Poor sleep habits are associated with increased risk of developing type 2 diabetes. In this review and meta-analysis, we aimed to investigate the effects of sleep manipulation on markers of insulin sensitivity from randomized, controlled trials. Sleep manipulation was defined as reduction in sleep duration, sleep quality, and circadian misalignment. A systematic literature search was conducted in three databases and resulted in 35 eligible articles. The studies included interventions on sleep restriction (26 studies), slow wave sleep suppression and rapid eye movement sleep disturbance (2 studies), sleep fragmentation (2 studies), and circadian misalignment (5 studies). The meta-analysis included 21 sleep restriction studies. Sleep restriction reduced insulin sensitivity assessed by oral or intravenous glucose tolerance test and homeostatic model assessment of insulin resistance. Whole-body insulin sensitivity was also reduced after short sleep when measured by the hyperinsulinemic euglycemic clamp, but peripheral insulin sensitivity was not affected. In addition, circadian misalignment and slow wave sleep suppression negatively affected insulin sensitivity, while rapid eye movement sleep disturbance and sleep fragmentation had no effect. In summary, the studies indicated that duration, quality, and timing of sleep are essential for metabolic function and risk of type 2 diabetes.

Summary: In parallel with an increased focus on climate changes and carbon footprint, the interest in plant‐based diets and its potential health effects have increased over the past decade. The objective of this systematic review and meta‐analysis was to examine the effect of vegan diets (≥12 weeks) on cardiometabolic risk factors in people with overweight or type 2 diabetes. We identified 11 trials (796 participants). In comparison with control diets, vegan diets reduced body weight (−4.1 kg, 95% confidence interval (CI) −5.9 to −2.4, p < 0.001), body mass index (BMI) (−1.38 kg/m², 95% CI −1.96 to −0.80, p < 0.001), glycated hemoglobin (HbA_1c) (−0.18% points, 95% CI −0.29 to −0.07, p = 0.002), total cholesterol (−0.30 mmol/L, 95% CI −0.52 to −0.08, p = 0.007), and low‐density lipoprotein cholesterol (−0.24 mmol/L, 95% CI −0.40 to −0.07, p = 0.005). We identified no effect on blood pressure, high‐density lipoprotein cholesterol, and triglycerides. We found that adhering to vegan diets for at least 12 weeks may be effective in individuals with overweight or type 2 diabetes to induce a meaningful decrease in body weight and improve glycemia. Some of this effect may be contributed to differences in the macronutrient composition and energy intake in the vegan versus control diets. Therefore, more research is needed regarding vegan diets and cardiometabolic health.

Background: Systematic reviews are essential but time‐consuming and expensive. Large language models (LLMs) and artificial intelligence (AI) tools could potentially automate data extraction, but no comprehensive workflow has been tested for different review types. Objective: To evaluate Elicit's and ChatGPT's abilities to extract data from journal articles as a replacement for one of two human data extractors in systematic reviews. Methods: Human‐extracted data from three systematic reviews (30 articles in total) was compared to data extracted by Elicit and ChatGPT. The AI tools extracted population characteristics, study design, and review‐specific variables. Performance metrics were calculated against human double‐extracted data as the gold standard, followed by a detailed error analysis. Results: Precision, recall and F1‐score were all 92% for Elicit and 91%, 89% and 90% for ChatGPT. Recall was highest for study design (Elicit: 100%; ChatGPT: 90%) and population characteristics (Elicit: 100%; ChatGPT: 97%), while review‐specific variables achieved 77% in Elicit and 80% in ChatGPT. Elicit had four instances of confabulation while ChatGPT had three. There was no significant difference between the two AI tools' performance (recall difference: 3.3% points, 95% CI: –5.2%–11.9%, p = 0.445). Conclusion: AI tools demonstrated high and similar performance in data extraction compared to human reviewers, particularly for standardized variables. Error analysis revealed confabulations in 4% of data points. We propose adopting AI‐assisted extraction to replace the second human extractor, with the second human instead focusing on reconciling discrepancies between AI and the primary human extractor.

Objective: This systematic scoping review aimed to map and synthesize research on feasibility of time‐restricted eating (TRE) in individuals with overweight, obesity, prediabetes, or type 2 diabetes, including recruitment rate, retention rate, safety, adherence, and participants' attitudes, experiences, and perspectives.Methods: The authors searched MEDLINE, Embase, and Cumulative Index to Nursing and Allied Health Literature from inception to November 22, 2022, supplemented by backward and forward citation search.Results: From 4219 identified records, 28 studies were included. In general, recruitment was easy and median retention rate was 95% among studies with <12 weeks duration and 89% among studies ≥12 weeks. Median (range) adherence to the target eating window for studies <12 and ≥12 weeks was 89% (75%–98%) and 81% (47%–93%), respectively. Variation in adherence among participants and studies was considerable, indicating that following TRE was difficult for some people and that intervention conditions influenced adherence. These findings were supported by qualitative data synthetized from seven studies, and determinants of adherence included calorie‐free beverages outside the eating window, provision of support, and influence on the eating window. No serious adverse events were reported.Conclusions: TRE is implementable, acceptable, and safe in populations with overweight, obesity, prediabetes, or type 2 diabetes, but it should be accompanied by support and options for individual adjustments.

The aim of this systematic review and meta-analysis was to examine the effects of plant-based diets on markers of insulin sensitivity in people with overweight/obesity, prediabetes, or type 2 diabetes (T2D). A systematic literature search in MEDLINE, Embase, CINAHL, and CENTRAL was conducted, and randomised controlled trials (RCTs) investigating the effect of plant-based diets (vegan, ovo-vegetarian, lacto-vegetarian, and lacto-ovo-vegetarian) for ≥14 d on markers of insulin sensitivity in adults (≥18 years) with BMI ≥ 25 kg/m², prediabetes, or T2D were eligible. We identified eight RCTs, including 716 participants. In comparison with control diets, plant-based diets improved Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (−0.97, 95% confidence interval (CI) (−1.67, −0.27), p = 0.007) and fasting insulin (−4.13 µU/mL, 95% CI (−7.22, −1.04), p = 0.009) in people with overweight/obesity. In people with prediabetes, one study compared vegan and vegetarian diets and found no difference in HOMA-IR, or fasting insulin. One study of people with T2D reported no difference in immunoreactive insulin and metabolic glucose clearance compared with a conventional diabetes diet. In conclusion, adhering to plant-based diets for ≥14 d improved HOMA-IR and fasting insulin in people with overweight/obesity. Long-term RCTs are needed to determine whether plant-based diets can result in prolonged improvements in insulin sensitivity in people at risk of or with T2D.

To design an appealing time-restricted eating (TRE) intervention by exploring behavioral and social mechanisms to improve TRE adoption and maintenance among people with type 2 diabetes (T2D) and overweight. Time-restricted eating is an intermittent fasting regimen suggested to improve glycemic control and body weight. Intervention development combined coherence theory and empirical data (workshops and semistructured interviews with the target group, their relatives, and health care professionals [HCPs]). Abductive analysis was applied. The analysis suggested designing the TRE intervention in 2 phases: a short period with strict TRE, followed by a longer period focusing on adapting TRE to individual needs with support from HCPs, relatives, and peers. To reinforce TRE motivation and maintenance, HCPs should adopt a whole-person approach that focuses on participants' previous experiences. Important intervention elements to promote TRE adoption and maintenance are suggested to include a 2-phase design and support from professionals, family, and peers.