Behavioural implications of traditional treatment and closed-loop automated insulin delivery systems in Type 1 diabetes: applying a cognitive restraint theory framework

Body mass index moderates the association between diabetes distress and objective self-management behaviours in adolescents with type 1 diabetes and elevated A1Cs

OBJECTIVE

To examine the cross-sectional associations between diabetes distress, BMI (zBMI; BMI z-score), objectively measured mean daily blood glucose readings and insulin boluses administered, and A1C in adolescents with type 1 diabetes (T1D) using insulin pumps.

METHODS

T1D self-management behaviour data were downloaded from adolescents' (N = 79) devices and mean daily frequency of blood glucose readings and insulin boluses were calculated. Diabetes distress was measured (Problem Areas in Diabetes-Teen questionnaire [PAID-T]), A1C collected, and zBMI calculated from height and weight. Three multiple linear regressions were performed with blood glucose readings, insulin boluses, and A1C as the three dependent variables and covariates (age, T1D duration), zBMI, diabetes distress, and the diabetes distress x zBMI interaction as independent variables.

RESULTS

Participants (55.7% female) were 14.9 ± 1.9 years old with T1D for 6.6 ± 3.4 years. zBMI moderated the relationship between diabetes distress and mean daily insulin boluses administered (b = -0.02, p = 0.02); those with higher zBMI and higher diabetes distress administered fewer daily insulin boluses. zBMI was not a moderator of the association between diabetes distress and blood glucose readings (b = -0.01, p = 0.29) or A1C (b = 0.002, p = 0.81).

CONCLUSIONS

Using objective behavioural data is useful for identifying how adolescent diabetes distress and zBMI affect daily bolusing behaviour amongst adolescent insulin pump users. Although distinct interventions exist to improve T1D self-management or diabetes distress, none addresses them together while considering zBMI. Decreasing diabetes distress could be especially important for youth with high zBMI.

Does Insulin Delivery Technology Change Our Relationship with Foods? A Scoping Review

Introduction: Automated insulin delivery (AID) systems reduce burden and improve glycemic management for people with type 1 diabetes (PwT1D) by automatically adjusting insulin as a response to measured glucose levels. There is a lack of evidence on AID and nutrition variables such as dietary intake, eating behaviors, and disordered eating. Objectives: This scoping review aims to provide a summary of the literature regarding AID and nutrition variables and to identify gaps that require further investigation. Methods: Two researchers conducted a blinded search of Medline (OVID) and PubMed for studies, including AID use (compared to non-AID use) and nutrition variables. Studies from January 2000 to July 2023 were included, as were PwT1D of all ages. Results: A total of 3132 articles were screened for appropriateness. After exclusions, 7 studies were included (2017-2023): 4 qualitative, 1 crossover, 1 randomized controlled, and 1 observational. Studies included adolescents (n = 1), adults (n = 3) or both (n = 2), and all ages (n = 1). In quantitative studies, AID was associated with lower eating distress (-0.43 ± 0.12, P = 0.004) and higher quality of life (3.1, 95% confidence interval [CI]: 0.8-5.4, P = 0.01), but not grams of carbohydrates at meals (1.0; 95% CI: -0.7 to 3.0; P = 0.24) and snacks (0.004; 95% CI: -0.8 to 0.8; P = 0.99) compared to non-AID use. In qualitative studies, AID increased the frequency and portions of food intake and led to less dietary control from parents. AID users reported eating foods higher in energy density. PwT1D were less worried about achieving accurate carbohydrate counting (CC) when using AID. Conclusions: AID use appears to influence eating behaviors, dietary patterns, and CC, although evidence was limited. AID may reduce food management burden due to the perception that AID can correct for CC inaccuracy. Significance: Further research needs to determine if AID allows for simplification of CC and improves eating behaviors while maintaining glycemic stability.

Eating behaviors and estimated body fat percentage among adolescents with type 1 diabetes

AIMS

Estimate associations between select eating behaviors and estimated body fat percentage (eBFP) and explore effect modification by sex among adolescents with type 1 diabetes (T1D).

METHODS

This analysis included 257 adolescents (mean age 14.9 ± 1.14 years; 49.8 % female) with baseline hemoglobin A1c (HbA1c) between 8 and 13 % (64 mmol/mol-119 mmol/mol) from a randomized trial designed to improve glycemia. Eating behaviors and eBFP were determined from surveys and validated equations respectively. Linear mixed models were used to estimate associations. Effect modification was assessed via stratified plots, stratified associations, and interaction terms.

RESULTS

Disordered eating, dietary restraint, and eBFP were significantly higher among females while external eating was higher among males. Disordered eating (β: 0.49, 95 %CI: 0.24, 0.73, p = 0.0001) and restraint (β: 1.11, 95 %CI: 0.29, 1.92, p = 0.0081) were positively associated with eBFP while external eating was not (β: -0.19, 95 %CI: -0.470, 0.096, p = 0.20). Interactions with sex were not significant (p-value range: 0.28-0.64).

