Effects of Exercise on Blood Glucose and Glycemic Variability in Type 2 Diabetic Patients with Dawn Phenomenon

Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes

The introduction of continuous glucose monitoring inaugurated a new era in clinical practice by shifting the characterization of glycemic control from HbA1c to novel metrics. The one that gained widespread attention over the past decades was glycemic variability (GV), which typically refers to peaks and nadirs of blood glucose measured over a given time interval. GV can be dichotomized into two main categories: short-term and long-term. Short-term GV reflects within-day and between-day glycemic oscillations, and its contribution to diabetic complications remains an enigma. In this review, we summarize the available data about short-term GV and its possible association with both microvascular and macrovascular complications, evaluating different pathogenic mechanisms and demonstrating nonpharmaceutical, as well as pharmaceutical, therapeutic interventions.

Exercise-induced improvement of glycemic fluctuation and its relationship with fat and muscle distribution in type 2 diabetes

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.

Attention to Innate Circadian Rhythm and the Impact of Its Disruption on Diabetes

Novel strategies are required to reduce the risk of developing diabetes and/or clinical outcomes and complications of diabetes. In this regard, the role of the circadian system may be a potential candidate for the prevention of diabetes. We reviewed evidence from animal, clinical, and epidemiological studies linking the circadian system to various aspects of the pathophysiology and clinical outcomes of diabetes. The circadian clock governs genetic, metabolic, hormonal, and behavioral signals in anticipation of cyclic 24-hour events through interactions between a "central clock" in the suprachiasmatic nucleus and "peripheral clocks" in the whole body. Currently, circadian rhythmicity in humans can be subjectively or objectively assessed by measuring melatonin and glucocorticoid levels, core body temperature, peripheral blood, oral mucosa, hair follicles, rest-activity cycles, sleep diaries, and circadian chronotypes. In this review, we summarized various circadian misalignments, such as altered light-dark, sleep-wake, rest-activity, fasting-feeding, shift work, evening chronotype, and social jetlag, as well as mutations in clock genes that could contribute to the development of diabetes and poor glycemic status in patients with diabetes. Targeting critical components of the circadian system could deliver potential candidates for the treatment and prevention of type 2 diabetes mellitus in the future.

Interactive effect of swimming training and fenugreek (Trigonella foenum graecum L.) extract on glycemic indices and lipid profile in diabetic rats

Present study investigated the interactive effect of swimming training and fenugreek on glycemic index and lipid profile of diabetic rats. Forty-eight diabetic rats were randomly assigned to (1) control(C), (2) training(T), (3) fenugreek(F), and (4) training + fenugreek(T + F) groups and 12 healthy rats were placed in healthy control (HC) group. During 4 weeks, groups 2 and 4 performed swimming training for 5 sessions per week and groups 3 and 4 received 100 mg/kg fenugreek. training, fenugreek and training + fenugreek significantly decreased glucose, insulin, insulin resistance, LDL, VLDL, TG and TC as well as increased HDL (p ≤ .05) also training + fenugreek had more favourable effects on improving glycemic indices and lipid profile compared to training and fenugreek alone (p ≤ .05). It seems that training and fenugreek alone or synergistically improve the glycemic indices and lipid profile in diabetic rats, nevertheless the synergistic effects of training and fenugreek can be more desirable than the effect of each alone.

Comparison of Point-of-Care and Laboratory Glycated Hemoglobin A1c and Its Relationship to Time-in-Range and Glucose Variability: A Real-World Study

Introduction The main objective of the current study was to perform a comparison of point-of-care testing for hemoglobin A1c (POCT-HbA1c) versus the standard laboratory method (Lab HbA1c) and their relationship to time-in-range (TIR) and glucose variability (GV) among patients with diabetes mellitus (DM) presented to the outpatient diabetes clinics. Methods This single-center cross-sectional study was carried out on diabetic patients (aged ≥14 years of both genders) who undergo routine follow-up at our institution and whose physicians ordered HbA1c analysis for routine care. The included patients were those using the intermittently scanned continuous glucose monitoring (isCGM) Abbott's FreeStyle Libre system for at least three months and regular CGM users with at least 70% use. Results We included 97 diabetic patients (41 female and 56 male), with a median age of 25 years (Interquartile range= 18) and a mean DM duration of 10.33±5.48 years. The mean values of Lab-HbA1c and POCT HbA1c were 8.82%±0.85% and 8.53%±0.89%, respectively. The TIR, time below range, and time above range were 33.47±14.38 minutes (47.78%±14.32%), 5.44±2.58 minutes (8.41%±4.42%), and 28.8±8.27 minutes (43.81%±13.22%), respectively. According to the Bland-Altman plot analysis, the POCT-HbA1c values are consistent with the standard Lab-HbA1c values (SD of bias= 0.55, and 95% CI= -0.78 to 1.4). The univariate linear regression analysis showed a statistically significant relationship between laboratory HbA1c and POCT HbA1c (R2= 0.637, p <0.001), TIR (R2= 0.406, p <0.001), and GV (R2= 0.048, p= 0.032). After adjusting for age, gender, disease duration, diabetes type, and percentage of sensor data in a multivariable linear regression model, the linear associations remained significant (all p < 0.05). Conclusion The current findings show that TIR and GV can be used as endpoints and valuable parameters for the therapy of DM.

