scholarly journals A prospective study of the relationships between movement and glycemic control during day and night in pregnancy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Masoud Behravesh ◽  
Juan Fernandez-Tajes ◽  
Angela C. Estampador ◽  
Tibor V. Varga ◽  
Ómar S. Gunnarsson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Glycemic Control ◽  
Sleep Disturbance ◽  
Time Of Day ◽  
Rate Of Change ◽  
Total Movement ◽  
Interaction Term ◽  
Continuous Glucose Monitors ◽  
A Prospective Study ◽  
In Pregnancy

AbstractBoth disturbed sleep and lack of exercise can disrupt metabolism in pregnancy. Accelerometery was used to objectively assess movement during waking (physical activity) and movement during sleeping (sleep disturbance) periods and evaluated relationships with continuous blood glucose variation during pregnancy. Data was analysed prospectively. 15-women without pre-existing diabetes mellitus wore continuous glucose monitors and triaxial accelerometers from February through June 2018 in Sweden. The relationships between physical activity and sleep disturbance with blood glucose rate of change were assessed. An interaction term was fitted to determine difference in the relationship between movement and glucose variation, conditional on waking/sleeping. Total movement was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.037, − 0.026)). Stratified analyses showed total physical activity was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.040, − 0.028)), whereas sleep disturbance was not related to glucose rate of change (p = 0.07, 95% CI (< − 0.001, 0.013)). The interaction term was positively related to glucose rate of change (p < 0.001, 95% CI (0.029, 0.047)). This study provides temporal evidence of a relationship between total movement and glycemic control in pregnancy, which is conditional on time of day. Movement is beneficially related with glycemic control while awake, but not during sleep.

scholarly journals Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5386 ◽  
Author(s):  
Chiara Fabris ◽  
Basak Ozaslan ◽  
Marc D. Breton
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
University Of Virginia ◽  
Percent Time ◽  
Activity Trackers ◽  
Continuous Glucose Monitors ◽  
The University

Objective: Suboptimal insulin dosing in type 1 diabetes (T1D) is frequently associated with time-varying insulin requirements driven by various psycho-behavioral and physiological factors influencing insulin sensitivity (IS). Among these, physical activity has been widely recognized as a trigger of altered IS both during and following the exercise effort, but limited indication is available for the management of structured and (even more) unstructured activity in T1D. In this work, we present two methods to inform insulin dosing with biosignals from wearable sensors to improve glycemic control in individuals with T1D. Research Design and Methods: Continuous glucose monitors (CGM) and activity trackers are leveraged by the methods. The first method uses CGM records to estimate IS in real time and adjust the insulin dose according to a person’s insulin needs; the second method uses step count data to inform the bolus calculation with the residual glucose-lowering effects of recently performed (structured or unstructured) physical activity. The methods were tested in silico within the University of Virginia/Padova T1D Simulator. A standard bolus calculator and the proposed “smart” systems were deployed in the control of one meal in presence of increased/decreased IS (Study 1) and following a 1-hour exercise bout (Study 2). Postprandial glycemic control was assessed in terms of time spent in different glycemic ranges and low/high blood glucose indices (LBGI/HBGI), and compared between the dosing strategies. Results: In Study 1, the CGM-informed system allowed to reduce exposure to hypoglycemia in presence of increased IS (percent time < 70 mg/dL: 6.1% versus 9.9%; LBGI: 1.9 versus 3.2) and exposure to hyperglycemia in presence of decreased IS (percent time > 180 mg/dL: 14.6% versus 18.3%; HBGI: 3.0 versus 3.9), tending toward optimal control. In Study 2, the step count-informed system allowed to reduce hypoglycemia (percent time < 70 mg/dL: 3.9% versus 13.4%; LBGI: 1.7 versus 3.2) at the cost of a minor increase in exposure to hyperglycemia (percent time > 180 mg/dL: 11.9% versus 7.5%; HBGI: 2.4 versus 1.5). Conclusions: We presented and validated in silico two methods for the smart dosing of prandial insulin in T1D. If seen within an ensemble, the two algorithms provide alternatives to individuals with T1D for improving insulin dosing accommodating a large variety of treatment options. Future work will be devoted to test the safety and efficacy of the methods in free-living conditions.