CONCLUSION

Disordered eating and dietary restraint were positively associated with eBFP, highlighting the potential salience of these eating behaviors to cardiometabolic risk for both female and male adolescents. Prospective studies should investigate whether these eating behaviors predict eBFP longitudinally to inform obesity prevention strategies in T1D.

The Psychological Implications of Automated Insulin Delivery Systems in Type 1 Diabetes Care

Automated insulin delivery (AID) systems have brought important glycemic benefits to type 1 diabetes management. The present paper provides an overview of their psychological implications. Trials and real-world observational studies report improvements in diabetes-specific quality of life, with qualitative work describing reduced management burden, increased flexibility and improved relationships. Not all experiences are positive, however, evidenced by dropping algorithm use soon after device initiation. Apart from finance and logistics, reasons for discontinuation include technology frustrations, wear-related issues and unmet glycemic and work load expectations. New challenges include distrust in proper AID functioning, overreliance and deskilling, compensatory behaviors to override or trick the system and optimize time in range, and concerns related to wearing multiple devices on the body. Research efforts may focus on incorporating a diversity perspective, updating existing person-reported outcome measures according to new technology developments, addressing implicit or explicit health professional bias in technology access, examining the merits of incorporating stress reactivity in the AID algorithm, and developing concrete approaches for psychological counseling and support related to technology use. An open dialogue with health professionals and peers about expectations, preferences and needs may foster the collaboration between the person with diabetes and the AID system.

Diabetes technologies in people with type 1 diabetes mellitus and disordered eating: A systematic review on continuous subcutaneous insulin infusion, continuous glucose monitoring and automated insulin delivery

AIMS

In this systematic review, we aimed (1) to identify and describe research investigating the use of advanced diabetes technologies (continuous subcutaneous insulin infusion, CSII; continuous glucose monitoring, CGM; automated insulin delivery, AID) in people with type 1 diabetes (T1DM) and disordered eating and (2) to discuss potential (dis)advantages of diabetes technology use in this population, derived from previous research.

METHODS

We conducted a systematic literature search in two electronic databases for English articles published between 2000 and 2020 addressing eating disorders and/or dysfunctional eating behaviours and diabetes technology use in children, adolescents and adults with T1DM (PROSPERO ID CRD42020160244).

RESULTS

Of 70 publications initially identified, 17 were included. Overall, evidence on the use of diabetes technologies in people with T1DM and disordered eating is scarce. The majority of the studies reports findings on CSII in people with T1DM and dysfunctional eating behaviours or eating disorders. Findings predominantly stem from observational data and are, in most cases, secondary findings of the respective studies. Providing the greatest flexibility in diabetes management, CSII may have benefits in disordered eating. CGM data may complement the diagnostic process of disordered eating with a physiological indicator of insulin restriction (i.e. time spent in hyperglycaemia).

CONCLUSIONS

Results on possible (dis)advantages of diabetes technology use in people with T1DM and disordered eating are based on observational data, small pilot trials and anecdotical evidence from case reports. Prospective data from larger samples are needed to reliably determine potential effects of diabetes technology on disordered eating in T1DM.

The impact of using a closed-loop system on food choices and eating practices among people with Type 1 diabetes: a qualitative study involving adults, teenagers and parents

AIMS

We explored whether, how and why moving onto and using a hybrid day-and-night closed-loop system affected people's food choices and dietary practices to better understand the impact of this technology on everyday life and inform recommendations for training and support given to future users.

METHODS

Twenty-four adults, adolescents and parents were interviewed before commencing use of the closed-loop system and following its 3-month use. Data were analysed thematically and longitudinally.

RESULTS

While participants described preparing and/or eating similar meals to those consumed prior to using a closed-loop, many described feeling more normal and less burdened by diabetes in dietary situations. Individuals also noted how the use of this technology could lead to deskilling (less precise carbohydrate counting) and less healthy eating (increased snacking and portion sizes and consumption of fatty, energy-dense foods) because of the perceived ability of the system to deal with errors in carbohydrate counting and address small rises in blood glucose without a corrective dose needing to be administered.

CONCLUSIONS

While there may be quality-of-life benefits to using a closed-loop, individuals might benefit from additional nutritional and behavioural education to help promote healthy eating. Refresher training in carbohydrate counting may also be necessary to help ensure that users are able to undertake diabetes management in situations where the technology might fail or that they take a break from using it.

