Prediabetes Prevalence by Adverse Social Determinants of Health in Adolescents.

Importance: Several clinical practice guidelines advise race- and ethnicity-based screening for youth-onset type 2 diabetes (T2D) due to a higher prevalence among American Indian and Alaska Native, Asian, Black, and Hispanic youths compared with White youths. However, rather than a biological risk, this disparity likely reflects the inequitable distribution of adverse social determinants of health (SDOH), a product of interpersonal and structural racism. Objective: To evaluate prediabetes prevalence by presence or absence of adverse SDOH in adolescents eligible for T2D screening based on weight status. Design, Setting, and Participants: This cross-sectional study and analysis used data from the 2011 to 2018 cycles of the National Health and Nutrition Examination Survey. Data were analyzed from June 1, 2023, to April 5, 2024. Participants included youths aged 12 to 18 years with body mass index (BMI) at or above the 85th percentile without known diabetes. Main Outcomes and Measures: The main outcome consisted of an elevated hemoglobin A1c (HbA1c) level greater than or equal to 5.7% (prediabetes or undiagnosed presumed T2D). Independent variables included race, ethnicity, and adverse SDOH (food insecurity, nonprivate health insurance, and household income <130% of federal poverty level). Survey-weighted logistic regression was used to adjust for confounders of age, sex, and BMI z score and to determine adjusted marginal prediabetes prevalence by race, ethnicity, and adverse SDOH. Results: The sample included 1563 individuals representing 10 178 400 US youths aged 12 to 18 years (mean age, 15.5 [95% CI, 15.3-15.6] years; 50.5% [95% CI, 47.1%-53.9%] female; Asian, 3.0% [95% CI, 2.2%-3.9%]; Black, 14.9% [95% CI, 11.6%-19.1%]; Mexican American, 18.8% [95% CI, 15.4%-22.9%]; Other Hispanic, 8.1% [95% CI, 6.5%-10.1%]; White, 49.1% [95% CI, 43.2%-55.0%]; and >1 or other race, 6.1% [95% CI, 4.6%-8.0%]). Food insecurity (4.1% [95% CI, 0.7%-7.5%]), public insurance (5.3% [95% CI, 1.6%-9.1%]), and low income (5.7% [95% CI, 3.0%-8.3%]) were each independently associated with higher prediabetes prevalence after adjustment for race, ethnicity, and BMI z score. While Asian, Black, and Hispanic youths had higher prediabetes prevalence overall, increasing number of adverse SDOH was associated with higher prevalence among White youths (8.3% [95% CI, 4.9%-11.8%] for 3 vs 0.6% [95% CI, -0.7% to 2.0%] for 0 adverse SDOH). Conclusions and Relevance: Adverse SDOH were associated with higher prediabetes prevalence, across and within racial and ethnic categories. Consideration of adverse SDOH may offer a more actionable alternative to race- and ethnicity-based screening to evaluate T2D risk in youth.

Race- and Neighborhood-Related Disparities Spanning the COVID-19 Pandemic: Trajectories of Combined Glycemic Control and BMI in Youth With Diabetes.

OBJECTIVE: To use combined glycemic (HbA1c) and BMI z-score (BMIZ) trajectories spanning the coronavirus disease 2019 (COVID-19) pandemic to identify high-risk subgroups of adolescents with diabetes. RESEARCH DESIGN AND METHODS: Retrospective cohort of adolescents 10-19 years old with type 1 and type 2 diabetes with one or more visits at a large pediatric hospital from January 2018 through February 2020 (prepandemic) and April 2020 through August 2021 (pandemic). Group-based trajectory models were used to identify latent classes of combined BMIZ and HbA1c trajectories. Multinomial logistic regression was used to evaluate predictors of class membership, including Area Deprivation Index (ADI) (socioeconomic status proxy). RESULTS: The cohort included 1,322 youth with type 1 diabetes (93% White and 7% Black) and 59 with type 2 diabetes (53% Black and 47% White). For type 1 diabetes, six trajectory classes emerged. Black youth were more likely to be in the class with worsening glycemic control and concurrent BMIZ decrease at pandemic onset (relative risk ratio [RRR] vs. White: 3.0 [95% CI 1.3-6.8]) or in the class with progressively worsening glycemic control and obesity (RRR 3.0 [95% CI 1.3-6.8]), while those from the most deprived neighborhoods (RRR ADI tertile 3 vs. 1: 1.9 [95% CI 1.2-2.9]) were more likely to be in the class with stable obesity and glycemic control. For type 2 diabetes, three distinct trajectories emerged, two of which experienced worsening glycemic control with concurrent BMIZ decline at pandemic onset. CONCLUSIONS: Race and neighborhood deprivation were independently associated with distinct glycemic and BMIZ trajectory classes in youth with diabetes, highlighting persistent and widening disparities associated with the COVID-19 pandemic.

Barriers and Facilitators to Uptake of Continuous Glucose Monitoring for Management of Type 2 Diabetes Mellitus in Youth.

PURPOSE: The purpose of this study was to identify factors impacting the acceptability of continuous glucose monitoring (CGM) in adolescents and young adults (AYAs) with type 2 diabetes mellitus (T2DM). METHODS: In this single-center study, semistructured interviews were conducted with AYAs with T2DM and their parents to determine attitudes about CGM, including barriers and facilitators. Interviews were audio-recorded, transcribed, and evaluated using thematic analysis. RESULTS: Twenty AYAs and 10 parents participated (n = 30 total). AYAs were mean age 16.5 years (SD 2.2, range = 13.7-20.1) and had median diabetes duration of 1.3 years. Most were female (65%) and from minoritized background (40% non-Hispanic Black, 10% Hispanic, 5% Asian). Seven (35%) used CGM. The primary facilitator elicited was convenience over glucose meter use. Important barriers included the impact of physically wearing the device and drawing unwanted attention, desire for AYA privacy, and inadequate education about the device. CONCLUSIONS: In this diverse sample of AYAs with T2DM and their parents, CGM was generally regarded as convenient, although concerns about worsening stigma and conflict with parents were prevalent. These findings can guide the development of patient-centered approaches to CGM for AYAs with T2DM, a critical step toward reducing inequities in diabetes technology uptake.