Abstract
Racial–ethnic disparities in technology use have been described in children with type 1 diabetes (T1D). It is not known whether these emerge early in disease management. This single-center retrospective study examined disparities in continuous glucose monitor (CGM) initiation and durability in the first-year after diagnosis of T1D in children. Of 345 eligible children, 46% started CGM within their first year. In non-Hispanic white (NHW) children, 51% started using CGM versus 28% of non-Hispanic black (NHB) children (P = 0.006). After stratifying by commercial/government insurance, a proxy for socioeconomic status, this difference persisted among those with commercial insurance. One-year post-CGM initiation, 96% (125/130) of NHW children were using CGM versus 73% (11/15) of NHB children (P = 0.003). Disparities in CGM use emerge early in care of children with T1D, with lower rates of initiation and sustained use of CGM in NHB children. Strategies addressing causes of these disparities should begin early in T1D management.
Introduction
Continuous glucose monitor (CGM) use in children has increased markedly over the past decade, increasing from 6% to 38% between 2011 and 2018 in data from the type 1 diabetes (T1D) exchange registry. 1 CGM use is associated with improved quality of life, and decreased frequency and fear of hypoglycemia. 2 –4 There is increasing evidence that CGM is associated with improved glycemic control, even when started within the first year after diagnosis. 5 –8 However, racial–ethnic disparities in diabetes technology use have been extensively described in children with T1D, with non-Hispanic white (NHW) children 3–6 times more likely to use CGM than non-Hispanic black (NHB) children and 1.5–3 times more likely to use CGM than Hispanic children. 1,9 –17
The first year after a new diagnosis of T1D is unique. The initial experiences of children and families during this time of intensive engagement with the health care system may have long-term effects. 18,19 The provider–patient approach to management in the first year has the potential to shape future attitudes and behaviors toward T1D management. In addition, glycemic control in the years immediately after a new diagnosis of T1D is associated with long-term clinical outcomes. 20,21 NHB children have higher hemoglobin A1c (HbA1c) levels in the first years after diagnosis than NHW and Hispanic children. 14,22 In addition, the majority of NHB children with established diabetes are less likely to achieve the target HbA1c of <7%. 12,15,23,24 With increased adoption of diabetes technology, racial–ethnic inequities in the early introduction of these technologies may contribute to a widening of prevailing disparities in glycemic control over the short and long term. 9,10,25
We have previously demonstrated that, among those with established T1D (beyond the first year from diagnosis), there are lower rates of initiation and ongoing use of CGM in NHB children. 9 It remains unclear whether these disparities in CGM use occur early during diabetes care. Thus, the aim of this study was to determine whether racial–ethnic disparities in CGM use emerge within the first year after diagnosis. As a secondary aim, we investigated whether there were disparities in rates of CGM discontinuation.
Materials and Methods
This is a retrospective chart review of children with T1D followed at Children's Hospital of Philadelphia, with a diagnosis date between January 1, 2016 and April 1, 2018. April 1, 2018 was chosen to ensure that data were not affected by the COVID-19 pandemic. The institutional review board at Children's Hospital of Philadelphia approved this study.
Population
Children 18 years of age or younger at diagnosis were included if they had a clinical diagnosis of T1D, and self-identified as NHW, NHB, or Hispanic. Children who transferred care to our institution and were already using CGM were excluded. Primary insurance was used as a surrogate for socioeconomic status (SES), with government insurance representing lower SES. To remove the confounding influence of varying access to CGM, our analysis was limited to Pennsylvania residents who are afforded access to CGM coverage through Medicaid, whether as primary or secondary insurance. Our center offers a diabetes education appointment to initiate the device and an appointment 2–3 weeks later to emphasize the importance of CGM review.
Data extraction
Age, gender, race, ethnicity, diabetes type, date of birth, date of diagnosis, date of CGM start, and primary insurance type were extracted from the electronic health record. Patients were identified as having started CGM if they started a Dexcom (Dexcom, Inc., San Diego, CA) or Medtronic (Medtronic, Inc., Minneapolis, MI) CGM device. Freestyle Libre was not yet approved for pediatric use and, therefore, was not studied. Subjects were defined as using CGM at 1-year if the CGM online portal documented any use in the 12th month after initiation. Subjects without portal data were defined as using CGM at 1-year if there was any use documented at the office visit closest to 1-year after initiation.
