The Effect of Physical Activity on Glycemic Variability in Patients With Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Timing of Moderate to Vigorous Physical Activity, Mortality, Cardiovascular Disease, and Microvascular Disease in Adults With Obesity

OBJECTIVE

To assess the association between timing of aerobic moderate to vigorous physical activity (MVPA) and risk of cardiovascular disease (CVD), microvascular disease (MVD), and all-cause mortality in adults with obesity and a subset with obesity and type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Participants included adults with obesity (BMI ≥30 kg/m2) and a subset of those with T2D from the UK Biobank accelerometry substudy. Aerobic MVPA was defined as bouts of MVPA lasting ≥3 continuous minutes. Participants were categorized into morning, afternoon, or evening MVPA based on when they undertook the majority of their aerobic MVPA. The reference group included participants with an average of less than one aerobic MVPA bout per day. Analyses were adjusted for established and potential confounders.

RESULTS

The core sample included 29,836 adults with obesity, with a mean age of 62.2 (SD 7.7) years. Over a mean follow-up period of 7.9 (SD 0.8) years, 1,425 deaths, 3,980 CVD events, and 2,162 MVD events occurred. Compared with activity in the reference group, evening MVPA was associated with the lowest risk of mortality (hazard ratio [HR] 0.39; 95% CI 0.27, 0.55), whereas afternoon (HR 0.60; 95% CI 0.51, 0.71) and morning MVPA (HR 0.67; 95% CI 0.56, 0.79) demonstrated significant but weaker associations. Similar patterns were observed for CVD and MVD incidence, with evening MVPA associated with the lowest risk of CVD (HR 0.64; 95% CI 0.54, 0.75) and MVD (HR 0.76; 95% CI 0.63, 0.92). Findings were similar in the T2D subset (n = 2,995).

CONCLUSIONS

Aerobic MVPA bouts undertaken in the evening were associated with the lowest risk of mortality, CVD, and MVD. Timing of physical activity may play a role in the future of obesity and T2D management.

Optimal Dose and Type of Physical Activity to Improve Glycemic Control in People Diagnosed With Type 2 Diabetes: A Systematic Review and Meta-analysis

BACKGROUND

The optimal dose or type of physical activity to control glycosylated hemoglobin (HbA1c) in people with diabetes remains unknown. Current guidelines do not include consideration of baseline HbA1c for activity prescription.

PURPOSE

To examine the dose-response relationship between physical activity and HbA1c (%) in individuals with type 2 diabetes.

DATA SOURCES

A systematic search was performed in Embase, MEDLINE, Scopus, CINAHL, SPORTDiscus, and Web of Science.

STUDY SELECTION

We included trials that involved participants diagnosed with type 2 diabetes that included any type of physical activity as intervention.

DATA EXTRACTION

Pre- and postintervention HbA1c data, population and interventions characteristics, and descriptive statistics were collected to calculate change scores for each study arm.

DATA SYNTHESIS

We used Bayesian random-effects meta-analyses to summarize high-quality evidence from 126 studies (6,718 participants). The optimal physical activity dose was 1,100 MET min/week, resulting in HbA1c reductions, ranging from -1.02% to -0.66% in severe uncontrolled diabetes, from -0.64% to -0.49% in uncontrolled diabetes, from -0.47% to -0.40% in controlled diabetes, and from -0.38% to -0.24% in prediabetes.

LIMITATIONS

The time required to achieve these HbA1c reductions could not be estimated due to the heterogeneity between interventions' duration and protocols and the interpersonal variability of this outcome.

CONCLUSIONS

The result of this meta-analysis provide key information about the optimal weekly dose of physical activity for people with diabetes with consideration of baseline HbA1c level, and the effectiveness of different types of active interventions. These results enable clinicians to prescribe tailored physical activity programs for this population.

Correlation Between Blood Glucose Indexes Generated by the Flash Glucose Monitoring System and Diabetic Vascular Complications

Objective

To discuss the relationship between time in range (TIR) which is deprived of the FGMS and the risk of diabetic vascular complications and to provide a theoretical foundation for the clinical application of TIR and other FGMS-deprived indexes.

Methods

Patients with T2DM who wore the FGMS sensor continuously were enrolled. Relevant indexes such as TIR, time below range (TBR), time above range (TAR), a standard deviation of blood glucose (SDBG), coefficient of variation of blood glucose (CV), and mean amplitude of glycemic excursion (MAGE) generated by the FGMS were recorded, and the risk of diabetic vascular complications were followed up for one year. The TIR was measured by continuous glucose monitoring at baseline, and patients were grouped according to TIR every 20%. Finally, the Cox proportional hazards regression model was used to estimate the association of different levels of TIR with different rates of diabetic vascular complications.

