Supporting the 'lived expertise' of older adults with type 1 diabetes: An applied focus group analysis to characterize barriers, facilitators, and strategies for self-management in a growing and understudied population.

INTRODUCTION: There is a growing number of older adults (≥65 years) who live with type 1 diabetes. We qualitatively explored experiences and perspectives regarding type 1 diabetes self-management and treatment decisions among older adults, focusing on adopting care advances such as continuous glucose monitoring (CGM). METHODS: Among a clinic-based sample of older adults ≥65 years with type 1 diabetes, we conducted a series of literature and expert informed focus groups with structured discussion activities. Groups were transcribed followed by inductive coding, theme identification, and inference verification. Medical records and surveys added clinical information. RESULTS: Twenty nine older adults (age 73.4 ± 4.5 years; 86% CGM users) and four caregivers (age 73.3 ± 2.9 years) participated. Participants were 58% female and 82% non-Hispanic White. Analysis revealed themes related to attitudes, behaviours, and experiences, as well as interpersonal and contextual factors that shape self-management and outcomes. These factors and their interactions drive variability in diabetes outcomes and optimal treatment strategies between individuals as well as within individuals over time (i.e. with ageing). Participants proposed strategies to address these factors: regular, holistic needs assessments to match people with effective self-care approaches and adapt them over the lifespan; longitudinal support (e.g., education, tactical help, sharing and validating experiences); tailored education and skills training; and leveraging of caregivers, family, and peers as resources. CONCLUSIONS: Our study of what influences self-management decisions and technology adoption among older adults with type 1 diabetes underscores the importance of ongoing assessments to address dynamic age-specific needs, as well as individualized multi-faceted support that integrates peers and caregivers.

Disparities in Food Security and Glycemic Control Among People with Type 2 Diabetes During the COVID-19 Pandemic.

Background: Little is known about the differing impacts of food insecurity on HbA1c by race in type 2 diabetes (T2D). Predictions around increased food insecurity from COVID-19 exacerbating racial disparities led us to estimate its prevalence and associations with HbA1c by race during the COVID-19 pandemic. Methods: Data came from medical records and surveys among a clinic-based sample of T2D patients. Linear regression models estimated associations between food insecurity and HbA1c and between change in food insecurity and change in HbA1c. Likelihood ratio tests and examination of stratum-specific estimates assessed effect modification by race. Results: Our sample was 59% White, 59% female, and mean age was 60.8 ± 12.6. During the pandemic, food insecurity prevalence and HbA1c were significantly (p < .05) higher among non-Whites (39%, 8.4% ± 2.1) compared to Whites (15%, 7.8% ±1.6). HbA1c among those who were very food insecure was 1.00% (95% CI: 0.222, 1.762, p = .01) higher than those who were food secure. Those with increased food insecurity had a 0.58% (95% CI: 0.024, 1.128, p = .04) higher HbA1c increase than among those experiencing no change. No effect modification was detected. Limitations: Convenience sampling in an endocrinology clinic, recall bias, and inadequate power may underlie null effect modification results. Conclusion: Although effect modification was not detected, racial disparities in HbA1c and food insecurity warrant further investigation. These disparities, combined with the significant impact of food insecurity on HbA1c, suggest that prioritization of resources to high-risk populations should be considered early during public emergencies to minimize short- and long-term health consequences.

Characterization of youth goal setting in the self-management of type 1 diabetes and associations with HbA1c: The Flexible Lifestyle Empowering Change trial.

INTRODUCTION: Youth with type 1 diabetes (T1D) commonly do not meet HbA1c targets. Youth-directed goal setting as a strategy to improve HbA1c has not been well characterized and associations between specific goal focus areas and glycemic control remain unexplored. OBJECTIVE: To inform future trials, this analysis characterized intended focus areas of youth self-directed goals and examined associations with change in HbA1c over a 18 months. METHODS: We inductively coded counseling session data from youth in the Flexible Lifestyle Empowering Change Intervention (n = 122, 13-16 years, T1D duration >1 year, HbA1c 8-13%) to categorize intended goal focus areas and examine associations between frequency of goal focus areas selected by youth and change in HbA1c between first and last study visit. RESULTS: We identified 13 focus areas that categorized youth goal intentions. Each session where youth goal setting concurrently incorporated blood glucose monitoring (BGM), continuous glucose monitoring (CGM), and insulin dosing was associated with a 0.4% (95% CI: -0.77, -0.01; P = .03) lower HbA1c at the end of intervention participation. No association was observed between HbA1c and frequency of sessions where goal intentions focused on BG only (without addressing insulin or CGM) (ß: 0.07; 95% CI: -0.07, 0.21; P = .33) nor insulin dosing only (without addressing BGM or CGM) (ß: 0.00; 95% CI: -0.11, 0.10; P = .95). CONCLUSIONS: Findings exemplify how guiding youth goal development and combining multiple behaviors proximally related to glycemic control into goal setting may benefit HbA1c among youth with T1D. More research characterizing optimal goal setting practices in youth with T1D is needed.