Disordered Eating Behaviors in Youth and Young Adults With Type 1 or Type 2 Diabetes Receiving Insulin Therapy: The SEARCH for Diabetes in Youth Study

OBJECTIVE

This study examines the prevalence of disordered eating behaviors (DEB) and its associations with glycemic control, insulin sensitivity (IS), and psychosocial functioning in a large, diverse cohort of youth and young adults with type 1 or type 2 diabetes.

RESEARCH DESIGN AND METHODS

In the SEARCH for Diabetes in Youth study, 2,156 youth and young adults with type 1 diabetes (mean ± SD age 17.7 ± 4.3 years; 50.0% female) and 149 youth and young adults with type 2 diabetes (age 21.8 years ± 3.5; 64.4% female) who were receiving insulin therapy completed the Diabetes Eating Problem Survey-Revised (DEPS-R), a self-reported measure for identifying disordered eating. DEB were defined as a DEPS-R score ≥20. Demographic characteristics, clinical measures, and health behaviors of participants with DEB and those without DEB were compared by using t tests.

RESULTS

DEB were observed in 21.2% of participants with type 1 diabetes and 50.3% of participants with type 2 diabetes. Participants encountered challenges in maintaining a healthy weight while controlling their diabetes. For both types of diabetes, individuals with DEB had a significantly higher BMI z score, lower insulin sensitivity, more depressive symptoms, and poorer quality of life than those without DEB. Diabetic ketoacidosis episodes occurred more frequently in youth with type 1 diabetes with DEB compared to those without DEB.

CONCLUSIONS

These findings highlight that DEB are prevalent among youth and young adults with type 1 and type 2 diabetes and who are receiving insulin therapy, and DEB are associated with poorer clinical outcomes and psychosocial well-being. Heightened awareness and early interventions are needed to address DEB for this at-risk population, as are longitudinal studies evaluating the course of DEB and diabetes outcomes.

Macrovascular disease and risk factors in youth with type 1 diabetes: time to be more attentive to treatment?

Cardiovascular disease remains the leading cause of mortality in patients with type 1 diabetes. Although cardiovascular disease complications are rare until adulthood, pathology and early markers can manifest in adolescence. Whereas advances have been made in the management of microvascular complications of type 1 diabetes, similar progress in reducing macrovascular complications has not been made. The reasons for the absence of progress remain incompletely understood, but most likely relate to the long time needed for cardiovascular disease to manifest clinically and hence for risk factor management to show a clinical benefit, thus allowing inertia to prevail for diagnosis and particularly for targeting risk factors. In this Review, we summarise paediatric data on traditional and novel risk factors of cardiovascular disease, provide an overview of data from previous and current clinical trials, discuss future directions in cardiovascular disease research for paediatric patients with type 1 diabetes, and advocate for the early identification and treatment of cardiovascular disease risk factors as recommended in multiple guidelines.

Obesity in Type 1 Diabetes: Pathophysiology, Clinical Impact, and Mechanisms

There has been an alarming increase in the prevalence of obesity in people with type 1 diabetes in recent years. Although obesity has long been recognized as a major risk factor for the development of type 2 diabetes and a catalyst for complications, much less is known about the role of obesity in the initiation and pathogenesis of type 1 diabetes. Emerging evidence suggests that obesity contributes to insulin resistance, dyslipidemia, and cardiometabolic complications in type 1 diabetes. Unique therapeutic strategies may be required to address these comorbidities within the context of intensive insulin therapy, which promotes weight gain. There is an urgent need for clinical guidelines for the prevention and management of obesity in type 1 diabetes. The development of these recommendations will require a transdisciplinary research strategy addressing metabolism, molecular mechanisms, lifestyle, neuropsychology, and novel therapeutics. In this review, the prevalence, clinical impact, energy balance physiology, and potential mechanisms of obesity in type 1 diabetes are described, with a special focus on the substantial gaps in knowledge in this field. Our goal is to provide a framework for the evidence base needed to develop type 1 diabetes-specific weight management recommendations that account for the competing outcomes of glycemic control and weight management.

Intensive Glycemic Treatment During Type 1 Diabetes Pregnancy: A Story of (Mostly) Sweet Success!