Statistical analysis
Chi-squared analysis was used to compare categorical variables. A Bonferonni adjustment was applied to analyses with three comparisons by multiplication of the P-value by 3. With this adjustment, a two-sided P-value of <0.05 was considered statistically significant. Data analyses were performed using SPSS v. 26.0 (IBM Corporation, Armonk, NY).
Results
There were 345 children (43% female) who attended the Diabetes Center at Children's Hospital of Philadelphia between January 1, 2016, and April 1, 2018, and were eligible for inclusion. Of these, 262 (76%) children were NHW, 54 (16%) were NHB, and 29 (8%) were Hispanic. A lower proportion of NHW (n = 238, 19%) children had government insurance than NHB (n = 33, 61%, P < 0.001) and Hispanic (n = 21, 72%, P < 0.001) children. The mean age at diagnosis was 9.9 (4.4) years.
Of the 345 eligible children, 158 (46%) started using CGM within the first year after diagnosis (133 NHW, 15 NHB, 10 Hispanic). The mean age at CGM start was 9.3 (4.6) years and mean HbA1c was 7.3% (1.6%). A greater proportion of children with commercial insurance (130/242, 54%) started using CGM than children with government insurance (28/103, 27%) (P < 0.001) (Table 1). One-year postinitiation, 155 of 158 children who started using CGM had data on CGM use. Of those who started using CGM, 95% (121/127) of children with commercial insurance were still using the device, compared with 86% (24/28) of children with government insurance (P = 0.06).
Characteristics of Continuous Glucose Monitor Users
CGM, continuous glucose monitor; NHB, non-Hispanic black; NHW, non-Hispanic white.
Racial disparities in CGM initiation
A higher proportion of NHW (133/262, 51%) than NHB (15/54, 28%, P = 0.006) children started CGM in the first year, with intermediate numbers of Hispanic (10/29, 35%, P = 0.3). Odds ratio for NHW children starting to use CGM was 2.6 (95% confidence interval [CI] 1.4–5.1) compared with NHB children and 2.0 (95% CI 0.9–4.4) compared with Hispanic children (Fig. 1). Analysis by insurance type found that racial–ethnic disparities were isolated to those with commercial insurance, where 56% (120/213) of NHW and 29% (6/21) of NHB children initiated CGM in the first year (P = 0.045). CGM initiation rates were intermediate (50% or 4/8) in Hispanic children. NHW children were 3.3 times (95% CI 1.2–8.6) more likely than NHB to start using CGM in the first year. Among children with government insurance, a lower rate of CGM initiation was observed in all racial–ethnic groups with no significant difference among the groups (27% of NHW, 27% of NHB, 29% of Hispanic).

CGM Initiation: The odds ratio for CGM initiation among NHW, NHB, and Hispanic children in the first year after diagnosis of T1D by insurance type. CGM, continuous glucose monitor; CI, confidence interval; NHB, non-Hispanic black; NHW, non-Hispanic white; T1D, type 1 diabetes.
Racial disparities in sustained use of CGM
Of those who started using CGM within the first year after diagnosis (n = 133 NHW, 15 NHB, 10 Hispanic), 94% (145/155) of children were using the device 1-year postinitiation. A lower proportion of NHB children (11/15, 73%) were using CGM at 1-year compared with 96% of NHW (125/130, P = 0.003) and 90% of Hispanic (9/10; P = 0.9 compared with both NHW and NHB). Among children with commercial insurance, fewer NHB children (4/6, 67%) were using CGM at 1 year compared with 97% (113/117, P = 0.003) of NHW. In children with government insurance (n = 28), continued use was higher in NHW, but the number was too low to identify any statistically significant racial–ethnic disparity in sustained CGM use (92% NHW, 78% NHB, 83% Hispanic).
Discussion
We have shown that racial–ethnic disparities in CGM use begin within the first year after diagnosis of T1D. CGM initiation was lowest among NHB, intermediate in Hispanic, and highest in NHW children. Ongoing use of CGM at 1-year postinitiation was higher among NHW than among NHB children. The finding that NHW children employ CGM technology at higher rates than NHB children is congruent with previous studies examining racial–ethnic disparities in CGM use among children with T1D. 1,9 –13,16,17 The novel observations in this study are (1) racial–ethnic disparities in CGM use begin early in the care of children with T1D and (2) lower rates of sustained use of CGM are seen in NHB children who initiate the device within the first year after diagnosis.