scholarly journals The Interplay Between Diet Quality and Pre-pregnancy Body Mass Index on Glycemic Parameters in Pregnancy: A Comparison of Various Diet Quality Scores (OR35-02-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Karen Lindsay ◽  
Claudia Buss ◽  
Sonja Entringer ◽  
Pathik Wadhwa
Keyword(s):  
Body Mass Index ◽  
Glycemic Control ◽  
Pregnant Women ◽  
Body Mass ◽  
Diet Quality ◽  
Healthy Eating Index ◽  
Quality Score ◽  
Obese Women ◽  
Interaction Term ◽  
In Pregnancy

Abstract Objectives Nutrition in pregnancy plays an important role in maintaining glycemic control but there is no consensus on how to characterize maternal diet quality with respect to glycemic outcomes. The objective of this study is to compare the associations between 4 indices of diet quality with biomarkers of glycemic control (insulin, homeostasis model of insulin resistance (HOMA-IR)) in pregnancy, and to determine whether associations vary as a function of pre-pregnancy body mass index (pBMI). Methods In a prospective longitudinal study of N = 220 pregnant women, dietary intakes were assessed at 3 time points across gestation by 3 × 24h-diet recalls per assessment, from which 4 validated diet quality scores were derived: Dietary Approaches to Stop Hypertension (DASH), Alternative Healthy Eating Index for Pregnancy (AHEI-P), Mediterranean Diet Score (MDS), Dietary Inflammatory Index (DII). Fasting blood samples collected at each assessment were assayed for insulin and glucose and HOMA-IR was computed. pBMI was computed from self-reported pre-pregnancy weight and measured height. Linear regression models predicting mean pregnancy values of insulin and HOMA-IR by diet quality score and pBMI and the diet quality*pBMI interaction term were computed. Results pBMI is strongly predictive of insulin and HOMA-IR and each diet quality score exerts similar significant main effects on glycemic parameters (Table 1). Only the DII*pBMI interaction term was significantly associated with insulin and HOMA-IR (Table 2). Figures 1A and 1B depict that the effect of DII on glycemic control is most pronounced for women with a pBMI < 25.0 Kg/m2, while levels among overweight and obese women remain relatively stable regardless of the inflammatory profile of the diet. Neither DASH, MDS or AHEI-P showed a significant effect on glycemic markers when analyzed as a function of pBMI. Conclusions Although each of the examined diet quality scores may serve as crude predictors of glycemic control in pregnancy, only the DII detected significant differential effects as a function of pBMI. A more pro-inflammatory diet in normal weight pregnant women may exert a stronger influence on glycemic control compared to overweight and obese women, likely attributed to the overriding effects of excess adiposity on dysglycemia. Funding Sources National Institutes of Health: NICHD, NIMHD, NIMH. Supporting Tables, Images and/or Graphs

Does physical activity in leisure time early in pregnancy reduce the incidence of preeclampsia or gestational hypertension?

2010 ◽  
Vol 89 (2) ◽  
pp. 261-267 ◽  
Author(s):  
KARLIJN C. VOLLEBREGT ◽  
HANS WOLF ◽  
KEES BOER ◽  
MARCEL F. VAN DER WAL ◽  
TANJA G.M. VRIJKOTTE ◽  
...  
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Gestational Hypertension ◽  
In Pregnancy

scholarly journals Factors Associated with Poor Glycemic Control Amongst Rural Residents with Diabetes in Korea

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 391
Author(s):  
Junhee Ahn ◽  
Youngran Yang
Keyword(s):  
Physical Activity ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Fasting Blood Glucose ◽  
Regular Physical Activity ◽  
Poor Glycemic Control ◽  
Rural Residents ◽  
Factors Associated ◽  
The Poor ◽  
Positive Urine

