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

Nutrients ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 366
Author(s):  
Su Hyun Park ◽  
Jiali Yao ◽  
Xin Hui Chua ◽  
Suresh Rama Chandran ◽  
Daphne S. L. Gardner ◽  
...  
Keyword(s):  
Physical Activity ◽  
High Risk ◽  
Vigorous Physical Activity ◽  
Glycemic Variability ◽  
Tolerance Test ◽  
Dietary Intakes ◽  
Polyunsaturated Fat ◽  
Meal Tolerance Test ◽  
Glucose Levels ◽  
Time In Range

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.

Metabolic and lifestyle determinants of glycemic variability in persons at high risk of type 2 diabetes: a study with continuous monitoring of diet, physical activity, and glucose level. (Preprint)

2021 ◽  
Author(s):  
Su Hyun Park ◽  
Jiali Yao ◽  
Clare Whitton ◽  
Xin Hui Chua ◽  
Suresh Rama Chandran ◽  
...  
Keyword(s):  
Physical Activity ◽  
High Risk ◽  
Glycemic Variability ◽  
Tolerance Test ◽  
Glucose Levels ◽  
Intensity Physical Activity ◽  
Time In Range ◽  
Vigorous Intensity ◽  
Mean Glucose

BACKGROUND Frequent and large fluctuations in blood glucose concentration during the day may increase risk of type 2 diabetes. It remains unclear how diet and physical activity affect glycemic variability in real-world conditions in persons without diabetes. OBJECTIVE We examined metabolic and lifestyle determinants (diet, physical activity, and sleep) of blood glucose levels over a seven-day period in people at high risk for diabetes METHODS Twenty-eight participants with a mean age of 46.0 (SD 9.9) years and a mean body mass index (BMI) of 27.5 (SD 1.8) kg/m2 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 daily mean glucose levels (mmol/L), the coefficient of variation (CV%) of glucose levels, and time-in-range (3.0 to 7.8 mmol/L, %). RESULTS A higher BMI (β = 0.12 per kg/m2; P = 0.01), body fat (β = 0.03 per kg; P = 0.01), 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 (β = -1.77 per hr./d, P = 0.008) and polyunsaturated fat intake (β = -2.23 per 5 energy %, P < 0.001) were independently associated with less variation in glucose levels (CV%). Higher protein (β = 0.90, P = 0.007) and polyunsaturated fatty acid (β = 3.21, P = 0.02) intakes were associated with more time-in-range. In contrast, higher carbohydrates intake was associated with less time-in-range (β = -0.59, P = 0.04). Sleep, sedentary behavior, or light intensity physical activity were not independently associated with glucose measures. CONCLUSIONS Body fatness was associated with higher mean glucose levels, and moderate-to-vigorous intensity physical activity was associated with less glycemic variability throughout a week. Diets with higher protein and polyunsaturated fat, and lower carbohydrates were associated with more time in normal glucose range. Physical activity and dietary composition can substantially influence glucose variation in people at high risk of diabetes.

scholarly journals Evaluation of Reference Metrics for Continuous Glucose Monitoring in Persons Without Diabetes and Prediabetes

2020 ◽  
pp. 193229682096559
Author(s):  
Sheyda Sofizadeh ◽  
Anders Pehrsson ◽  
Arndís F. Ólafsdóttir ◽  
Marcus Lind
Keyword(s):  
Clinical Practice ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Mean Amplitude ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Glucose Lowering ◽  
Glucose Levels ◽  
Deviation Coefficient

