Abstract

The interest in intermittent energy restriction (IER) diets as a weight-loss approach is increasing. Different IER protocols exist, including time-restricted eating (TRE), alternate-day fasting (ADF), and the 5:2 diet. This meta-analysis compared the effects of these IER diets with continuous energy restriction (CER) on anthropometrics and cardiometabolic risk markers in healthy adults. Twenty-eight trials were identified that studied TRE (k = 7), ADF (k = 10), or the 5:2 diet (k = 11) for 2-52 wk. Energy intakes between intervention groups within a study were comparable (17 trials), lower in IER (5 trials), or not reported (6 trials). Weighted mean differences (WMDs) were calculated using fixed- or random-effects models. Changes in body weight [WMD: -0.42 kg; 95% confidence interval (CI): -0.96 to 0.13; P = 0.132] and fat mass (FM) (WMD: -0.31 kg; 95% CI: -0.98 to 0.36; P = 0.362) were comparable when results of the 3 IER diets were combined and compared with those of CER. All IER diets combined reduced fat-free mass (WMD: -0.20 kg; 95% CI: -0.39 to -0.01; P = 0.044) and waist circumference (WMD: -0.91 cm; 95% CI: -1.76 to -0.06; P = 0.036) more than CER. Effects on body mass index [BMI (kg/m2)], glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), serum lipid and lipoprotein concentrations, and blood pressure did not differ. Further, TRE reduced body weight, FM, and fat-free mass more than CER, whereas ADF improved HOMA-IR more. BMI was reduced less in the 5:2 diet compared with CER. In conclusion, the 3 IER diets combined did not lead to superior improvements in anthropometrics and cardiometabolic risk markers compared with CER diets. Slightly greater reductions were, however, observed in fat-free mass and waist circumference. To what extent differences in energy intakes between groups within studies may have influenced these outcomes should be addressed in future studies.

Abstract

BACKGROUND AND AIMS Sleep disorders are bidirectionally linked with eating behaviors and glucose metabolism, which could be clinically relevant in type 1 diabetes (T1D). We investigated the relationship between dietary habits and sleep quality in individuals with T1D on insulin pumps and continuous glucose monitoring (CGM). METHODS AND RESULTS In a cross-sectional study, dietary habits (7-day food diary, EPIC questionnaire) and sleep quality (Pittsburgh Sleep Quality Index questionnaire) were assessed in 59 men and 58 women with T1D, aged 19-79 years, using CGM and insulin pump. Differences in dietary habits and blood glucose after dinner (6 h) between participants differing in sleep quality, sleep duration, and sleep onset latency were evaluated. Bad Sleepers (n = 81) were twice as prevalent as Good Sleepers (n = 36) and had a significantly higher intake of fat than Good Sleepers (dinner: 30.7 ± 10.7 vs. 24.0 ± 10.5 g, p = 0.004). Short sleepers had a significantly higher usual intake (g/1000 kcal) of coffee and tea (90.4 ± 71.7 vs. 62.0 ± 35.6), alcoholic (47.8 ± 51.1 vs. 28.9 ± 31.5) and carbonated beverages (21.8 ± 38.1 vs. 9.3 ± 17.2) (p < 0.05 for all) than Long Sleepers. Long Sleep Onset Latency was associated with a significantly higher fat intake at dinner (41.8 ± 7.4 vs. 38.1 ± 9.1 % total energy, p = 0.029) than Short Sleep Onset Latency. No significant differences in post-dinner blood glucose levels were detected between participants with good or bad sleep quality. CONCLUSION Sleep disruption is common in T1D and is associated with unhealthy dietary choices, especially at dinner, independently of post-dinner blood glucose control.

Abstract

BACKGROUND & AIMS Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. METHODS Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome. RESULTS Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. CONCLUSION GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

