Type 1 diabetes (T1D) treatment is centered around the improvement and maintenance of tight glycemic control, as assessed by levels of hemoglobin A_1c (HbA_1c), to prevent acute and chronic diabetes-related complications.^1–3 Glycemic control can vary considerably from diabetes onset through adolescence,^4–6 where fluctuations are known to occur during puberty^3,4,7–12 and during early adulthood. Poorer glycemic control during early adulthood or from childhood to young adulthood has been attributed to a lack of continuity in diabetes-related clinical care^4,11,12 as well as changes in self-care as children and adolescents with T1D grow into adulthood.^9,10,13 However, glycemic control in youth and young adults with T1D is critical, as a higher average HbA_1c level in this period of development is associated with impaired growth as well as diabetic complications.^14–17

In cross-sectional studies of adolescents and young adults, glycemic control differs by racial and ethnic subgroups.¹⁸ African American, American Indian, Hispanic, and Asian or Pacific Islander youth with T1D are more likely to have higher HbA_1c levels compared with non-Hispanic white youth.¹⁹ In longitudinal studies, nonwhite youth with T1D have increased markers of poor prognosis at diagnosis and 3 years following diagnosis, including higher HbA_1c levels, more frequent diabetic ketoacidosis, and severe hypoglycemia.²⁰ A constellation of sociodemographic factors related to race/ethnicity and glycemic control have been proposed, ranging from family dynamics, depressive symptoms, and quality of life^13,21–25 to diabetes regimen.^26–28 The role of socioeconomic position as a mediator of racial/ethnic associations remains controversial.^28–31 Additionally, health care–specific factors such as disparities in health literacy, diabetes-related knowledge, or access to health care are known to contribute to pediatric health disparity but have not been well explored in T1D.^32,33

Latent class trajectory modeling has been used to identify subgroups who share a similar trajectory of HbA_1c over time.³⁴ Few studies have examined whether racial/ethnic disparities in glycemic control persist over time from childhood into young adulthood among individuals with T1D. Our objective was to first visualize major trajectories of glycemic control from childhood into young adulthood using all data from youth of all racial and ethnic groups and to then characterize specific associations between race/ethnicity and distinct longitudinal patterns of glycemic control. Our hypothesis was that non-Hispanic black and Hispanic youth would be more likely than non-Hispanic white youth to have unfavorable trajectory patterns representing poor glycemic control and that this association may be mediated by clinical factors such as diabetes regimen^26–28 and by socioeconomic position.^29–31

The sample of 1313 youths with T1D was 49.3% female (647 patients); 77.0% were non-Hispanic white (1011 patients); 10.7%, Hispanic (140 patients); 9.8%, non-Hispanic black (128 patients); and 2.6%, other race/ethnicity (34 patients) (Table 1). At the baseline visit, the mean (SD) age was 9.7 (4.3) years and the mean (SD) diabetes duration was 9.2 (6.3) months. Group-based trajectory modeling identified 3 distinct HbA_1c trajectories over a mean (SD) follow-up of 108 (16) months (9.0 [1.4] years) of diabetes duration: group 1, low baseline and mild increases (50.7% [666 patients]); group 2, moderate baseline and moderate increases (41.7% [548 patients]); and group 3, moderate baseline and major increases (7.5% [99 patients]) (Figure 2).

The prevalence of black and Hispanic youth was the highest in group 3 and the lowest in group 1 (non-Hispanic black patients made up 5.1% of group 1, 12.6% of group 2, and 25.3% of group 3; Hispanic patients made up 8.4% of group 1, 12.2% of group 2, and 17.2% of group 3). For non-Hispanic black patients, the difference between group 1 and group 2 was 7.5% (95% CI, 4.2%−10.7%; P < .001); between group 1 and group 3, 20.2% (95% CI, 11.4%−28.9%; P < .001); and between group 2 and group 3, 12.6% (95% CI, 3.7%−21.7%; P = .001). For Hispanic patients, the difference between group 1 and group 2 was 3.8% (95% CI, 0.4%−7.3%; P = .03); between group 1 and group 3, 8.8% (95% CI, 1.0%−16.5%; P = .006); and between group 2 and group 3, 5.0% (95% CI, 3.0%−12.9%; P = .18). Group 3 was composed of 47.5% nonwhite youths (47 patients) (Table 1). Table 2 depicts the odds ratios (ORs) for non-Hispanic black and Hispanic vs non-Hispanic white race/ethnicity and HbA_1c trajectory group in a series of sequentially adjusted models. Non-Hispanic black youth had 7.98 higher odds than non-Hispanic white youth of being in the highest HbA_1c trajectory group relative to the lowest HbA_1c trajectory group (unadjusted OR of non-Hispanic black race in group 3 vs group 1, 7.98; 95 CI, 4.42–14.38). After adjustment for baseline demographic characteristics, clinical factors, and socioeconomic position, non-Hispanic black youth had 4.54 times higher odds than non-Hispanic white youth of being in the highest HbA_1c trajectory group relative to the lowest HbA_1c trajectory group (adjusted OR [aOR] of non-Hispanic black race in group 3 vs group 1, 4.54; 95% CI, 2.08–9.89). Hispanic youth had 3.29 higher unadjusted odds than non-Hispanic white youth of being in the highest HbA_1c trajectory group relative to the lowest HbA_1c trajectory group (unadjusted OR of Hispanic ethnicity in group 3 vs group 1, 3.29; 95% CI, 1.78–6.08). Adjustment for baseline demographic characteristics, clinical factors, and socioeconomic position did not fully attenuate the association (aOR of Hispanic ethnicity in group 3 vs group 1, 2.24; 95% CI, 1.02–4.92). Adjustment for clinical variables diminished statistical significance associated with the moderate HbA_1c trajectory (aOR of Hispanic ethnicity in group 2 vs group 1, 1.43; 95% CI, 0.90–2.27 vs unadjusted OR, 1.71; 95% CI, 1.17–2.49).