(1) Background: Glycemic control is an effective way to reduce the cardiovascular complications of diabetes. The purpose of this study was to identify the factors associated with poor glycemic control amongst rural residents with diabetes in Korea. (2) Methods: This cross-sectional analysis was conducted amongst a total of 522 participants who had completed baseline health examinations for the Korean Genome and Epidemiology Study (KoGES) Rural Cohort from 2005 to 2011. The subjects were divided into two groups: the good glycemic control group (GCG) (glycosylated hemoglobin (HbA1C) < 7%) and the poor GCG (HbA1C ≥ 7%). Logistic regression was used to examine the role of sociodemographics, health-related behavior, comorbidity and diabetes-related and clinical factors in poor glycemic control amongst rural residents with diabetes. (3) Results: In total, 48.1% of participants were in the poor GCG. Poor GCG was significantly associated with drinking (odds ratio (OR) = 0.42, 95% CI = 0.24–0.71), lack of regular physical activity (OR = 1.68, 95% CI = 1.03–2.76), fasting blood glucose (FBG) > 130 mg/dL (OR = 7.80, 95% CI = 4.35–13.98), diabetes for > 7 years (OR = 1.79, 95% CI = 1.08–2.98), cholesterol ≥ 200 mg/dL (OR = 1.73, 95% CI = 1.05–2.84) and positive urine glucose (OR = 6.24, 95% CI = 1.32–29.44). (4) Conclusion: Intensive glucose control interventions should target individuals amongst rural residents with diabetes who do not engage in regular physical activity, have been diagnosed with diabetes for more than seven years and who have high fasting-blood glucose, high cholesterol levels and glucose-positive urine.

scholarly journals Diet and physical activity in pregnancy to prevent gestational diabetes: a protocol for an individual participant data (IPD) meta-analysis on the differential effects of interventions with economic evaluation

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e048119
Author(s):  
Dyuti Coomar ◽  
Jonathan M Hazlehurst ◽  
Frances Austin ◽  
Charlie Foster ◽  
Graham A Hitman ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cost Effectiveness ◽  
Gestational Diabetes ◽  
Systematic Reviews ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Randomised Trials ◽  
Diet And Physical Activity ◽  
Individual Participant ◽  
In Pregnancy

IntroductionMothers with gestational diabetes mellitus (GDM) are at increased risk of pregnancy-related complications and developing type 2 diabetes after delivery. Diet and physical activity-based interventions may prevent GDM, but variations in populations, interventions and outcomes in primary trials have limited the translation of available evidence into practice. We plan to undertake an individual participant data (IPD) meta-analysis of randomised trials to assess the differential effects and cost-effectiveness of diet and physical activity-based interventions in preventing GDM and its complications.MethodsThe International Weight Management in Pregnancy Collaborative Network database is a living repository of IPD from randomised trials on diet and physical activity in pregnancy identified through a systematic literature search. We shall update our existing search on MEDLINE, Embase, BIOSIS, LILACS, Pascal, Science Citation Index, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects and Health Technology Assessment Database without language restriction to identify relevant trials until March 2021. Primary researchers will be invited to join the Network and share their IPD. Trials including women with GDM at baseline will be excluded. We shall perform a one and two stage random-effect meta-analysis for each intervention type (all interventions, diet-based, physical activity-based and mixed approach) to obtain summary intervention effects on GDM with 95% CIs and summary treatment–covariate interactions. Heterogeneity will be summarised using I2 and tau2 statistics with 95% prediction intervals. Publication and availability bias will be assessed by examining small study effects. Study quality of included trials will be assessed by the Cochrane Risk of Bias tool, and the Grading of Recommendations, Assessment, Development and Evaluations approach will be used to grade the evidence in the results. A model-based economic analysis will be carried out to assess the cost-effectiveness of interventions to prevent GDM and its complications compared with usual care.Ethics and disseminationEthics approval is not required. The study is registered on the International Prospective Register of Systematic Reviews (CRD42020212884). Results will be submitted for publication in peer-reviewed journals.

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