Impact of free-living pattern of sedentary behaviour on intra-day glucose regulation in type 2 diabetes

Relationship between intra-individual variability in nutrition-related lifestyle behaviors and blood glucose outcomes under free-living conditions in adults without type 2 diabetes

AIMS

This study determined the relationship between intra-individual variability in day-to-day nutrition-related lifestyle behaviors (meal timing, eating window, food intake, movement behaviors, sleep conditions, and body weight) and glycemic outcomes under free-living conditions in adults without type 2 diabetes.

METHODS

We analyzed 104 adults without type 2 diabetes. During the 7-day measurement period, dietary intake, movement behaviors, sleep conditions, and glucose outcomes were assessed. Daily food intake was assessed using a mobile-based health application. Movement behaviors and sleep conditions were assessed using a tri-axial accelerometer. Meal timing was assessed from the participant's daily life record. Blood glucose levels were measured continuously using a glucose monitor. Statistical analyses were conducted using a linear mixed-effects model, with mealtime, food intake, body weight, movement behaviors, and sleep conditions as fixed effects and participants as a random effect.

RESULTS

Dinner time and eating window were positively significantly correlated with mean (dinner time, p = 0.003; eating window, p = 0.001), standard deviation (SD; both at p < 0.001), and maximum (both at p < 0.001) blood glucose levels. Breakfast time was negatively associated with glucose outcomes (p < 0.01). Sedentary time was positively significantly associated with blood glucose SD (p = 0.040). Total sleep time was negatively significantly correlated with SD (p = 0.035) and maximum (p = 0.032) blood glucose levels. Total daily energy intake (p = 0.001), carbohydrate intake (p < 0.001), and body weight (p < 0.05) were positively associated with mean blood glucose levels.

CONCLUSION

Intra-individual variations in nutrition-related lifestyle behaviors, especially morning and evening body weight, and food intake, were associated with mean blood glucose levels, and a long sedentary time and total sleep time were associated with glucose variability. Earlier dinner times and shorter eating windows per day resulted in better glucose control.

Digital Biomarkers for Personalized Nutrition: Predicting Meal Moments and Interstitial Glucose with Non-Invasive, Wearable Technologies

Digital health technologies may support the management and prevention of disease through personalized lifestyle interventions. Wearables and smartphones are increasingly used to continuously monitor health and disease in everyday life, targeting health maintenance. Here, we aim to demonstrate the potential of wearables and smartphones to (1) detect eating moments and (2) predict and explain individual glucose levels in healthy individuals, ultimately supporting health self-management. Twenty-four individuals collected continuous data from interstitial glucose monitoring, food logging, activity, and sleep tracking over 14 days. We demonstrated the use of continuous glucose monitoring and activity tracking in detecting eating moments with a prediction model showing an accuracy of 92.3% (87.2-96%) and 76.8% (74.3-81.2%) in the training and test datasets, respectively. Additionally, we showed the prediction of glucose peaks from food logging, activity tracking, and sleep monitoring with an overall mean absolute error of 0.32 (+/-0.04) mmol/L for the training data and 0.62 (+/-0.15) mmol/L for the test data. With Shapley additive explanations, the personal lifestyle elements important for predicting individual glucose peaks were identified, providing a basis for personalized lifestyle advice. Pending further validation of these digital biomarkers, they show promise in supporting the prevention and management of type 2 diabetes through personalized lifestyle recommendations.

Health effects of reduced occupational sedentary behaviour in type 2 diabetes using a mobile health intervention: a study protocol for a 12-month randomized controlled trial-the ROSEBUD study

BACKGROUND

Short-term trials conducted in adults with type 2 diabetes mellitus (T2DM) showed that reducing sedentary behaviour by performing regular short bouts of light-intensity physical activity enhances health. Moreover, support for reducing sedentary behaviour may be provided at a low cost via mobile health technology (mHealth). There are a wide range of mHealth solutions available including SMS text message reminders and activity trackers that monitor the physical activity level and notify the user of prolonged sitting periods. The aim of this study is to evaluate the effects of a mHealth intervention on sedentary behaviour and physical activity and the associated changes in health in adults with T2DM.