The associations between health-related physical fitness and fasting blood glucose in war veterans: a population-based study

The main purpose of the study was to analyze the associations between health-related physical fitness and fasting blood glucose in war veterans. In this cross-sectional study, we recruited 764 men and women aged 45-75 years, who were part of the Homeland War between 1990 and 1995 (33.5% women). Health-related physical fitness included: (1) fat mass and fat-free mass (body composition), (2) push-ups in 30 s (muscular dynamic endurance of upper extremities), (3) sit-ups in 30 s (repetitive upper body strength), (4) chair-stands in 30 s (lower body strength), (5) sit-and-reach test (flexibility) and (6) the 2-min step test (cardiorespiratory function). Laboratory measurement of fasting blood glucose was performed according to standardized procedures in resting seated position after a 12-h overnight fast. Generalized estimating equations with multiple regression models were used to calculate the associations between health-related physical fitness and fasting blood glucose. In men, fasting blood glucose was significantly correlated with fat-free mass (β = - 0.25, p < 0.001), push-ups in 30 s (β = - 0.55, p < 0.001), chair-stands in 30 s (β = - 0.50, p < 0.001), sit-ups in 30 s (r = - 0.45, p < 0.001), the sit-and reach test (r = - 0.46, p < 0.001) and the 2-min step test (r = - 0.19, p < 0.001), while fat mass was positively correlated with fasting blood glucose (β = 0.14, p = 0.004). In women, fasting blood glucose was significantly correlated with fat mass (β = 0.20, p = 0.002), fat-free mass (β = - 0.15, p = 0.014), push-ups in 30 s (β = - 0.49, p < 0.001), chair-stands in 30 s (β = - 0.43, p < 0.001), sit-ups in 30 s (β = - 0.52, p < 0.001), the sit-and reach test (β = - 0.40, p < 0.001) and the 2-min step test (β = - 0.35, p < 0.001). This study shows that fasting blood glucose may be predicted by health-related physical fitness test in war veterans.

Moderate-intensity exercise decreases the circulating level of betatrophin and its correlation among markers of obesity in women

OBJECTIVES

Positive energy homeostasis due to overnutrition and a sedentary lifestyle triggers obesity. Obesity has a close relationship with elevated levels of betatrophin and may increase the risk of developing metabolic syndrome. Therefore, lifestyle modification through a nonpharmacological approach based on physical exercise is the right strategy in lowering betatrophin levels. This study aimed to analyze the effect of moderate-intensity interval and continuous exercises on decreased betatrophin levels and the association between betatrophin levels and obesity markers in women.

METHODS

A total of 30 women aged 20-24 years old were randomly divided into three groups. Measurement of betatrophin levels using Enzyme-Linked Immunosorbent Assay (ELISA). Data analysis techniques used were one-way ANOVA and parametric linear correlation.

RESULTS

The results showed that the average levels of betatrophin pre-exercise were 200.40 ± 11.03 pg/mL at CON, 203.07 ± 42.48 pg/mL at MIE, 196.62 ± 21.29 pg/mL at MCE, and p=0.978. Average levels of betatrophin post-exercise were 226.65 ± 18.96 pg/mL at CON, 109.31 ± 11.23 pg/mL at MIE, 52.38 ± 8.18 pg/mL at MCE, and p=0.000. Pre-exercise betatrophin levels were positively correlated with age, BMI, FM, WHR, FBG, and PBF (p≤0.001).

CONCLUSIONS

Our study showed that betatrophin levels are decreased by 10 min post-MIE and post-MCE. However, moderate-intensity continuous exercise is more effective in lowering betatrophin levels than moderate-intensity interval exercise. In addition, pre-exercise betatrophin levels also have a positive correlation with obesity markers.

Cycling to Regulate Random Blood Glucose Levels in Individuals with Diabetes

BACKGROUND: In Indonesia, the four pillars of diabetes management include health education, food planning, physical exercise, and drug adherence. However, the most common imprudence in those four pillars was ignoring physical activity. Cycling has become a new social activity and a lifestyle among the community during the COVID-19 pandemic. It is an aerobic exercise that increases insulin receptor sensitivity. AIM: This study aims to analyze the effect of cycling on Random Blood Glucose (RBG) levels in individuals with diabetes. METHODOLOGY: This paper used a quasi-experiment pre-post test design with the control group. It utilized total sampling with 60 respondents. The independent variable was cycling using a dynamic bicycle. Meanwhile, the dependent variable was RBG levels with a glucometer as the instrument. The procedure in the intervention group was cycling using a dynamic bicycle twice a week with a distance of 2–3 kilometers each session. The data analysis used a paired T-test and independent sample T-test. RESULTS: After cycling, the independent T-test result was p = 0.00 (p < 0.05). Thus, there was a difference in the mean RBG levels between the intervention and control groups after cycling. There was a decrease in mean RBG levels in the intervention group (206.67 ± 69.887 in pre-test and 114.60 ± 30.395 in post-test). In addition, the paired T-test resulted in p = 0.00 (p < 0.05). Thus, there was a difference in the intervention group’s mean RBG levels before and after cycling CONCLUSION: Cycling can lower RBG levels in individuals with diabetes.

