events as measured objectively by continuous glucose monitoring (CGM) in patients with type 2 diabetes (T2D). Methods: This is a single‐site micro‐randomized trial (MRT). People with T2D, aged 18‐75 years, managed with diet or a stable dose of oral antidiabetic medications for at least 3 months, and who habitual snack after dinner at least 3 nights per week, will be recruited. Picto‐graphic nudges were designed by mixed research methods. After a 2‐week lead‐in phase to determine eligibility and snacking behaviours by a CGM detection algorithm developed by the investigators, participants will be micro‐randomized daily (1:1) to a second 2‐week period to either a picto‐graphic nudge delivered‐in‐time (Intui Research) or no nudge. During lead‐in and MRT phases, 24‐hour glucose will be measured by CGM, sleep will be tracked by an under‐mattress sleep sensor, and dinner timing will be captured daily by photographing the evening meal. Results: The primary outcome is the difference in the incremental area under the CGM curve between nudging and non‐nudging days during the period from 90 minutes after dinner until 04:00 AM. Secondary outcomes include the effect of baseline characteristics on treatment, and comparisons of glucose peaks and time‐in‐range between nudging and non‐nudging days. The feasibility of 'just‐in‐time' messaging and nudge acceptability will be evaluated, along with the analysis of sleep quality measures and their night‐to‐night variability. Conclusions: This study will provide preliminary evidence of the impact of appropriately timed digital nudges on 24 ‐hour intertitial glucose levels resulting from altered after‐dinner snacking in people with T2D. An exploratory sleep substudy will provide evidence of a bidirectional relationship between after‐dinner snacking behaviour, glycaemia and sleep. Ultimately, this study will allow for the design of a future confirmatory study of the potential for digital nudging to improve health related behaviours and health outcomes. [ABSTRACT FROM AUTHOR]

Objective: Time‐restricted eating (TRE) restores circadian rhythms in mice, but the evidence to support this in humans is limited. The objective of this study was to investigate the effects of TRE on 24‐hour profiles of plasma metabolites, glucoregulatory hormones, and the subcutaneous adipose tissue (SAT) transcriptome in humans. Methods: Men (n = 15, age = 63 [4] years, BMI 30.5 [2.4] kg/m2) were recruited. A 35‐hour metabolic ward stay was conducted at baseline and after 8 weeks of 10‐hour TRE. Assessment included 24‐hour profiles of plasma glucose, nonesterified fatty acid (NEFA), triglyceride, glucoregulatory hormones, and the SAT transcriptome. Dim light melatonin onset and cortisol area under the curve were calculated. Results: TRE did not alter dim light melatonin onset but reduced morning cortisol area under the curve. TRE altered 24‐hour profiles of insulin, NEFA, triglyceride, and glucose‐dependent insulinotropic peptide and increased transcripts of circadian locomotor output cycles protein kaput (CLOCK) and nuclear receptor subfamily 1 group D member 2 (NR1D2) and decreased period circadian regulator 1 (PER1) and nuclear receptor subfamily 1 group D member 1 (NR1D1) at 12:00 am. The rhythmicity of 450 genes was altered by TRE, which enriched in transcripts for transcription corepressor activity, DNA‐binding transcription factor binding, regulation of chromatin organization, and small GTPase binding pathways. Weighted gene coexpression network analysis revealed eigengenes that were correlated with BMI, insulin, and NEFA. Conclusions: TRE restored 24‐hour profiles in hormones, metabolites, and genes controlling transcriptional regulation in SAT, which could underpin its metabolic health benefit. [ABSTRACT FROM AUTHOR]

Eating architecture is a term that describes meal frequency, meal timing and meal size and the daily variation in each of these. The aim of this study was to determine the relationship between components of eating architecture on body fat and markers of glycaemic control in healthy adults at increased risk of type 2 diabetes (T2DM). Participants (n 73, 39 males, age 58·8 (8·1) years, BMI 33·4 (4·4) kg/m2) recorded food intake and wore accelerometers and continuous glucose monitors (CGM) for 7–14 d under free-living conditions. Body fat and glycated Hb (HbA1c) were also measured. The mean and day-to-day variation (calculated as the standard deviation during the monitoring period) of each component of eating architecture were calculated. Multivariable linear regression models were constructed for three separate outcome variables (body fat mass, mean CGM glucose and HbA1c) for each component of eating architecture before and after adjustment for confounders. Higher variability in the time of first meal consumption was associated with increased body fat mass after adjusting for confounders (β = 0·227, 95 % CI: 0·019, 0·434, P = 0·033). Increased variability in the time lag from waking to first meal consumption was also positively associated with increased HbA1c after adjustment (β = 0·285, 95 % CI: 0·040, 0·530, P = 0·023). Low day-to-day variability in first meal consumption was associated with lower body fat and improved glucose control in adults at increased risk of T2DM. Routine consumption of meals may optimise temporal regulation to anticipate and respond appropriately to a glucose challenge. [ABSTRACT FROM AUTHOR]