Background: Recent guidelines have been developed for continuous glucose monitoring (CGM) metrics in persons with diabetes. To understand what glucose profiles should be judged as normal in clinical practice and glucose-lowering trials, we examined the glucose profile of healthy individuals using CGM. Methods: Persons without diabetes or prediabetes were included after passing a normal oral glucose tolerance test, two-hour value <8.9 mmol/L (160 mg/dL), fasting glucose <6.1 mmol/L (110 mg/dL), and HbA1c <6.0% (<42 mmol/mol). CGM metrics were evaluated using the Dexcom G4 Platinum. Results: In total, 60 persons were included, mean age was 43.0 years, 70.0% were women, mean HbA1c was 5.3% (34 mmol/mol), and mean body mass index was 25.7 kg/m2. Median and mean percent times in hypoglycemia <3.9 mmol/L (70 mg/dL) were 1.6% (IQR 0.6-3.2), and 3.2% (95% CI 2.0; 4.3), respectively. For glucose levels <3.0 mmol/L (54 mg/dL), the corresponding estimates were 0.0% (IQR 0.0-0.4) and 0.5% (95% CI 0.2; 0.8). Median and mean time-in-range (3.9-10.0 mmol/L [70-180 mg/dL]) was 97.3% (IQR 95.4-98.7) and 95.4% (95% CI 94.0; 96.8), respectively. Median and mean standard deviations were 1.04 mmol/L (IQR 0.92-1.29) and 1.15 mmol/L (95% CI 1.05; 1.24), respectively. Measures of glycemic variability (standard deviation, coefficient of variation, mean amplitude of glycemic excursions) were significantly greater during daytime compared with nighttime, whereas others did not differ. Conclusions: People without prediabetes or diabetes show a non-negligible % time in hypoglycemia, median 1.6% and mean 3.2%, which needs to be accounted for in clinical practice and glucose-lowering trials. Glycemic variability measures differ day and night in this population.

scholarly journals FitKids360: Design, Conduct, and Outcomes of a Stage 2 Pediatric Obesity Program

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jared M. Tucker ◽  
Joey C. Eisenmann ◽  
Kathleen Howard ◽  
Emily H. Guseman ◽  
Kimbo E. Yee ◽  
...  
Keyword(s):  
Physical Activity ◽  
High Risk ◽  
Screen Time ◽  
Pediatric Obesity ◽  
Healthy Lifestyle ◽  
Low Cost ◽  
Vigorous Physical Activity ◽  
Management Program ◽  
Dietary Behaviors ◽  
Lifestyle Behaviors

This paper describes FitKids360, a stage 2 pediatric weight management program. FitKids360 is a physician-referred, multicomponent, low-cost healthy lifestyle program for overweight and obese youth 5–16 years of age and their families. FitKids360 provides an evidence-based approach to the treatment of pediatric overweight by targeting patients’ physical activity, screen time, and dietary behaviors using a family-centered approach. The intervention begins with a two-hour orientation and assessment period followed by six weekly sessions. Assessments include lifestyle behaviors, anthropometry, and the Family Nutrition and Physical Activity (FNPA) survey, which screens for obesogenic risk factors in the home environment. Outcomes are presented from 258 patients who completed one of 33 FitKids360 classes. After completing FitKids360, patients increased moderate to vigorous physical activity by 14 minutes (P=0.019), reduced screen time by 44 minutes (P<0.001), and improved key dietary behaviors. Overall, FNPA scores increased by 9% (P<0.001) and 69% of patients with “high risk” FNPA scores at baseline dropped below the “high risk” range by followup. Patients also lowered BMIs (P=0.011) and age- and sex-adjusted BMIz-scores (P<0.001) after completing the 7-week program. We hope this report will be useful to medical and public health professionals seeking to develop stage 2 pediatric obesity programs.

scholarly journals Physical activity attenuates postprandial hyperglycaemia in homozygous TBC1D4 loss-of-function mutation carriers

Diabetologia ◽  
2021 ◽  
Author(s):  
Theresia M. Schnurr ◽  
Emil Jørsboe ◽  
Alexandra Chadt ◽  
Inger K. Dahl-Petersen ◽  
Jonas M. Kristensen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Precision Medicine ◽  
Plasma Glucose ◽  
Autoimmune Diabetes ◽  
Vigorous Physical Activity ◽  
Genetic Admixture ◽  
Oral Glucose ◽  
Loss Of Function ◽  
Risk Variant ◽  
Glucose Levels