Dietary intake on days with and without hypoglycemia in youth with type 1 diabetes: The Flexible Lifestyle Empowering Change trial.

OBJECTIVE: To address a common perception that hypoglycemia is associated with increased dietary intake, we examined calorie and carbohydrate consumption on days with and without hypoglycemia among adolescents with type 1 diabetes (T1D). METHODS: Days (N = 274) with 24-hour dietary recalls and continuous glucose monitoring were available for 122 adolescents with T1D in the Flexible Lifestyle Empowering Change trial (age 13-16 years, diabetes duration >1 year, hemoglobin A1c 8%-13%). Days with no hypoglycemia, clinical hypoglycemia (54-69 mg/dL) or clinically serious hypoglycemia (<54 mg/dL) were further split into night (12-5:59 am) and day (6 am-11:59 pm). Mixed models tested whether intake of calories or carbohydrates was greater on days with than without hypoglycemia. RESULTS: Fifty-nine percent, 23% and 18% of days had no hypoglycemia, clinical hypoglycemia and clinically serious hypoglycemia, respectively. Intake of calories and carbohydrates was not statistically significantly different on days with clinical hypoglycemia (57.2 kcal [95% CI -126.7, 241.5]; 12.6 g carbohydrate [95% CI -12.7, 38.0]) or clinically serious hypoglycemia (-74.0 kcal [95% CI -285.9, 137.9]; (-7.8 g carbohydrate [95% CI -36.8, 21.1]), compared to days without hypoglycemia. Differences by day and night were not statistically significant. CONCLUSIONS: Among adolescents with T1D, daily intake of calories and carbohydrates did not differ on days with and without hypoglycemia. It is possible that hypoglycemic episodes caused by undereating relative to insulin dosing, followed by overeating, leading to a net neutral difference. Given the post-hoc nature of these analyses, larger studies should be designed to prospectively test the hypoglycemia-diet relationship.

Nutritional Status, Dietary Intake, and Nutrition-Related Interventions Among Older Adults With Type 1 Diabetes: A Systematic Review and Call for More Evidence Toward Clinical Guidelines.

There is an emerging population of older adults (≥65 years) living with type 1 diabetes. Optimizing health through nutrition during this life stage is challenged by multiple and ongoing changes in diabetes management, comorbidities, and lifestyle factors. There is a need to understand nutritional status, dietary intake, and nutrition-related interventions that may maximize well-being throughout the life span in type 1 diabetes, in addition to nutrition recommendations from clinical guidelines and consensus reports. Three reviewers used Cochrane guidelines to screen original research (January 1993-2023) and guidelines (2012-2023) in two databases (MEDLINE and CENTRAL) to characterize nutrition evidence in this population. We found limited original research explicitly focused on nutrition and diet in adults ≥65 years of age with type 1 diabetes (six experimental studies, five observational studies) and meta-analyses/reviews (one scoping review), since in the majority of analyses individuals ≥65 years of age were combined with those age ≥18 years, with diverse diabetes durations, and also individuals with type 1 and type 2 diabetes were combined. Further, existing clinical guidelines (n = 10) lacked specificity and evidence to guide clinical practice and self-management behaviors in this population. From a scientific perspective, little is known about nutrition and diet among older adults with type 1 diabetes, including baseline nutrition status, dietary intake and eating behaviors, and the impact of nutrition interventions on key clinical and patient-oriented outcomes. This likely reflects the population's recent emergence and unique considerations. Addressing these gaps is foundational to developing evidence-based nutrition practices and guidelines for older adults living with type 1 diabetes.