Abstract

AIMS/HYPOTHESIS Continuous glucose monitoring (CGM) is increasingly used in the treatment of type 2 diabetes, but the effects on glycaemic control are unclear. The aim of this systematic review and meta-analysis is to provide a comprehensive overview of the effect of CGM on glycaemic control in adults with type 2 diabetes. METHODS We performed a systematic review using Embase, MEDLINE, Web of Science, Scopus and ClinicalTrials.gov from inception until 2 May 2023. We included RCTs investigating real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) compared with self-monitoring of blood glucose (SMBG) in adults with type 2 diabetes. Studies with an intervention duration <6 weeks or investigating professional CGM, a combination of CGM and additional glucose-lowering treatment strategies or GlucoWatch were not eligible. Change in HbA1c and the CGM metrics time in range (TIR), time below range (TBR), time above range (TAR) and glycaemic variability were extracted. We evaluated the risk of bias using the Cochrane risk-of-bias tool version 2. Data were synthesised by performing a meta-analysis. We also explored the effects of CGM on severe hypoglycaemia and micro- and macrovascular complications. RESULTS We found 12 RCTs comprising 1248 participants, with eight investigating rtCGM and four isCGM. Compared with SMBG, CGM use (rtCGM or isCGM) led to a mean difference (MD) in HbA1c of -3.43 mmol/mol (-0.31%; 95% CI -4.75, -2.11, p<0.00001, I2=15%; moderate certainty). This effect was comparable in studies that included individuals using insulin with or without oral agents (MD -3.27 mmol/mol [-0.30%]; 95% CI -6.22, -0.31, p=0.03, I2=55%), and individuals using oral agents only (MD -3.22 mmol/mol [-0.29%]; 95% CI -5.39, -1.05, p=0.004, I2=0%). Use of rtCGM showed a trend towards a larger effect (MD -3.95 mmol/mol [-0.36%]; 95% CI -5.46 to -2.44, p<0.00001, I2=0%) than use of isCGM (MD -1.79 mmol/mol [-0.16%]; 95% CI -5.28, 1.69, p=0.31, I2=64%). CGM was also associated with an increase in TIR (+6.36%; 95% CI +2.48, +10.24, p=0.001, I2=9%) and a decrease in TBR (-0.66%; 95% CI -1.21, -0.12, p=0.02, I2=45%), TAR (-5.86%; 95% CI -10.88, -0.84, p=0.02, I2=37%) and glycaemic variability (-1.47%; 95% CI -2.94, -0.01, p=0.05, I2=0%). Three studies reported one or more events of severe hypoglycaemia and macrovascular complications. In comparison with SMBG, CGM use led to a non-statistically significant difference in the incidence of severe hypoglycaemia (RR 0.66, 95% CI 0.15, 3.00, p=0.57, I2=0%) and macrovascular complications (RR 1.54, 95% CI 0.42, 5.72, p=0.52, I2=29%). No trials reported data on microvascular complications. CONCLUSIONS/INTERPRETATION CGM use compared with SMBG is associated with improvements in glycaemic control in adults with type 2 diabetes. However, all studies were open label. In addition, outcome data on incident severe hypoglycaemia and incident microvascular and macrovascular complications were scarce. REGISTRATION This systematic review was registered on PROSPERO (ID CRD42023418005).

Abstract

BACKGROUND People with type 1 diabetes generally view it easier to exercise when having continuous information of the glucose levels. We evaluated whether patients with type 1 diabetes managed with multiple daily insulin injections (MDI) exercised more after initiating continuous glucose monitoring (CGM) and whether the improved glycemic control and well-being associated with CGM translates into improved blood lipids and markers of inflammation. METHOD The GOLD trial was a randomized cross-over trial over 16 months where patients used either CGM or capillary self-monitoring of blood glucose (SMBG) over six months, with a four-month wash-out period between the two treatment periods. We compared grade of physical activity, blood lipids, apolipoproteins, and high-sensitivity C-reactive protein (hsCRP) levels during CGM and SMBG. RESULTS There were 116 patients with information of physical activity estimated by the International Physical Activity Questionnaire (IPAQ) during both CGM and SMBG. No changes were found during CGM or SMBG, IPAQ scores 3305 versus 3878 (P = .16). In 136 participants with information of blood lipid levels with no change in lipid-lowering medication during the two treatment periods, HbA1c differed by 4.2 mmol/mol (NGSP 0.39%) between SMBG and CGM treatment (P < .001). No significant changes existed in low-density lipoprotein, high-density lipoprotein, triglycerides, total cholesterol, apolipoprotein A1, apolipoprotein B1, or hsCRP, during CGM and SMBG. CONCLUSION Although many patients experience it easier to perform physical activity when monitoring glucose levels with CGM, it does not influence the amount of physical activity in persons with type 1 diabetes. Blood lipids, apolipoprotein, and hsCRP levels were similar during CGM and SMBG.

