Correlation between Glycemic Control and Physical Activity Level in Adolescents and Children with Type 1 Diabetes

2015 ◽  
Vol 12 (2) ◽  
pp. 232-237 ◽  
Author(s):  
Cristiane Petra Miculis ◽  
Wagner De Campos ◽  
Margaret Cristina da Silva Boguszewski
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Physical Activity Level ◽  
Activity Level

Correlation Between Glycemic Control and Physical Activity Level in Adolescents and Children With Type 1 Diabetes

2015 ◽  
Vol 12 (2) ◽  
pp. 232-237 ◽  
Author(s):  
Cristiane Petra Miculis ◽  
Wagner De Campos ◽  
Margaret Cristina da Silva Boguszewski
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Physical Activity Level ◽  
Sedentary Time ◽  
Insulin Dose ◽  
Fasting Blood Glucose ◽  
Activity Level ◽  
Sleeping Time

Background:The aim of this study was to correlate glycemic control (GC) and variables of physical activity levels (PAL) in children with type 1 diabetes mellitus (T1DM).Methods:Fifty children and adolescents with T1DM were selected. Personal and medical data for the patients were collected. Physical evaluations of body weight and sexual maturation were undertaken. Bouchard’s questionnaire was applied to evaluate PAL as well as for time spent on physical activities.Results:Sixty-four percent of the subjects were sexually mature. Differences were observed between females and males in insulin dose, duration of light physical activity, and sleeping time (P < .05). Ninety percent presented poor GC and 80% had a low PAL. Fasting blood glucose (FBG) was significantly correlated with PAL, with sedentary time, and with sleeping time. Glycated hemoglobin (HbA1c) was significantly correlated with sedentary time and sleeping time. Among the three groups of PAL (insufficient × moderate × active) there were differences in HbA1c (%), FBG (mg/dL), duration of disease (years), and insulin dose (UI/kg/day) (P < 0.001).Conclusion:GC was significantly correlated with PAL. Among the three groups of physical activity level, the most active group was seen to have the best GC.

scholarly journals Physical activity level and hypoglycemia in type 1 diabetes patients

2016 ◽  
Vol 36 (2) ◽  
pp. 59-65
Author(s):  
Camila Kümmel Duarte ◽  
Ticiana C. Rodrigues ◽  
Aline Juliana Schneider Merker ◽  
Fabiane de Oliveira Brauner ◽  
Jussara Carnevale de Almeida
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Physical Activity Level ◽  
Activity Level ◽  
Diabetes Patients

Physical activity level and body composition among adults with Type 1 diabetes

2012 ◽  
Vol 29 (11) ◽  
pp. e402-e408 ◽  
Author(s):  
A. S. Brazeau ◽  
C. Leroux ◽  
H. Mircescu ◽  
R. Rabasa-Lhoret
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Body Composition ◽  
Physical Activity Level ◽  
Activity Level

Association of physical activity level with depression, anxiety, and quality of life in children with type 1 diabetes mellitus

2015 ◽  
Vol 28 (11-12) ◽  
Author(s):  
Ebru Kaya Mutlu ◽  
Caner Mutlu ◽  
Hanifegul Taskiran ◽  
Ilker Tolga Ozgen
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Physical Activity Level ◽  
Activity Level ◽  
Pedsql 4.0

AbstractChildren with type 1 diabetes mellitus (T1DM) have low physical activity levels and are at high risk for psychosocial morbidities, including depression, heightened anxiety and low health-related quality of life (HRQoL).The aim of this study was to assess the associations of physical activity level with depression, anxiety, and HRQoL in children with T1DM.A cross-sectional study design, including children with T1DM aged between 8 and 12 years and healthy controls, was used. Physical activity (PA) level was assessed with the Physical Activity Questionnaire for Older Children (PAQ-C). Anxiety was screened by The Screen for Anxiety Related Emotional Disorders (SCARED) questionnaire. Depressive symptoms were evaluated using the Children’s Depression Inventory (CDI). Quality of life was assessed with the The Pediatric Quality of Life Inventory 4.0 (PedsQL 4.0).Forty-seven T1DM and 55 healthy children were included with mean ages of 9.87±1.63 and 9.56±1.60 years, respectively. The T1DM group had significantly higher depression and anxiety score (p<0.05) and lower HRQoL-child self-report score (p<0.05, for all) compared with the control group. Significant associations were found between PAQ-C and PedsQL 4.0 (p<0.05), between SCARED and PedsQL 4.0 (p<0.05), and between HbA1c and PedsQL 4.0 (p<0.05) in children with T1DM.The result of our study suggested that only HRQoL was related to physical activity, anxiety and HbA1c in children with T1DM.

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.

Dietary intake, body composition, and physical activity among young patients with type 1 diabetes mellitus

2015 ◽  
Vol 28 (7-8) ◽  
Author(s):  
Constanza Mosso ◽  
Victoria Halabi ◽  
Tamara Ortiz ◽  
Maria Isabel Hodgson
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Body Composition ◽  
Dietary Intake ◽  
Type 1 Diabetes Mellitus ◽  
Body Fat ◽  
Activity Level ◽  
The Mean

AbstractThe aim of this study was to assess dietary intake, nutritional status, body composition, and physical activity level in a group of Chilean children and adolescents with Type 1 diabetes mellitus (T1DM), compare these parameters with the recommendations of the International Society for Pediatric and Adolescent Diabetes (ISPAD), and determine the relationships between dietary intake, body composition, and diabetes control.A total of 30 patients with T1DM (aged 15.2±4.0 years) were included. Dietary intake was assessed using a 92-item quantitative food frequency questionnaire. Body composition was determined using dual-energy X-ray densitometry. Physical activity was assessed by means of a survey.The energy intake of these patients was derived from 21.4% protein, 48% carbohydrates, and 31.2% fat. The glycosylated hemoglobin (HbA1c) was significantly correlated with fat as grams per day (r: 0.363, p<0.05) and calories per day (r: 0.364, p<0.05). The mean body fat percentage in females was 31.2% and 20.2% in males (p < 0.01) and the mean amount of physical activity was 4.5±2.7 h per week.The study patients had a higher protein intake than recommended by ISPAD. Dietary carbohydrate intake was rather low, and dietary fat intake was the same as the limits recommended by ISPAD. Diabetic control was significantly correlated with protein, carbohydrates, fat, and sodium intake. The girls in the study had a higher percentage of body fat than the standard recommendations for their age. The level of physical activity was adequate.

Fitness and physical activity in youth with type 1 diabetes mellitus in good or poor glycemic control

2014 ◽  
Vol 16 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Thanh Nguyen ◽  
Joyce Obeid ◽  
Rachel G Walker ◽  
Matthew P Krause ◽  
Thomas J Hawke ◽  
...  
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Type 1 Diabetes Mellitus ◽  
Poor Glycemic Control

Physical activity in adolescents with type 1 diabetes: is more better for glycemic control?

2009 ◽  
Vol 10 (4) ◽  
pp. 231-233 ◽  
Author(s):  
Lisa Younk ◽  
Donna Tate ◽  
Stephen N Davis
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control
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