METHODS

A dual-arm, 12-month, randomized controlled trial (RCT) will be conducted within a nationwide Swedish collaboration for diabetes research in primary health care. Individuals with T2DM (n = 142) and mainly sedentary work will be recruited across primary health care centres in five regions in Sweden. Participants will be randomized (1:1) into two groups. A mHealth intervention group who will receive an activity tracker wristband (Garmin Vivofit4), regular SMS text message reminders, and counselling with a diabetes specialist nurse, or a comparator group who will receive counselling with a diabetes specialist nurse only. The primary outcomes are device-measured total sitting time and total number of steps (activPAL3). The secondary outcomes are fatigue, health-related quality of life and musculoskeletal problems (self-reported questionnaires), number of sick leave days (diaries), diabetes medications (clinical record review) and cardiometabolic biomarkers including waist circumference, mean blood pressure, HbA1c, HDL-cholesterol and triglycerides.

DISCUSSION

Successful interventions to increase physical activity among those with T2DM have been costly and long-term effectiveness remains uncertain. The use of mHealth technologies such as activity trackers and SMS text reminders may increase awareness of prolonged sedentary behaviour and encourage increase in regular physical activity. mHealth may, therefore, provide a valuable and novel tool to improve health outcomes and clinical management in those with T2DM. This 12-month RCT will evaluate longer-term effects of a mHealth intervention suitable for real-world primary health care settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04219800 . Registered on 7 January 2020.

Diet and Physical Activity as Determinants of Continuously Measured Glucose Levels in Persons at High Risk of Type 2 Diabetes

We examined how dietary and physical activity behaviors influence fluctuations in blood glucose levels over a seven-day period in people at high risk for diabetes. Twenty-eight participants underwent a mixed meal tolerance test to assess glucose homeostasis at baseline. Subsequently, they wore an accelerometer to assess movement behaviors, recorded their dietary intakes through a mobile phone application, and wore a flash glucose monitoring device that measured glucose levels every 15 min for seven days. Generalized estimating equation models were used to assess the associations of metabolic and lifestyle risk factors with glycemic variability. Higher BMI, amount of body fat, and selected markers of hyperglycemia and insulin resistance from the meal tolerance test were associated with higher mean glucose levels during the seven days. Moderate- to vigorous-intensity physical activity and polyunsaturated fat intake were independently associated with less variation in glucose levels (CV%). Higher protein and polyunsaturated fatty acid intakes were associated with more time-in-range. In contrast, higher carbohydrate intake was associated with less time-in-range. Our findings suggest that dietary composition (a higher intake of polyunsaturated fat and protein and lower intake of carbohydrates) and moderate-to-vigorous physical activity may reduce fluctuations in glucose levels in persons at high risk of diabetes.

Different frequencies of active interruptions to sitting have distinct effects on 22 h glycemic control in type 2 diabetes

BACKGROUND & AIMS

Whether the frequency of interruptions to sitting time involving simple resistance activities (SRAs), compared to uninterrupted sitting, differentially affected 22 h glycemic control in adults with medication-controlled type 2 diabetes (T2D).

METHODS & RESULTS

Twenty-four participants (13 men; mean ± SD age 62 ± 8 years) completed three 8 h laboratory conditions: SIT: uninterrupted sitting; SRA3: sitting interrupted with 3 min of SRAs every 30 min; and, SRA6: sitting interrupted with 6 min of SRAs every 60 min. Flash glucose monitors assessed glycemic control over a 22 h period. No differences were observed between conditions for overall 22 h glycemic control as measured by AUC_total, mean glucose and time in hyperglycemia. During the 3.5 h post-lunch period, mean glucose was significantly lower during SRA6 (10.1 mmol·L^-1, 95%CI 9.2, 11.0) compared to SIT (11.1 mmol·L^-1, 95%CI 10.2, 12.0; P = 0.006). Post-lunch iAUC_net was significantly lower during SRA6 (6.2 mmol·h·L^-1, 95%CI 3.3, 9.1) compared to SIT (9.9 mmol·h·L^-1, 95%CI 7.0, 12.9; P = 0.003). During the post-lunch period, compared to SIT (2.2 h, 95%CI 1.7, 2.6), time in hyperglycemia was significantly lower during SRA6 (1.5 h, 95%CI 1.0, 1.9, P = 0.001). Nocturnal mean glucose was significantly lower following the SRA3 condition (7.6 mmol·L^-1, 95%CI 7.1, 8.1) compared to SIT (8.1 mmol·L^-1, 95%CI 7.6, 8.7, P = 0.024).