Abstract

AIMS/HYPOTHESIS Hypomagnesaemia has been associated with insulin resistance and an increased risk of type 2 diabetes. Whether magnesium supplementation improves insulin sensitivity in people with type 2 diabetes and a low serum magnesium level is unknown. METHODS Using a randomised, double-blind (both participants and investigators were blinded to the participants' treatment sequences), placebo-controlled, crossover study design, we compared the effect of oral magnesium supplementation (15 mmol/day) for 6 weeks with that of matched placebo in individuals with insulin-treated type 2 diabetes (age ≥18 years, BMI 18-40 kg/m2, HbA1c <100 mmol/mol [11.3%], serum magnesium ≤0.79 mmol/l). Participants were recruited from the outpatient clinic and through advertisements. Randomisation to a treatment sequence order was done using a randomisation list. We used block randomisation and the two possible treatment sequences were evenly distributed among the trial population. The primary outcome was the mean glucose infusion rate during the final 30 min of a hyperinsulinaemic-euglycaemic clamp (i.e. M value). Secondary outcomes included variables of glucose control, insulin need, BP, lipid profile and hypomagnesaemia-related symptoms during follow-up. RESULTS We recruited 14 participants (50% women, 100% White, mean ± SD age 67±6 years, BMI 31±5 kg/m2, HbA1c 58±9 mmol/mol [7.4±0.9%]) with insulin-treated type 2 diabetes. Magnesium supplementation increased both mean ± SEM serum magnesium level (0.75±0.02 vs 0.70±0.02 mmol/l, p=0.016) and urinary magnesium excretion (magnesium/creatinine ratio, 0.23±0.02 vs 0.15±0.02, p=0.005), as compared with placebo. The M value of the glucose clamp did not differ between the magnesium and placebo study arms (4.6±0.5 vs 4.4±0.6 mg kg-1 min-1, p=0.108). During the 6 weeks of treatment, continuous glucose monitoring outcomes, HbA1c, insulin dose, lipid profile and BP also did not differ, except for a lower HDL-cholesterol concentration after magnesium compared with placebo (1.14±0.08 vs 1.20±0.09 mmol/l, p=0.026). Symptoms potentially related to hypomagnesaemia were similar for both treatment arms. CONCLUSIONS/INTERPRETATION Despite an albeit modest increase in serum magnesium concentration, oral magnesium supplementation does not improve insulin sensitivity in people with insulin-treated type 2 diabetes and low magnesium levels. TRIAL REGISTRATION EudraCT number 2021-001243-27. FUNDING This study was supported by a grant from the Dutch Diabetes Research Foundation (2017-81-014).

Abstract

AIMS: Management of blood glucose fluctuation is essential for diabetes. Exercise is a key therapeutic strategy for diabetes patients, although little is known about determinants of glycemic response to exercise training. We aimed to investigate the effect of combined aerobic and resistance exercise training on blood glucose fluctuation in type 2 diabetes patients and explore the predictors of exercise-induced glycemic response. MATERIALS AND METHODS Fifty sedentary diabetes patients were randomly assigned to control or exercise group. Participants in the control group maintained sedentary lifestyle for 2 weeks, and those in the exercise group specifically performed combined exercise training for 1 week. All participants received dietary guidance based on a recommended diet chart. Glycemic fluctuation was measured by flash continuous glucose monitoring. Baseline fat and muscle distribution were accurately quantified through magnetic resonance imaging (MRI). RESULTS Combined exercise training decreased SD of sensor glucose (SDSG, exercise-pre vs exercise-post, mean 1.35 vs 1.10 mmol/L, p = .006) and coefficient of variation (CV, mean 20.25 vs 17.20%, p = .027). No significant change was observed in the control group. Stepwise multiple linear regression showed that baseline MRI-quantified fat and muscle distribution, including visceral fat area (β = -0.761, p = .001) and mid-thigh muscle area (β = 0.450, p = .027), were significantly independent predictors of SDSG change in the exercise group, as well as CV change. CONCLUSIONS Combined exercise training improved blood glucose fluctuation in diabetes patients. Baseline fat and muscle distribution were significant factors that influence glycemic response to exercise, providing new insights into personalized exercise intervention for diabetes.

Abstract

OBJECTIVES To assess the feasibility and change in clinical outcomes associated with continuous glucose monitoring (CGM) use among a rural population in Malawi living with type 1 diabetes. DESIGN A 2:1 open randomised controlled feasibility trial. SETTING Two Partners In Health-supported Ministry of Health-run first-level district hospitals in Neno, Malawi. PARTICIPANTS 45 people living with type 1 diabetes (PLWT1D). INTERVENTIONS Participants were randomly assigned to Dexcom G6 CGM (n=30) use or usual care (UC) (n=15) consisting of Safe-Accu glucose monitors and strips. Both arms received diabetes education. OUTCOMES Primary outcomes included fidelity, appropriateness and severe adverse events. Secondary outcomes included change in haemoglobin A1c (HbA1c), acceptability, time in range (CGM arm only) SD of HbA1c and quality of life. RESULTS Participants tolerated CGM well but were unable to change their own sensors which resulted in increased clinic visits in the CGM arm. Despite the hot climate, skin rashes were uncommon but cut-out tape overpatches were needed to secure the sensors in place. Participants in the CGM arm had greater numbers of dose adjustments and lifestyle change suggestions than those in the UC arm. Participants in the CGM arm wore their CGM on average 63.8% of the time. Participants in the UC arm brought logbooks to clinic 75% of the time. There were three hospitalisations all in the CGM arm, but none were related to the intervention. CONCLUSIONS This is the first randomised controlled trial conducted on CGM in a rural region of a low-income country. CGM was feasible and appropriate among PLWT1D and providers, but inability of participants to change their own sensors is a challenge. TRIAL REGISTRATION NUMBER PACTR202102832069874.