Our observation that NHB children started using CGM at lower rates than NHW children is consistent with existing cross-sectional studies. In recent T1D exchange registry data from 81 centers in the United States, 37% of NHW were using CGM compared with 8% of NHB children and young adults. 1 At a large academic pediatric center in Texas, 76% of NHW children compared with 5% of NHB children were using CGM. 16 A Colorado center found 63% of NHW children compared with 4% of NHB children were using CGM in their Medicaid-insured population. 17
Although previous studies may have concluded that racial–ethnic disparities in T1D were primarily the results of differences in SES, 26 our data demonstrated greater racial–ethnic disparities among children of higher SES. The relationship between racial–ethnic disparities in diabetes care and SES is complex. Limiting our population to Pennsylvania state residents is one of the strengths of this study. As children with diabetes are eligible for Medicaid (which covers CGM) without regard to household income, we were able to observe patterns of technology use without the influences of insurance coverage.
The etiology of these disparities is not well understood. The first year of learning to manage T1D is challenging, and has been associated with high rates of anxiety and depression among families. 27 This provides an additional challenge for families with unaddressed difficulties related to social determinants of health (SDOH), including health literacy, food security, safe housing, and a supportive social network. 19,28 NHB families are more likely to be facing SDOH barriers to achieving optimal health outcomes. 29,30 Lastly, there were no NHB or Hispanic billing providers (attendings, nurse practitioners) in our center during the course of this study. These barriers may contribute to the disparities in technology use that we have shown in the early management of T1D in children. The early approach to diabetes management by providers and families may persist long term. Hawkes et al. found that intensive diabetes education in the first year had lasting effects on glycemic control. 19
With increasing evidence that CGM use is associated with improved glycemic control, 5 –8 we postulate that disparities in CGM use could contribute to NHB children having poorer diabetes control in the early years after diagnosis as well as later in life. 1,12,15,22,24 Without addressing disparities that present early in care, we will not be able to address the significant differences in outcomes later in life.
Many articles describing racial–ethnic disparities in health care postulate that providers' “unconscious” bias is responsible. 31 –34 Imploring clinicians to tame “unconscious” beliefs obfuscates the need to confront their role in perpetuating the racial disparities that objectively exist and undergird systemic inequities. In addition to acknowledging individual racism, we need to examine and address the role of underlying structural racism as a root cause of these disparities. Structural racism, the concept that our societal history, laws, norms, and institutions all interact with each other to generate and reinforce inequities, 35 has been named as fundamental cause of health disparities in the United States. 36 –40 To achieve equity, further research and interventions are needed, focused on addressing the role of individual and structural racism (health system and societal) as critical barriers to diabetes care. 41
The strengths of this study include the large and diverse patient population and universal Medicaid coverage for children with T1D. Limitations include the retrospective nature of the study and the absence of a control group without CGM use. The number of NHB and Hispanic children who initiated CGM was low, which may affect the strength of our findings of greater racial–ethnic disparities in children with commercial insurance as well as the sustained use analysis. The single-center nature of the study may limit generalizability to other institutions. Although we were able to clearly describe patterns of CGM initiation that are driving disparities in CGM use, this study design did not allow for further evaluation of the reasons behind these disparities.
Conclusion
Racial disparities in diabetes care emerge early and persist throughout the management of this chronic disease. To advance beyond merely documenting disparities and move toward health equity, we must understand the etiology of these inequities. SDOH, including structural racism, are likely playing a role in disparities in the care and outcomes of children with T1D. Future studies and interventions to improve equity in health care should focus on examining and addressing systemic factors that contribute to disparities.
Footnotes
Authors' Contributions
C.W.L. researched data and wrote the article; T.H.L. and S.M.W. contributed to study design and reviewed/edited the article; and C.P.H. wrote the article, was responsible for study design, and is the guarantor for this study.
Financial Disclosure
All others have no financial relationships relevant to this article to disclose.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
No funding was received for this article.
