Dataset Information

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

ABSTRACT:

Background

Despite the widespread clinical perception that hypoglycemia may drive weight gain in youth with type 1 diabetes (T1D), there is an absence of published evidence supporting this hypothesis.

Methods

We estimated the body fat percentage (eBFP) of 211 youth (HbA1c 8.0-13.0%, age 13-16) at baseline, 6, and 18 months of the Flexible Lifestyles Empowering Change trial using validated equations. Group-based trajectory modeling assigned adolescents to sex-specific eBFP groups. Using baseline 7-day blinded continuous glucose monitoring data, "more" vs. "less" percent time spent in hypoglycemia was defined by cut-points using sample median split and clinical guidelines. Adjusted logistic regression estimated the odds of membership in an increasing eBFP group comparing youth with more vs. less baseline hypoglycemia.

Results

More time spent in clinical hypoglycemia (defined by median split) was associated with 0.29 the odds of increasing eBFP in females (95% CI: 0.12, 0.69; p = 0.005), and 0.33 the odds of stable/increasing eBFP in males (95% CI: 0.14, 0.78; p = 0.01).

Conclusions

Hypoglycemia may not be a major driver of weight gain in US youth with T1D and HbA1c ≥8.0. Further studies in different sub-groups are needed to clarify for whom hypoglycemia may drive weight gain and focus future etiological studies and interventions.

Impact

We contribute epidemiological evidence that hypoglycemia may not be a major driver of weight gain in US youth with type 1 diabetes and HbA1c ≥8.0% and highlight the need for studies to prospectively test this hypothesis rooted in clinical perception. Future research should examine the relationship between hypoglycemia and adiposity together with psychosocial, behavioral, and other clinical factors among sub-groups of youth with type 1 diabetes (i.e., who meet glycemic targets or experience a frequency/severity of hypoglycemia above a threshold) to further clarify for whom hypoglycemia may drive weight gain and progress etiological understanding of and interventions for healthy weight maintenance.

SUBMITTER: Sarteau AC

PROVIDER: S-EPMC10958738 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

Sarteau Angelica Cristello AC Kahkoska Anna R AR Crandell Jamie J Igudesman Daria D Corbin Karen D KD Kichler Jessica C JC Maahs David M DM Muntis Frank F Pratley Richard R Seid Michael M Zaharieva Dessi D Mayer-Davis Elizabeth E

Pediatric research 20220622 3

<h4>Background</h4>Despite the widespread clinical perception that hypoglycemia may drive weight gain in youth with type 1 diabetes (T1D), there is an absence of published evidence supporting this hypothesis.<h4>Methods</h4>We estimated the body fat percentage (eBFP) of 211 youth (HbA1c 8.0-13.0%, age 13-16) at baseline, 6, and 18 months of the Flexible Lifestyles Empowering Change trial using validated equations. Group-based trajectory modeling assigned adolescents to sex-specific eBFP groups. ...[more]

PMID: 35729217

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Project description:Excess adiposity is common in youth with type 1 diabetes, yet little is known about the sociodemographic factors that predict longitudinal trajectories of body fat. We analyzed data from 363 females and 379 males with type 1 diabetes over ~9 years of follow-up (mean baseline age 12.8 ± 2.3 years in females, 13.2 ± 2.4 years in males). Estimated body fat percentage (eBFP) was calculated with validated sex- and race/ethnicity-specific equations. Group-based modeling identified three eBFP trajectories for each sex. All female trajectories showed gradual increases, while male trajectories showed gradual decreases (<5% in eBFP) that plateaued around 7 years of diabetes duration. Female trajectories showed differences in baseline eBFP: Group F1 (38.0%), mean eBFP 27.8 ± 3.0%: Group F2 (47.9%), mean eBFP 33.9 ± 3.0%: and Group F3 (14.1%), mean eBFP 41.7 ± 4.1%. Male trajectories also showed differences in baseline eBFP: Group M1 (57.2%), mean eBFP 22.0 ± 3.0%: Group M2 (30.9%), mean eBFP 33.9 ± 3.0%: and Group M3 (12.9%), mean eBFP 36.1 ± 3.7%. In multinomial models, adjusted for clinical factors (eg, insulin regimen, insulin dose, and hemoglobin A1c), females who reported a single-parent household (adjusted odds ratio [aOR] = 3.34, 95% confidence interval [CI]: 1.49, 7.47), parental education of less than a college degree (aOR = 3.79, 95% CI: 1.60, 9.60), and a lack of private health insurance (aOR = 3.74, 95% CI: 1.45, 9.60), and a household income of less than $75 000 per year (aOR = 3.13, 95% CI: 1.27, 7.70) were approximately three to four times more likely to be in the highest eBFP trajectory group relative to the lowest eBFP trajectory group. Males who reported a household income of <$75 000/year were almost twice as likely to be in the Group M3 than the Group M1 in the unadjusted model only (aOR = 1.79, 95% CI: 0.91, 4.01 vs unadjusted OR: 2.48, 95% CI: 1.22, 5.06). Lower socioeconomic status may be associated with excess body fat throughout adolescence in type 1 diabetes, particularly among females.