Abstract Aims/hypothesis The common muscle-specific TBC1D4 p.Arg684Ter loss-of-function variant defines a subtype of non-autoimmune diabetes in Arctic populations. Homozygous carriers are characterised by elevated postprandial glucose and insulin levels. Because 3.8% of the Greenlandic population are homozygous carriers, it is important to explore possibilities for precision medicine. We aimed to investigate whether physical activity attenuates the effect of this variant on 2 h plasma glucose levels after an oral glucose load. Methods In a Greenlandic population cohort (n = 2655), 2 h plasma glucose levels were obtained after an OGTT, physical activity was estimated as physical activity energy expenditure and TBC1D4 genotype was determined. We performed TBC1D4–physical activity interaction analysis, applying a linear mixed model to correct for genetic admixture and relatedness. Results Physical activity was inversely associated with 2 h plasma glucose levels (β[main effect of physical activity] −0.0033 [mmol/l] / [kJ kg−1 day−1], p = 6.5 × 10−5), and significantly more so among homozygous carriers of the TBC1D4 risk variant compared with heterozygous carriers and non-carriers (β[interaction] −0.015 [mmol/l] / [kJ kg−1 day−1], p = 0.0085). The estimated effect size suggests that 1 h of vigorous physical activity per day (compared with resting) reduces 2 h plasma glucose levels by an additional ~0.7 mmol/l in homozygous carriers of the risk variant. Conclusions/interpretation Physical activity improves glucose homeostasis particularly in homozygous TBC1D4 risk variant carriers via a skeletal muscle TBC1 domain family member 4-independent pathway. This provides a rationale to implement physical activity as lifestyle precision medicine in Arctic populations. Data repository The Greenlandic Cardio-Metabochip data for the Inuit Health in Transition study has been deposited at the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/dacs/EGAC00001000736) under accession EGAD00010001428. Graphical abstract

scholarly journals Clustering of multiple lifestyle behaviors among migrant, left-behind and local adolescents in China: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li He ◽  
Xiaoyan Li ◽  
Weidong Wang ◽  
Youfa Wang ◽  
Haiyan Qu ◽  
...  
Keyword(s):  
Physical Activity ◽  
High Risk ◽  
Vegetable Consumption ◽  
Vigorous Physical Activity ◽  
Low Risk ◽  
Lifestyle Behaviors ◽  
Migrant Status ◽  
Moderate Risk ◽  
Cross Sectional ◽  
Left Behind

Abstract Background Influence of migration on externalized behavioral problems (e.g., aggressive) among adolescents has been well assessed, yet lifestyle behaviors of migrant, left-behind and local adolescents have been largely overlooked by researchers and policy-makers. Therefore, this study aimed to identify clustering of multiple lifestyle behaviors and their associations with migrant status among Chinese adolescents. Methods A cross-sectional survey was conducted in 2015 in Beijing, and Wuhu city (Anhui province). Adolescents self-reported age, gender, family economic status, migrant situation, and lifestyle behaviors (i.e., physical activity, screen time, sleep, smoke, soft-drink, alcohol, fruit and vegetable consumption) via a battery of validated questionnaires. Latent class analysis was conducted to identify behavioral clusters using Mplus 7.1. ANOVA, and multivariable logistic regression were used to examine associations between migrant situations and behavioral clusters using SPSS 22. Results Three distinct behavioral clusters were exhibited among 1364 students (mean age: 13.41 ± 0.84 years): “low risk” (N = 847), “moderate risk” (N = 412) and “high risk” (N = 105). The “high-risk” cluster had the highest prevalence of adolescents not meeting healthy behavioral recommendations. There were no significant differences in the prevalence of high-risk lifestyle among migrant, left-behind, rural local and urban local adolescents. But migrant adolescents had the lowest prevalence of low-risk lifestyle, followed by left-behind, rural and urban local adolescents. Moreover, compared with urban local, migrant (OR = 2.72, 95%CI: 1.88,3.94), left-behind (OR = 2.28, 95%CI: 1.46, 3.55), and rural local (OR = 1.76, 95%CI:1.03,3.01) adolescents had a higher risk of moderate-risk lifestyle. Conclusions Clustering of assessed lifestyle behaviors differed by the migrant status. Particularly, migrant and left-behind adolescents were more likely to have moderate-risk lifestyle compared with their counterparts. Interventions that promote moderate to vigorous physical activity and consumption of fruits and vegetables simultaneously are needed among them.

scholarly journals Comparison Between Glycemic Variability Values Calculated From Professional-CGM and Glycemic Variability Values Calculated From Personal-CGM

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A330-A330
Author(s):  
Soichi Takeishi ◽  
Tatsuo Inoue
Keyword(s):  
Glycemic Variability ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Time Calibration ◽  
Sensor Glucose ◽  
Time In Range ◽  
The Individual ◽  
A Prospective Study ◽  
Relative Differences ◽  
Mean Glucose