A conceptual model of the continuous glucose monitoring integration process for older adults with diabetes developed using participatory systems science methods.

AIMS: Continuous glucose monitoring (CGM) use remains low in older adults. We aimed to develop a conceptual model of CGM integration among older adults with type 1 and type 2 diabetes. METHODS: We previously engaged older adults with type 1 diabetes using participatory system science methods to develop a model of the system of factors that shape CGM integration. To validate and expand the model, we conducted semi-structured interviews with 17 older adults with type 1 and type 2 diabetes and 3 caregivers. Vignettes representing each integration phase were used to elicit outcomes and strategies to support CGM use. Data were analyzed using team-based causal loop diagraming. RESULTS: The model includes six phases spanning (1) CGM uptake; (2) device set-up; acquisition of (3) belief in oneself to use CGM effectively; (4) belief that CGM is preferable to blood glucose monitoring; (5) belief in future CGM benefits CGM; and (6) development of a sense of reliance on CGM. Causal loop diagrams visualize factors and feedback loops shaping outcomes at each phase. Participants proposed support strategies spanning clinical, educational, and behavioral interventions. CONCLUSIONS: The model underscores the complex transition of learning new technology and provides opportunities for tailored support for older adults.

Too Much Dietary Flexibility May Hinder, Not Help: Could More Specific Targets for Daily Food Intake Distribution Promote Glycemic Management among Youth with Type 1 Diabetes?

Average glycemic levels among youth with type 1 diabetes (T1D) have worsened in some parts of the world over the past decade despite simultaneous increased uptake of diabetes technology, thereby highlighting the persistent need to identify effective behavioral strategies to manage glycemia during this life stage. Nutrition is fundamental to T1D management. We reviewed the evidence base of eating strategies tested to date to improve glycemic levels among youth with T1D in order to identify promising directions for future research. No eating strategy tested among youth with T1D since the advent of flexible insulin regimens-including widely promoted carbohydrate counting and low glycemic index strategies-is robustly supported by the existing evidence base, which is characterized by few prospective studies, small study sample sizes, and lack of replication of results due to marked differences in study design or eating strategy tested. Further, focus on macronutrients or food groups without consideration of food intake distribution throughout the day or day-to-day consistency may partially underlie the lack of glycemic benefits observed in studies to date. Increased attention paid to these factors by future observational and experimental studies may facilitate identification of behavioral targets that increase glycemic predictability and management among youth with T1D.

Development and design of the first structured clinic-based program in lower resource settings to transition emerging adults with type 1 diabetes from pediatric to adult care.

INTRODUCTION: Type 1 diabetes (T1D) is increasing in young people worldwide and more children in resource limited settings are living into adulthood. There is a need for rigorous testing and reporting of evidence-based and stakeholder-informed strategies that transition individuals with T1D from pediatric to adult care. We present the development of and design of the first structured transition program in Delhi, India, to inform similar efforts in India and resource limited settings. METHODS: The intervention development team included clinicians and researchers with expertise in T1D and the implementation context. To select intervention outcomes, establish intervention targets, and design session modules, we drew upon formative research conducted at prospective intervention implementation sites, consensus guidelines, and previous care transition and behavior change research conducted in developed settings. We used the Template for Intervention Description and Replication and GUIDance for the rEporting of intervention Development checklists to report the intervention and development process. RESULTS: The 15-month program ("PATHWAY") includes five quarterly ~30 minute sessions delivered predominantly by diabetes educators at pediatric and adult clinics, which coincide with routine care visits. Primary program components include educational and behavioral sessions that address psychosocial drivers of clinic attendance and self-management, diabetes educators as transition coordinators and counselors, and a one-year "overlap period" of alternating visits between pediatric and adult providers. CONCLUSIONS: We followed a systematic and transparent process to develop PATHWAY, which facilitated rich description of intervention context, guiding principles, targets, and components. Dependence on previously published program examples to design PATHWAY may have introduced challenges for program feasibility and effectiveness, underscoring the importance of input gathering from prospective intervention actors at multiple points in the development process. This detailed report in combination with future evaluations of PATHWAY support efforts to increase rigorous development and testing of strategies to improve outcomes among emerging adults with T1D.