CONCLUSIONS

With standardized total activity time, less-frequent active interruptions to sitting may acutely improve glycemic control; while more-frequent interruptions may be beneficial for nocturnal glucose in those with medication-controlled T2D.

Frequency of Interruptions to Sitting Time: Benefits for Postprandial Metabolism in Type 2 Diabetes

OBJECTIVE

To determine whether interrupting sitting with brief bouts of simple resistance activities (SRAs) at different frequencies improves postprandial glucose, insulin, and triglycerides in adults with medication-controlled type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Participants (n = 23, 10 of whom were female, with mean ± SD age 62 ± 8 years and BMI 32.7 ± 3.5 kg · m^-2) completed a three-armed randomized crossover trial (6- to 14-day washout): sitting uninterrupted for 7 h (SIT), sitting with 3-min SRAs (half squats, calf raises, gluteal contractions, and knee raises) every 30 min (SRA3), and sitting with 6-min SRAs every 60 min (SRA6). Net incremental areas under the curve (iAUC_net) for glucose, insulin, and triglycerides were compared between conditions.

RESULTS

Glucose and insulin 7-h iAUC_net were attenuated significantly during SRA6 (glucose 17.0 mmol · h · L^-1, 95% CI 12.5, 21.4; insulin 1,229 pmol · h · L^-1, 95% CI 982, 1,538) in comparison with SIT (glucose 21.4 mmol · h · L^-1, 95% CI 16.9, 25.8; insulin 1,411 pmol · h · L^-1, 95% CI 1,128, 1,767; P < 0.05) and in comparison with SRA3 (for glucose only) (22.1 mmol · h · L^-1, 95% CI 17.7, 26.6; P = 0.01) No significant differences in glucose or insulin iAUC_net were observed in comparison of SRA3 and SIT. There was no statistically significant effect of condition on triglyceride iAUC_net.

CONCLUSIONS

In adults with medication-controlled T2D, interrupting prolonged sitting with 6-min SRAs every 60 min reduced postprandial glucose and insulin responses. Other frequencies of interruptions and potential longer-term benefits require examination to clarify clinical relevance.

Acute and Chronic Effects of Exercise on Continuous Glucose Monitoring Outcomes in Type 2 Diabetes: A Meta-Analysis

Objective: To examine the acute and chronic effects of structured exercise on glucose outcomes assessed by continuous glucose monitors in adults with type 2 diabetes. Methods: PubMed, Medline, EMBASE were searched up to January 2020 to identify studies prescribing structured exercise interventions with continuous glucose monitoring outcomes in adults with type 2 diabetes. Randomized controlled trials, crossover trials, and studies with pre- and post-designs were eligible. Short-term studies were defined as having exercise interventions lasting ≤2 weeks. Longer-term studies were defined as >2 weeks. Results: A total of 28 studies were included. Of these, 23 studies were short-term exercise interventions. For all short-term studies, the same participants completed a control condition as well as at least one exercise condition. Compared to the control condition, exercise decreased the primary outcome of mean 24-h glucose concentrations in short-term studies (-0.5 mmol/L, [-0.7, -0.3]; p < 0.001). In longer-term studies, mean 24-h glucose was not significantly reduced compared to control (-0.9 mmol/L [-2.2, 0.3], p = 0.14) but was reduced compared to pre-exercise values (-0.5 mmol/L, [-0.7 to -0.2] p < 0.001). The amount of time spent in hyperglycemia and indices of glycemic variability, but not fasting glucose, also improved following short-term exercise. Among the shorter-term studies, subgroup, and regression analyses suggested that the timing of exercise and sex of participants explained some of the heterogeneity among trials. Conclusion: Both acute and chronic exercise can improve 24-h glucose profiles in adults with type 2 diabetes. The timing of exercise and sex of participants are among the factors that may explain part of the heterogeneity in acute glycemic improvements following exercise.