Abstract It is important whether the differences between glycemic variability (GV) values calculated from professional CGM and GV values calculated from personal CGM are acceptable when using professional CGM data and personal CGM data together in studies. This is a prospective study. 41 inpatients with type 2 diabetes wore professional CGM (iPro2) and personal CGM (GUARDIAN CONNECT) in parallel for 6 days (CGM attachment: day 1). Each CGM were calibrated 22 times from day 2 to day 5, on the same timing in all patients (n of calibration = 902). Four 24 h GV from day 2 to day 5 per patient were evaluated (n of 24 h GV = 164) on each CGM. There were no significant differences between the standard deviation on professional CGM and that on personal CGM (32.2 mg/dL vs 32.8 mg/dL, p = 0.21). For time in range (70–180 mg/dL) [TIR 70–180], mean glucose levels and coefficient of variation (CV), the values were numerically almost equal between GV on professional CGM and that on personal CGM. However, for TIR 70–180 and CV, the GV on professional CGM was statistically significantly lower than that on personal CGM (70.8 % vs 72.5 %, p = 0.002, 20.6 % vs 21.3 %, p = 0.04); and for mean glucose levels, the GV on professional CGM was statistically significantly higher than that on personal CGM (157.7 mg/dL vs 155.2 mg/dL, p &lt; 0.001). For mean absolute glucose (MAG) and glycemic variability percentage (GVP), the GV on professional CGM was significantly lower than that on personal CGM (25.3 mg/dL/h vs 41.0 mg/dL/h, p &lt; 0.001, 14.4 % vs 31.1 %, p &lt; 0.001). The calibrations, whose blood glucose levels (BG) were higher than ‘sensor glucose levels just before the BG’ (SGjb), were more than those, whose BG were lower than SGjb (482 times vs 420 times). The mean absolute relative differences on professional CGM were significantly lower than those on personal CGM (5.0 % vs 6.3 %, p &lt; 0.001). The study patients correlated to distributions of ‘ratio of CV on personal CGM to CV on professional CGM on the same day’ (correlation ratio: η 2 = 0.48, p &lt; 0.001). The results of TIR 70–180 and mean glucose levels may have been caused by the fact that the calibration BG were high dissociated from SGjb and algorithm of professional CGM is easier to allow the dissociation than that of personal CGM. The results of CV may have been caused by the individual differences in sensor accuracy between professional CGM and personal CGM. The results of MAG and GVP may have been caused by the fact that personal CGM can reveal detailed glycemic variability which cannot be revealed by professional CGM, due to real time calibration. According to purpose of studies, it should be determined whether using professional CGM data and personal CGM data together is acceptable.

scholarly journals Time in range is a tool for assessing the quality of glycemic control in diabetes

2021 ◽  
Vol 24 (3) ◽  
pp. 282-290
Author(s):  
L. A. Suplotova ◽  
A. S. Sudnitsyna ◽  
N. V. Romanova ◽  
M. V. Shestakova
Keyword(s):  
Glycemic Control ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Macrovascular Complications ◽  
International Consensus ◽  
Glucose Levels ◽  
Target Values ◽  
Patients With Diabetes ◽  
Time In Range ◽  
Diagnostic Capabilities

The presence of continuous glucose monitoring (CGM) systems has expanded diagnostic capabilities. The implementation of this technology into clinical practice allowed to determine the patterns and tendencies of excursions in glucose levels, to obtain reliable data concerning short-term glycemic control. Taking into consideration the large amount of obtained information using CGM systems, more than 30 different indicators characterizing glycemic variability were proposed. However, it is very difficult for a practitioner to interpret the data obtained due to the variety of indicators and the lack of their target values. The first step in the standardization of indices was the creation of the International Guidelines for CGM in 2017, where the Time in Range (TIR) (3,9–10,0 mmol/l, less often 3,9–7,8 mmol/l) was significant. To complement the agreed parameters and simplify the interpretation of obtained data using CGM, in 2019 the recommendations were prepared for the International Consensus on Time in Range, where TIR was validated as an additional component of the assessment of glycemic control along with HbA1c. In the literature review the issues of the association of TIR with the development of micro- and macrovascular complications in type 1 and 2 diabetes are considered. The relationship with other indicators of the glycemic control assessment was also analyzed and the dependence of insulin therapy on TIR was shown. TIR is a simple and convenient indicator, it has a proven link with micro- and macrovascular complications of diabetes and can be recommended as a new tool for assessing the glycemic control. The main disadvantage of TIR usage is the insufficient apply of CGM technology by the majority of patients with diabetes.