Project description:BackgroundLittle is known about the frequency of significant hypoglycemic events in actual practice. Limited health literacy (HL) is common among patients with type 2 diabetes, may impede diabetes self-management, and thus HL could increase the risk of hypoglycemia.ObjectiveTo determine the proportion of ambulatory, pharmacologically-treated patients with type 2 diabetes reporting > or =1 significant hypoglycemic events in the prior 12 months, and evaluate whether HL is associated with hypoglycemia.Research designCross-sectional analysis in an observational cohort, the Diabetes Study of Northern California (DISTANCE).SubjectsThe subjects comprised 14,357 adults with pharmacologically-treated, type 2 diabetes who are seen at Kaiser Permanente Northern California (KPNC), a non-profit, integrated health care delivery system.MeasuresPatient-reported frequency of significant hypoglycemia (losing consciousness or requiring outside assistance); patient-reported health literacy.ResultsAt least one significant hypoglycemic episode in the prior 12 months was reported by 11% of patients, with the highest risk for those on insulin (59%). Patients commonly reported limited health literacy: 53% reported problems learning about health, 40% needed help reading health materials, and 32% were not confident filling out medical forms by themselves. After adjustment, problems learning (OR 1.4, CI 1.1-1.7), needing help reading (OR 1.3, CI 1.1-1.6), and lack of confidence with forms (OR 1.3, CI 1.1-1.6) were independently associated with significant hypoglycemia.ConclusionsSignificant hypoglycemia was a frequent complication in this cohort of type 2 diabetes patients using anti-hyperglycemic therapies; those reporting limited HL were especially vulnerable. Efforts to reduce hypoglycemia and promote patient safety may require self-management support that is appropriate for those with limited HL, and consider more vigilant surveillance, conservative glycemic targets or avoidance of the most hypoglycemia-inducing medications.

Project description:BackgroundDespite the centrality of nutrition in the management of type 1 diabetes, the association of diet quality and macronutrient distribution with glycemic control is ambiguous.ObjectiveThis study examined longitudinally the association of dietary intake with multiple indicators of glycemic control in youth with type 1 diabetes participating in a behavioral nutrition intervention study.DesignParticipants in a randomized clinical trial of a behavioral nutrition intervention [n = 136; mean ± SD age: 12.8 ± 2.6 y; glycated hemoglobin (HbA1c): 8.1% ± 1.0%; 69.1% using an insulin pump] completed 3-d diet records at baseline and months 3, 6, 9, 12, and 18; masked continuous glucose monitoring (CGM) data were obtained concurrently with the use of the Medtronic iPro CGM system. HbA1c was obtained every 3 mo; 1,5-anhydroglucitol was obtained every 6 mo. Linear mixed-effects regression models estimated associations of time-varying dietary intake variables with time-varying glycemic control indicators, controlling for age, height, weight, sex, Tanner stage, diabetes duration, regimen, frequency of blood glucose monitoring, physical activity, and treatment assignment.ResultsHbA1c was associated inversely with carbohydrate and natural sugar, and positively with protein and unsaturated fat. 1,5-Anhydroglucitol was associated positively with fiber intake and natural sugar. Greater glycemic control as indicated by ≥1 CGM variable was associated with higher Healthy Eating Index-2005, whole plant food density, fiber, carbohydrate, and natural sugar and lower glycemic index and unsaturated fat.ConclusionsBoth overall diet quality and macronutrient distribution were associated with more optimal glycemic control. Associations were more consistent for CGM variables obtained concurrently with dietary intake than for biomarkers of longer-term glycemic control. These findings suggest that glycemic control may be improved by increasing intake of high-fiber, low glycemic-index, carbohydrate-containing foods. This trial was registered at clinicaltrials.gov as NCT00999375.

Project description:BackgroundDiabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occur because of a variety of causes, such as taking additional doses of insulin, skipping meals, or overexercising. Mainly, the symptoms of hypoglycemia range from mild dysphoria to more severe conditions, if not detected in a timely manner.ObjectiveIn this review, we aimed to report on innovative detection techniques and tactics for identifying and preventing hypoglycemic episodes, focusing on T1D.MethodsA systematic literature search following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed focusing on the PubMed, GoogleScholar, IEEEXplore, and ACM Digital Library to find articles on technologies related to hypoglycemia detection in patients with T1D.ResultsThe presented approaches have been used or devised to enhance blood glucose monitoring and boost its efficacy in forecasting future glucose levels, which could aid the prediction of future episodes of hypoglycemia. We detected 19 predictive models for hypoglycemia, specifically on T1D, using a wide range of algorithmic methodologies, spanning from statistics (1.9/19, 10%) to machine learning (9.88/19, 52%) and deep learning (7.22/19, 38%). The algorithms used most were the Kalman filtering and classification models (support vector machine, k-nearest neighbors, and random forests). The performance of the predictive models was found to be satisfactory overall, reaching accuracies between 70% and 99%, which proves that such technologies are capable of facilitating the prediction of T1D hypoglycemia.ConclusionsIt is evident that continuous glucose monitoring can improve glucose control in diabetes; however, predictive models for hypo- and hyperglycemia using only mainstream noninvasive sensors such as wristbands and smartwatches are foreseen to be the next step for mobile health in T1D. Prospective studies are required to demonstrate the value of such models in real-life mobile health interventions.

Dataset Information

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

Background

Methods

Results

Conclusions

Impact

Publications

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

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