Results

TIR was negatively correlated with HbA1C, CV, SDBG, and amplitude of glycemic excursion (MV), wherein, the lower the TIR, the higher the HbA1C, CV, SDBG, and MV. TIR in the diabetic microvascular complication was significantly lower than that in the non-microvascular complication group, and the difference was statistically significant. TIR <40% was identified as a risk factor for DN, DPN, and DR according to the risk assessment. The mean TAR in the DN group was significantly higher than that in the non-DN group. TAR, CV, SD, MAGE, and HbA1C in the DR group were significantly higher than those in the non-DR group. TAR, ABG, CV, SD, MAGE, and HbA1C in the DPN group were significantly higher than those in the non-DPN group.

Conclusion

The relationships between the TIR and the prevalence and risk of diabetic vascular complications and the HbA1C may be negative. Other CGM-deprived indexes such as CV and MV should be integrated into glycemic control and diabetes complication prediction.

Digital Behavior Change Interventions to Reduce Sedentary Behavior and Promote Physical Activity in Adults with Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Technological advancements and ease of Internet access have increased the number of digital behavior change interventions (DBCIs). This systematic review and meta-analysis aimed to assess the effectiveness of DBCIs in reducing sedentary behavior (SB) and promoting physical activity (PA) in adults with diabetes.

METHODS

A comprehensive search of seven databases-PubMed, Embase, PsycINFO, Cochrane Library, CINAHL, Web of Science, and Sedentary Behavior Research Database-was performed. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence evaluation. Meta-analyses were performed where feasible; otherwise, narrative summaries were performed.

RESULTS

A total of 13 randomized controlled trials with 980 participants met the inclusion criteria. Overall, DBCIs could significantly increase steps and the number of breaks in sedentary time. The subgroup analyses exhibited significant effects in DBCIs with over 10 behavior change techniques (BCTs) in improving steps, the time spent in light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). The subgroup analyses showed a significant step increment in DBCIs of moderate and long durations, with over 4 BCT clusters, or in conjunction with a face-to-face component. The subgroup analyses also indicated significant effects in studies with ≥ 2 DBCI components in improving steps, the time spent in LPA and MVPA, and reducing sedentary time.

CONCLUSION

There is some evidence that DBCI may increase PA and reduce SB in adults with type 2 diabetes. However, more high-quality studies are required. Future studies are needed to examine the potential of DBCIs in adults with type 1 diabetes.

Hypoglycemia and glycemic variability of people with type 1 diabetes with lower and higher physical activity loads in free-living conditions using continuous subcutaneous insulin infusion with predictive low-glucose suspend system

INTRODUCTION

Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime-daytime and active- sedentary behavior hours in free-living conditions.

RESEARCH DESIGN AND METHODS

Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m²; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime-daytime and active-sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA.

RESULTS

Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05).

CONCLUSION

Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.

Physical activity interventions for glycaemic control in African adults - A systematic review and meta-analysis

BACKGROUND AND AIM

Growing evidence indicates that increasing physical activity may aid in regulating altered glycaemic control, thereby mitigating the risk of diabetes. However, the evidence summarising the efficacy of physical activity on glycaemic control among African adults remains unconsolidated. Our objective was to provide an amalgamated summary of the empirical evidence that explored the effectiveness of physical activity interventions on glycaemic control among African adults.

METHODS

A systematic search of six journal databases for the studies exploring the efficacy of physical activity on glycaemic control among African adults until March 21, 2022, was administered. Two independent reviewers screened the citations based on a priori set eligibility criteria. Data were analysed using inverse variance method and a summary of findings was synthesised using the Grading of Recommendations, Assessment, Development and Evaluations approach.

RESULTS

Of the 14,624 citations retrieved, 26 articles with 1474 participants were included for final analysis. Most of the included trials had a high risk of bias (N = 20; 76.92%). Our review found a significant reduction in fasting blood glucose (FBG, -2.18 [ 95% CI -3.18, -1.18] mmol/L), insulin (-0.99 [-2.71, 0.74] μU/L), Glycosylated haemoglobin (HbA1C) (-0.53% [-0.88, -0.19]), Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (-0.74% [-1.10, -0.38]) and insulin sensitivity (-0.90 μU/l/min [-1.75, -0.06]) following physical activity interventions. The review reports low certainty of evidence across all outcome measures.

DISCUSSION AND CONCLUSION

Physical activity interventions were found to improve glycaemic control among African adults. However, the optimal physical activity dose for demonstrating meaningful benefits on glucose tolerance still remains unclear due to the limited number of primary studies available.

Cross-Sectional and Individual Relationships between Physical Activity and Glycemic Variability

Introduction/Purpose

Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM).

Methods

Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed.

Results

LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%-71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action.

Conclusions

Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.