Low-carbohydrate-diet and maternal glucose metabolism in Chinese pregnant women

2020 ◽  
pp. 1-22
Author(s):  
Qian Chen ◽  
Yajun Chen ◽  
Weijia Wu ◽  
Nu Tang ◽  
Dongyu Wang ◽  
...  
Keyword(s):  
Glucose Metabolism ◽  
Pregnant Women ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Dietary Intakes ◽  
Glucose Levels ◽  
Low Carbohydrate Diet ◽  
Low Carbohydrate ◽  
Mixed Regression ◽  
Maternal Glucose

Abstract Few studies have suggested that long-term adherence to low-carbohydrate diets (LCD) may affect maternal glucose metabolism in western countries. We aimed to investigate the association between LCD during pregnancy and glucose metabolism in Chinese population. A total of 1,018 women in mid-pregnancy were recruited in 2017-2018. Participants underwent a 75g oral glucose tolerance test (OGTT). Daily dietary intakes over the past month were accessed using a validated food frequency questionnaire. The overall, animal, and vegetable LCD scores which represent adherence to different low-carbohydrate dietary patterns were calculated. Mixed linear regression and generalized linear mixed regression were conducted to evaluate the associations between LCD scores and maternal glucose metabolism. Of the 1,018 subjects, 194 (19.1%) was diagnosed with gestational diabetes mellitus (GDM). The overall LCD score (β: 0.024, standard error (SE): 0.008, PFDR=0.02) and animal LCD score (β: 0.023, SE: 0.008, PFDR=0.02) was positively associated with OGTT 1-h glucose. No significant associations were found between the three different LCD scores with fasting plasma glucose (FPG), OGTT 2-h glucose, or insulin resistance, respectively. Compared with the lowest quartile, the crude odds ratios of GDM for the highest quartile were 1.84 (95% CI: 1.14, 2.95) for overall LCD score (P for trend = 0.02) and 1.56 (1.00, 2.45) for animal LCD score (P for trend = 0.02). However, these associations became nonsignificant after adjustment for covariates. In conclusion, a low-carbohydrate dietary pattern with high animal protein and fat is associated with higher postprandial 1-h glucose levels in Chinese pregnant women.

scholarly journals Associations between physical activity and trimethylamine N-oxide in those at risk of type 2 diabetes

2020 ◽  
Vol 8 (2) ◽  
pp. e001359
Author(s):  
Stavroula Argyridou ◽  
Dennis Bernieh ◽  
Joseph Henson ◽  
Charlotte L Edwardson ◽  
Melanie J Davies ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
High Risk ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Estimating Equation ◽  
Cardiometabolic Health ◽  
Light Physical Activity ◽  
Design And Methods

IntroductionTrimethylamine N-oxide (TMAO) has been identified as a novel gut-derived molecule that is associated with the risk of cardiometabolic diseases. However, the relationship between TMAO and physical activity is not well understood. This study prospectively investigates the association between TMAO and objectively assessed physical activity in a population at high risk of type 2 diabetes mellitus.Research design and methodsBaseline and 12-month follow-up data were used from the Walking Away from Type 2 Diabetes trial, which recruited adults at high risk of type 2 diabetes from primary care in 2009–2010. TMAO was analyzed using targeted mass spectrometry. Generalized estimating equation models with an exchangeable correlation structure were used to investigate the associations between accelerometer-assessed exposures (sedentary time, light physical activity, moderate to vigorous physical activity (MVPA)) and TMAO, adjusting for demographic, clinical and lifestyle factors in varying degrees.ResultsOverall, 483 individuals had plasma samples available for the analysis of TMAO (316 (65.4%) men, 167 (34.6%) women), contributing 886 observations to the analysis. MVPA (min/day) was associated with TMAO in all models. In the fully adjusted model, each 30 min or SD difference in MVPA was associated with 0.584 μmol/L (0.070, 1.098) and 0.456 μmol/L (0.054, 0.858) lower TMAO, respectively. Sedentary time and light physical activity were not associated with TMAO in any model.ConclusionsEngagement with MVPA was associated with lower TMAO levels, suggesting a possible new mechanism underlining the inverse relationship between physical activity and cardiometabolic health.

Sign in / Sign up

Export Citation Format

Share Document