Abstract

BACKGROUND Time-restricted eating (TRE) is increasingly popular, but its benefits in combination with exercise still need to be determined. OBJECTIVES This systematic review and meta-analysis aimed to evaluate the efficacy of TRE combined with exercise compared with control diet with exercise in improving the body composition and metabolic health of adults. METHODS Five electronic databases were searched for relevant studies. Randomized controlled trials (RCTs) examining the effect of TRE combined with exercise on body composition and metabolic health in adults were included. All results in the meta-analysis are reported as mean difference (MD) with 95% confidence interval (CI). Study quality was assessed using the revised Cochrane Risk of Bias Tool and Grading of Recommendations Assessment, Development, and Evaluation assessment. RESULTS In total, 19 RCTs comprising 568 participants were included in this systematic review and meta-analysis. TRE combined with exercise likely reduced the participants' body mass (MD: -1.86 kg; 95% CI: -2.75, -0.97 kg) and fat mass (MD: -1.52 kg; 95% CI: -2.07, -0.97 kg) when compared with the control diet with exercise. In terms of metabolic health, the TRE combined with exercise group likely reduced triglycerides (MD: -13.38 mg/dL, 95% CI: -21.22, -5.54 mg/dL) and may result in a reduction in low-density lipoprotein (MD: -8.52 mg/dL; 95% CI: -11.72, -5.33 mg/dL) and a large reduction in leptin (MD: -0.67 ng/mL; 95% CI: -1.02, -0.33 ng/mL). However, TRE plus exercise exhibited no additional benefit on the glucose profile, including fasting glucose and insulin, and other lipid profiles, including total cholesterol and high-density lipoprotein concentrations, compared with the control group. CONCLUSIONS Combining TRE with exercise may be more effective in reducing body weight and fat mass and improving lipid profile than control diet with exercise. Implementing this approach may benefit individuals aiming to achieve weight loss and enhance their metabolic well-being. This study was registered in PROSPERO as CRD42022353834.

Abstract

INTRODUCTION AND AIM Exercise training (Ex) and intermittent fasting (IF) are effective for improving body composition and cardiometabolic health overweight and obese adults, but whether combining Ex and IF induces additive or synergistic effects is less well established. We therefore, performed a systematic review and meta-analysis to compare the combined versus independent effects of Ex and IF on body composition and cardiometabolic health in adults. METHOD An electronic search was conducted in three main online databases including PubMed, Web of Science, and Scopus, from inception to March 9, 2023 for studies involving Ex plus IF trials versus standalone Ex and/or IF interventions in adults. Interventions had a duration of ≥ 2 weeks. Standardized (SMD) or weighted mean differences (WMD) and 95% confidence intervals were calculated in order to compare effects on body weight, body mass index (BMI), body fat lean body mass (LBM), visceral fat, and waist circumference. For cardiometabolic health, outcomes included fasting glucose, insulin, total cholesterol (TC), low-density lipoprotein cholesterol (LDL), triglycerides (TG), high-density lipoprotein cholesterol (HDL), systolic (SBP) and diastolic (DBP) blood pressure, and VO2max/peak. RESULTS Ex plus IF decreased body weight [WMD: -3.03 kg (95% CI: -3.44 to -2.61), p = 0.001], BMI [WMD: -1.12 kg.m2 (95% CI: -1.28 to -0.95), p = 0.001], body fat [SMD: -0.72 (95% CI: -1.23 to -0.21), p = 0.005], visceral fat [SMD: -0.34 (95% CI: -0.63 to -0.05), p = 0.01], and waist circumference [WMD: -2.63 cm (95% CI: -4.16 to -1.11), p = 0.001] more than Ex alone. However, changes in body composition and cardiometabolic health markers were not significantly different for Ex plus IF when compared with IF alone, with the exception of VO2max/peak [SMD: 0.55 (95% CI: 0.14 to 0.97), p = 0.009]. CONCLUSION We demonstrate that a combination of Ex and IF produces superior changes in body composition, but not in markers of cardiometabolic health when compared with Ex or IF alone. Ex plus IF could therefore be effective for weight and fat loss but has no additive or synergistic effects for other cardiometabolic health markers.