The Impact of Self-monitoring of Blood Glucose on a Behavioral Weight Loss Intervention for Patients With Type 2 Diabetes

2012 ◽  
Vol 39 (3) ◽  
pp. 397-405 ◽  
Author(s):  
Lisa M. McAndrew ◽  
Melissa A. Napolitano ◽  
Leonard M. Pogach ◽  
Karen S. Quigley ◽  
Kerri Leh Shantz ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Weight Loss ◽  
Blood Glucose ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention ◽  
The Impact

scholarly journals Frequency of self-monitoring of blood glucose in relation to weight loss and A1C during intensive multidisciplinary weight management in patients with type 2 diabetes and obesity

2019 ◽  
Vol 7 (1) ◽  
pp. e000659 ◽  
Author(s):  
Shaheen Tomah ◽  
Noor Mahmoud ◽  
Adham Mottalib ◽  
David M Pober ◽  
Mhd Wael Tasabehji ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Weight Loss ◽  
Body Weight ◽  
Blood Glucose ◽  
Weight Management ◽  
Average Frequency ◽  
Baseline Body Mass Index ◽  
Self Monitoring ◽  
Median Change

ObjectiveWe evaluated the relationship between frequency of self-monitoring of blood glucose (SMBG) and body weight, A1C, and cardiovascular risk factors in patients with type 2 diabetes (T2D) and obesity enrolled in a 12-week intensive multidisciplinary weight management (IMWM) program.Research design and methodsWe conducted a retrospective analysis of 42 patients who electronically uploaded their SMBG data over 12 weeks of an IMWM program and divided them into tertiles based on their average frequency of SMBG per day. Mean (range) SMBG frequencies were 2.3 (1.1–2.9) times/day, 3.4 (3–3.9) times/day, and 5 (4–7.7) times/day in the lowest, middle, and highest tertiles, respectively. Anthropometric and metabolic parameters were measured at baseline and after 12 weeks of intervention.ResultsParticipants in the highest tertile achieved a median change (IQR) in body weight of −10.4 kg (−7.6 to −14.4 kg) compared with −8.3 kg (−5.2 to −12.2 kg), and −6.9 kg (−4.2 to −8.9 kg) in the middle and lowest tertiles, respectively (p=0.018 for trend). Participants in the highest tertile had a median change (IQR) in A1C of −1.25% (−0.6 to −3.1%) compared with −0.8% (−0.3% to −2%) and −0.5% (−0.2% to −1.2%) in the middle and lowest tertiles, respectively (p=0.048 for trend). The association between change in body weight and SMBG frequency remained significant after adjusting for age, sex, baseline body mass index, diabetes duration, and use of insulin therapy.ConclusionsIncreased frequency of SMBG during IMWM is associated with significantly better weight loss and improvement of A1C in patients with T2D and obesity. These findings may suggest future clinical recommendations aimed at increasing SMBG frequency to achieve the most favorable outcomes.

scholarly journals Defining Valid Activity Monitor Data: A Multimethod Analysis of Weight-Loss Intervention Participants’ Barriers to Wear and First 100 Days of Physical Activity

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Stephanie L. Orstad ◽  
Lauren Gerchow ◽  
Nikhil R. Patel ◽  
Meghana Reddy ◽  
Christina Hernandez ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Low Income ◽  
Activity Monitor ◽  
Accelerometer Data ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention ◽  
Monitor Data

Despite the popularity of commercially available wearable activity monitors (WAMs), there is a paucity of consistent methodology for analyzing large amounts of accelerometer data from these devices. This multimethod study aimed to inform appropriate Fitbit wear thresholds for physical activity (PA) outcomes assessment in a sample of 616 low-income, majority Latina patients with obesity enrolled in a behavioral weight-loss intervention. Secondly, this study aimed to understand intervention participants’ barriers to Fitbit use. We applied a heart rate (HR) criterion (≥10 h/day) and a step count (SC) criterion (≥1000 steps/day) to 100 days of continuous activity monitor data. We examined the prevalence of valid wear and PA outcomes between analytic subgroups of participants who met the HR criterion, SC criterion, or both. We undertook qualitative analysis of research staff notes and participant interviews to explore barriers to valid Fitbit data collection. Overall, one in three participants did not meet the SC criterion for valid wear in Weeks 1 and 13; however, we found the SC criterion to be more inclusive of participants who did not use a smartphone than the HR criterion. Older age, higher body mass index (BMI), barriers to smartphone use, device storage issues, and negative emotional responses to WAM-based self-monitoring may predict higher proportions of invalid WAM data in weight-loss intervention research.

Model estimates of the results of diabetes patients using modern glucometers with tri-color technology for displaying test results

2019 ◽  
pp. 81-89
Author(s):  
Larisa Dmitrievna Popovich ◽  
Svetlana Valentinovna Svetlichnaya ◽  
Aleksandr Alekseevich Moiseev
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Economic Benefits ◽  
Test Results ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Impact

Diabetes – a disease in which the effect of the treatment substantially depends on the patient. Known a study showed that the use of glucometers with the technology of three-color display of test results facilitates self-monitoring of blood sugar and leads to a decrease in glycated hemoglobin (HbAlc). Purpose of the study: to modeling the impact of using of a glucometer with a color-coded display on the clinical outcomes of diabetes mellitus and calculating, the potential economic benefits of reducing the hospitalization rate of patients with diabetes. Material and methods. Based on data from two studies (O. Schnell et al. and M. Baxter et al.) simulation of the reduction in the number of complications with the use of a glucometer with a color indication. In a study by O. Schnell et al. a decrease of HbA1c by 0.69 percent is shown when using the considered type of glucometers, which was the basis of the model. Results. In the model, the use of a glucometer with a color-coded display for type 1 diabetes led to a decrease in the total number of complications by 9.2 thousand over 5 years per a cohort of 40 thousand patients with different initial levels of HbA1c. In a cohort of 40 thousand patients with type 2 diabetes, the simulated number of prevented complications was 1.7 thousand over 5 years. When extrapolating these data to all patients with diabetes included in the federal register of diabetes mellitus (FRD), the number of prevented complications was 55.4 thousand cases for type 1 diabetes and 67.1 thousand cases for type 2 diabetes. The possible economic effect from the use of the device by all patients with a diagnosis of diabetes, which are included in the FRD, estimated at 1.5 billion rubles for a cohort of patients with type 1 diabetes and 5.3 billion rubles for patients with type 2 diabetes. Conclusion. Improving the effectiveness of self-monitoring, which is the result of the use of glucometers with color indicators, can potentially significantly reduce the incidence of complications in diabetes and thereby provide significant economic benefits to society.

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