Metabolomic signatures in elite cyclists: differential characterization of a seeming normal endocrine status regarding three serum hormones

INTRODUCTION

Serum phenotyping of elite cyclists regarding cortisol, IGF1 and testosterone is a way to detect endocrine disruptions possibly explained by exercise overload, non-balanced diet or by doping. This latter disruption-driven approach is supported by fundamental physiology although without any evidence of any metabolic markers.

OBJECTIVES

Serum samples were distributed through Low, High or Normal endocrine classes according to hormone concentration. A ¹H NMR metabolomic study of 655 serum obtained in the context of the longitudinal medical follow-up of 253 subjects was performed to discriminate the three classes for every endocrine phenotype.

METHODS

An original processing algorithm was built which combined a partial-least squares-based orthogonal correction of metabolomic signals and a shrinkage discriminant analysis (SDA) to get satisfying classifications. An extended validation procedure was used to plan in larger size cohorts a minimal size to get a global prediction rate (GPR), i.e. the product of the three class prediction rates, higher than 99.9%.

RESULTS

Considering the 200 most SDA-informative variables, a sigmoidal fitting of the GPR gave estimates of a minimal sample size to 929, 2346 and 1408 for cortisol, IGF1 and testosterone, respectively. Analysis of outliers from cortisol and testosterone Normal classes outside the 97.5%-confidence limit of score prediction revealed possibly (i) an inadequate protein intake for outliers or (ii) an intake of dietary ergogenics, glycine or glutamine, which might explain the significant presence of heterogeneous metabolic profiles in a supposedly normal cyclists subgroup.

CONCLUSION

In a next validation metabolomics study of a so-sized cohort, anthropological, clinical and dietary metadata should be recorded in priority at the blood collection time to confirm these functional hypotheses.

Time-in-range as a target in type 2 diabetes: An urgent need

Time-in-range emerged as a valuable blood glucose metric, 'beyond HbA1c' for a deeper insight into glycemic control in people with diabetes. It denotes the proportion of time that a person's glucose level remains within the desired target range (usually 70-180 mg/dL or 3.9-10.0 mmol/L). Though clinical targets in the current recommendations for type 1 and type 2 diabetes are close enough, their clinical profiles and prevalences are quite different. Type 2 diabetes is the commonest form of diabetes. Many clinical trials have challenged the usefulness of HbA1c as a glycemic target for Type 2 diabetes mellitus. On account of the higher prevalence and complications of type 2 diabetes, more outcomes-based studies are needed to associate time-in-range with its ongoing risk. These studies strongly support the dependability of time-in-range to identify patients with elevated risk in type 2 diabetes. We discuss the utility of time-in-range, a new metric of continuous glucose monitoring as an outcome measure to correlate with type 2 diabetes risks and complications and to analyze the effectiveness of type 2 diabetes management. This approach may support the use of time-in-range as a metric for long-term health outcomes in the type 2 diabetes population.

Antidiabetic Effects of Physical Activity: How It Helps to Control Type 2 Diabetes

Despite the improvements in clinical care of the patients, research updates, and public health interventions, there is still an increase in the prevalence, incidence, and mortality because of diabetes mellitus (DM). DM is a public health problem in both developed and developing countries. It has increased alarmingly, putting this disease in the dimension of an epidemic. Diabetes is associated with several complications which increase the risk of many serious health problems on the other side. Therefore, this review was aimed to discuss the antidiabetic effects of physical activity (PA) on type 2 DM (T2DM) by summarizing the significant studies on this topic. This review found that several studies have recommended the utilization of PA for the effective management of T2DM. PA is a non-pharmacologic therapy which is a significant strategy for the management of T2DM and is an appropriate lifestyle modification approach to be practiced by these patients. The studies showed that PA has antidiabetic effects which are evidenced by its substantial role in improving the blood glucose (BG) levels of the individuals with T2DM where it helps them to control their levels of glucose in the blood. It plays a significant role in glycemic control of this disease by lowering the BG levels through possible mechanisms such as decreasing insulin resistance, increasing production of glucose transporter type 4 (GLUT-4), lowering visceral adipose tissue (VAT), increasing pancreatic β-cell functions, using glucose for energy, and so on. In turn, the controlled glycemia helps to prevent the complications associated with uncontrolled T2DM and this would further improve the overall health of the patients and the burden on the health professionals as well. Finally, this review concludes that PA is the cornerstone in the management of T2DM. It also suggests that more attention is needed to its significance in the prevention, glycemic control, and its role in the management of the morbidity and mortality associated with T2DM. Practical PA recommendations and suggestions for the future direction of research in this area are also provided.