The association of race/ethnicity and HbA_1c trajectory was modified by sex (P for interaction = .04) (Table 3). Nonwhite male patients had significantly elevated odds of membership in the highest HbA_1c trajectory group (OR of group 3 vs group 1, 5.34; 95% CI, 2.16–13.2) and moderate HbA_1c trajectory group (OR of group 2 vs group 1, 2.06; 95% CI, 1.18–3.57) relative to non-Hispanic white male patients. The associations were not significant in female patients (aOR of group 3 vs group 1, 1.48; 95% CI, 0.65–3.39 and aOR of group 2 vs group 1, 1.00; 95% CI, 0.61–1.64). The association of race/ethnicity and HbA_1c trajectory was also modified by age at diagnosis (P for interaction = .02) (Table 3). Nonwhite youths diagnosed at or younger than 9 years had significantly elevated odds of membership in the highest HbA_1c trajectory group (aOR of group 3 vs group 1, 5.37; 95% CI, 1.91–15.1) and the moderate HbA_1c trajectory group (aOR of group 2 vs group 1, 2.04; 95% CI, 1.23–3.37). The association was not significant in youth who were diagnosed when they were older than 9 years (aOR of group 3 vs group 1, 1.65; 95% CI, 0.77–3.51 and aOR of group 2 vs group 1, 0.96; 95% CI, 0.55–1.65).

In a large, population-based multiethnic cohort of youth with T1D, we found 3 distinct HbA_1c trajectories that deteriorated over a mean (SD) follow-up of 9.0 (1.4) years (range, 6.1–13.3 years) following diabetes diagnosis, reinforcing that early youth and the transition to adulthood are high-risk periods for worsening glycemic control.^3,7,8 Black race and Hispanic ethnicity were associated with membership in the highest and most rapidly increasing (worsening) HbA_1c trajectory group.

We tested the association of race/ethnicity with HbA_1c trajectory by adjusting for other variables, including clinical factors and socioeconomic position. For example, prescribing practices may vary based on race/ethnicity²⁷ and insulin pump use is known to be higher in white youth than non-Hispanic black or Hispanic youth.²⁸ Lower socioeconomic position has been proposed as a major mediator of the association of race/ethnicity with health outcomes,^29–31 including T1D complications, due to poorer self-management among persons whose socioeconomic conditions are less favorable.^20,46 Despite adjustment for these known risk factors, black race remained significantly associated with HbA_1c trajectory. Similarly, adjustment for demographic characteristics, clinical variables, and socioeconomic position did not fully attenuate the association of Hispanic ethnicity with the highest HbA_1c trajectory, where the OR remained significantly elevated, suggesting remaining impact of inequity in this group. Evidence of disparity in glycemic control trajectory that exists particularly among nonwhite male patients and nonwhite youth with diabetes diagnosis at an early age (9 years) is consistent with previously reported patterns in acute glycemic complications that are more common among the youngest patients and male patients of all ages.⁴⁷

An important finding of the trajectory analysis was that the highest HbA_1c trajectory subgroup also showed the highest mean HbA_1c level at baseline, which occurred at a mean (SD) of 9.8 (6.3) months following diagnosis. This suggests that glycemic control obtained in the first year following diagnosis may confer information about longitudinal trends over time. Furthermore, the magnitude of racial/ethnic inequity over the longitudinal data are striking. Group 3 diverged over the follow-up period to give vastly different mean HbA_1c measures at the cohort visit that may translate to significant increases in the risk for complications of diabetes based on evidence from the Diabetes Control and Complications Trial (DCCT) and the Epidemiology of Diabetes Interventions and Complications Study (EDIC).^1–3,48 Disparity in glycemic control across trajectory groups in the present analyses even exceeds differences reported across groups of the DCCT/EDIC trial (which compared a median HbA_1c of 7% of total hemoglobin in the intensive insulin treatment group with a median HbA_1c of 9% of total hemoglobin in the conventional group), suggesting that those risk estimates may be conservative for youth who additionally face a longer period of disease-related exposures.⁴⁹

Previous studies have shown that the migration status of parents is associated with glycemic control among youth with T1D.⁵⁰ To address potential differences, we examined a subset of the sample with data on parental nativity (ie, US born vs foreign born) and found no significant differences across HbA_1c trajectory groups. Adjustment for parental nativity did not attenuate the association of black race or Hispanic ethnicity with the moderate or highest HbA_1c trajectory group, although the analysis is limited by small sample size (data not shown). Differences in youth and parental nativity status likely warrant future study in adequately powered samples.

