A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison

Abstract

Objective: As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A_1c (HbA_1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA_1c disparities.

Research design and methods: Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., n = 16,457) and Diabetes Prospective Follow-up (DPV, Germany, n = 39,836) registries were categorized into lowest (Q1) to highest (Q5) SES quintiles. Multiple regression analyses compared the relationship of SES quintiles with diabetes technology use and HbA_1c from 2010-2012 to 2016-2018.

Results: HbA_1c was higher in participants with lower SES (in 2010-2012 and 2016-2018, respectively: 8.0% and 7.8% in Q1 and 7.6% and 7.5% in Q5 for DPV; 9.0% and 9.3% in Q1 and 7.8% and 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA_1c did not change between the two time periods, whereas for T1DX, disparities in HbA_1c by SES increased significantly (P < 0.001). After adjusting for technology use, results for DPV did not change, whereas the increase in T1DX was no longer significant.

Conclusions: Although causal conclusions cannot be drawn, diabetes technology use is lowest and HbA_1c is highest in those of the lowest SES quintile in the T1DX, and this difference for HbA_1c broadened in the past decade. Associations of SES with technology use and HbA_1c were weaker in the DPV registry.

Figure 1

Pump use, CGM use, and HbA_1c by SES in the DPV and T1DX registries in 2010–2012 and 2016–2018. A–F: Mean estimates by SES quintiles and time period from logistic (pump use, CGM use) and linear (HbA_1c) regression models adjusted for sex, age, diabetes duration, SES, time period, minority status, SES-by–time period interaction, and SES-by–minority status interaction. G and H: Mean estimates with the regression model additionally adjusted for pump and CGM use. Dashed lines are connecting mean estimates for pump and CGM use or regression lines for HbA_1c from models including SES as an ordinal term. From these models, P values for trend are given for the association with SES within each time period. Q1 is the lowest and Q5 is the highest SES quintile.

Figure 2

Effect of SES on insulin pump use, CGM use, and HbA_1c. Effects of SES are slopes with 95% CIs of the regression lines for the dependent variables derived from multiple regression models including sex, age, diabetes duration, SES, time period, minority status, SES-by–time period interaction, and SES-by–minority status interaction, with SES modeled as an ordinal term. A positive value in insulin pump use and CGM use indicates higher use in quintiles of higher SES. A negative value in HbA_1c indicates higher HbA_1c in quintiles of lower SES. P values are given for the difference in effects of SES between the two time periods.