Studies from Scotland and Canada confirm large increases in the incidence of pregnancies complicated by pregestational type 1 diabetes (T1D). With this increased antenatal workload comes more specialization and staff expertise, which may be important as diabetes technology use increases. While euglycemia remains elusive and obstetrical intervention (earlier delivery, increased operative deliveries) is increasing, there have been some notable successes in the past 5-10 years. These include a decline in the rates of congenital anomaly (Canada) and stillbirths (U.K.) and substantial reductions in both maternal hypoglycemia (both moderate and severe) across many countries. However, pregnant women with T1D still spend ∼30-45% of the time (8-11 h/day) hyperglycemic during the second and third trimesters. The duration of maternal hyperglycemia appears unchanged in routine clinical care over the past decade. This ongoing fetal exposure to maternal hyperglycemia likely explains the persistent rates of large for gestational age (LGA), neonatal hypoglycemia, and neonatal intensive care unit (NICU) admissions in T1D offspring. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) found that pregnant women using real-time continuous glucose monitoring (CGM) spent 5% less time (1.2 h/day) hyperglycemic during the third trimester, with clinically relevant reductions in LGA, neonatal hypoglycemia, and NICU admissions. This article will review the progress in our understanding of the intensive glycemic treatment of T1D pregnancy, focusing in particular on the recent technological advances in CGM and automated insulin delivery. It suggests that even with advanced diabetes technology, optimal maternal dietary intake is needed to minimize the neonatal complications attributed to postprandial hyperglycemia.

Day-and-Night Closed-Loop Insulin Delivery in a Broad Population of Pregnant Women With Type 1 Diabetes: A Randomized Controlled Crossover Trial

OBJECTIVE

Despite advances in technology, optimal glucose control remains elusive and neonatal complications remain ubiquitous in type 1 diabetes (T1D) pregnancy. Our aim was to examine the safety, efficacy, and longer-term feasibility of day-and-night closed-loop insulin delivery.

RESEARCH DESIGN AND METHODS

We recruited 16 pregnant women (mean [SD]: age 32.8 [5.0] years, T1D duration 19.4 [10.2] years, HbA_1c 8.0% [1.1], and BMI 26.6 [4.4] kg/m²) to an open-label, randomized, crossover trial. Participants completed 28 days of closed-loop and sensor-augmented pump (SAP) insulin delivery separated by a washout period. Afterward, participants could continue to use the closed-loop system up to 6 weeks postpartum. The primary end point was the proportion of time with glucose levels within the target range (63-140 mg/dL).

RESULTS

The proportion of time with glucose levels within target was comparable during closed-loop and SAP insulin delivery (62.3 vs. 60.1% [95% CI -4.1 to 8.3]; P = 0.47). Mean glucose and time spent hyperglycemic >140 mg/dL also did not differ (131.4 vs. 131.4 mg/dL [P = 0.85] and 36.6 vs. 36.1% [P = 0.86], respectively). During closed-loop, fewer hypoglycemic episodes occurred (median 8 [range 1-17] vs. 12.5 [1-53] over 28 days; P = 0.04) and less time at <63 mg/dL (1.6 vs. 2.7%; P = 0.02). Hypoglycemia <50 mg/dL (0.24 vs. 0.47%; P = 0.03) and low blood glucose index (1.0 vs. 1.4; P = 0.01) were lower. Less nocturnal hypoglycemia (2300-0700 h) during closed-loop therapy (1.1 vs. 2.7%; P = 0.008) and a trend toward higher overnight time in target (67.7 vs. 60.6%; P = 0.06) were found.

CONCLUSIONS

Closed-loop insulin delivery was associated with comparable glucose control and significantly less hypoglycemia than SAP therapy. Larger, longer-duration multicenter trials are now indicated to determine clinical efficacy of closed-loop insulin delivery in T1D pregnancy and the impact on neonatal outcomes.

Understanding antagonism and synergism: A qualitative assessment of weight management in youth with Type 1 diabetes mellitus

Aims

No current clinical guidelines focus on weight management in youth with type 1 diabetes mellitus (T1DM). Our aim was to characterize the patient-perceived experience and barriers to weight management in youth with T1DM.

Methods

Participants were recruited from the University of North Carolina (n = 16, 56% female, 60% White, 50% insulin pump users, mean age 14.8 years, mean HbA1c 8.5% (69 mmol/mol)) and the University of Colorado (n = 18, 50% female, 80% white, 53% pump users, mean age 15.3 years, mean HbA1c 9.3% (78 mmol/mol)). Focus groups were stratified by sex and weight status (BMI cutoff = 25). Discussions were guided by a standardized set of questions, audio-taped, transcribed, and analyzed thematically using inductive qualitative methods.

Results

Youth with T1DM expressed four interrelated themes of antagonism between type 1 diabetes and weight management: dysregulated appetite, disruption of blood glucose levels associated with changing diet/exercise, hypoglycemia as a barrier to weight loss, and the overwhelming nature of dual management of weight and glycemic control, and two interrelated themes of synergism: improvement in shared, underlying heath behaviors and exercise as a tool for weight and glycemic control. Variation in emphasis of specific thematic elements was greatest across sex. Youth identified five major components of a weight management program for T1DM: intensified glucose management, healthy diet with known carbohydrate content, exercise, individualization and flexibility, and psychosocial and peer support.

Conclusions

There is critical need for personalized, T1DM-specific weight recommendations to overcome disease-specific barriers to weight management in the context of T1DM.