Given the complexity of the study of race and health outcomes in the United States, in which health risks associated with race/ethnicity are not inherent but instead may signal underlying inequalities,⁵¹ we posit that our results may reflect health inequity in T1D operating at multiple levels. The social determinants of health operating outside of the health care system, including aspects of the physical environment, food security, social integration, barriers to health care,⁵² and complex patterns in health care utilization,^53,54 may create race-based groups of individuals for whom glycemic control is challenged by inconsistencies in the availability of resources or support for T1D management. In general, adverse childhood experiences among nonwhite youth have been shown to result in a myriad of psychological and medical sequelae later in life.⁵⁵

There may also be modifiable aspects within the health care system, including racial/ethnic differences in the interpersonal dynamics of interactions between patients or parents and health care professionals that occur in pediatric clinical settings, extending from implicit bias and microaggressions to stereotyping, prejudice, and macroaggressions.⁵⁶ Nonwhite youth and families report overtly weakened patient–health care professional communication and decreased participatory decision making.^32,33 Implicit bias, the unconscious attitudes that unintentionally influence behavior, may affect health care professionals’ medical management decisions⁵⁶ and perceptions about black, Hispanic, and young people of color in terms of disease experience⁵⁷ and patient compliance.⁵⁸ Higher levels of perceived bias or discrimination have been linked to worse diabetes care.^59,60 The direct effect of implicit bias on HbA_1c has not been well studied in pediatric diabetes. Finally, while social stigma associated with T1D is known,^61–63 it may be more pronounced in specific communities where health literacy and resources are lacking or where T1D is significantly less common than type 2 diabetes. Nonwhite youth may struggle with misunderstanding and stigma that act as chronic stressors that indirectly affect glycemic control via psychosocial or behavioral effects,^64,65 resulting in impaired self-care strategies or maladaptive coping behaviors that damage health.⁶⁶

A limitation of the study is that the observed inequity after adjustment for other factors may reflect racial and ethnic differences in the validity of HbA_1c as a measure of average glycemia owing to racial differences in the glycation of hemoglobin or other factors affecting red blood cell turnover.^67–69 However, the between-race differences that have been reported are small (0.4 percentage point in HbA_1c⁶⁹) relative to the differences in the present study, where the mean (SD) HbA_1c of group 3 was 12.2% (1.5%) of total hemoglobin at the last visit, roughly 2.2% higher than group 2 and 4.4% higher than group 1 at that time. Combining individuals of many races, ethnicities, and cultures into single categories for analysis may result in residual confounding and underemphasize within-group heterogeneity. We are careful to avoid implying that all nonwhite youth have poor control; in our data, nearly a quarter of nonwhite youth had an HbA_1c at or below 7.4% of total hemoglobin at the cohort visit (data not shown). Several of the variables measured at baseline may change over time, including health insurance status. Adjustment variables may provide information for future work that will delve into what drives the inequities. For example, measures of socioeconomic position may be improved by including other measures such as the ability to pay for medication, heath literacy, housing security, or food security. We did not control for diet and physical activity in these analyses. A larger sample may identify additional trajectories that capture the experience of smaller subpopulations, such as individuals who initially have low HbA_1c that deteriorates later in the course of T1D. The outcome of trajectory group necessitated the use of logistic regression modeling, which may overestimate effect estimates, particularly when the outcome is common.^70,71 Finally, there were relatively small numbers of participants across groups in the analyses stratified by sex and age at diagnosis. Larger studies are needed to further explore interactions and identify nonwhite youth who are at the highest risk for poor glycemic control over time. Finally, associations of data-driven trajectory models should be confirmed with future analyses that quantify and compare differences in longitudinal HbA_1c across racial/ethnic groups.

However, the study has several strengths, including the large, well-characterized, multiethnic cohort;⁷² the extended follow-up period; and the use of an analytic approach to characterize multiple common HbA_1c trajectories and understand associated individual characteristics from an extensive collection of covariates.

Compared with non-Hispanic white youth with T1D, non-Hispanic black youth, Hispanic youth, and youth with other racial/ethnic backgrounds who are male and diagnosed earlier in life are more likely to show rapid deterioration in glycemic control within 9 years of T1D diagnosis. The findings of this study can be used to inform future research on the identification of factors that contribute to and reinforce racial and ethnic disparity among youth with T1D, particularly nonwhite male patients and nonwhite youth diagnosed earlier in life.