Predictors of HbA1c Trajectories in Predominantly Black Adolescents With Type 1 Diabetes

Differential item functioning of the revised Multigroup Ethnic Identity Measure (MEIM-R) in racially and income diverse youth with type 1 diabetes

OBJECTIVE

Racially minoritized youth with T1D are made vulnerable to disproportionately adverse health outcomes compared to White peers due to enduring systems of oppression. Thus, understanding modifiable psychosocial factors associated with diabetes-related outcomes in racially minoritized youth may help to buffer deleterious effects of racism. One factor meriting exploration is racial-ethnic identity. There is currently limited research on measures fit to assess ethnic identity in youth with chronic illnesses. This study's purpose is to examine the factor structure, reliability, and validity of the revised Multigroup Ethnic Identity Measure (MEIM-R) in a racially- and income-diverse sample of youth with T1D across sociodemographic and illness-related proxies for one's positionality in oppressive systems.

METHOD

As part of a larger study examining resilience, 142 youth with T1D ages 12-18 (Mage = 14.66, SDage = 1.62, 55.6% Black/African-American, 44.4% White) completed the MEIM-R and various psychosocial measures. HbA1c levels and illness duration were extracted from medical records and caregivers reported income information. Confirmatory factor analyses compared the structural validity of competing MEIM-R models, and uniform and non-uniform differential item functioning (DIF) was explored across sociodemographic and illness-related factors.

RESULTS

While a bifactor structure was supported, the MEIM-R was found to exhibit DIF by race and gender on multiple MEIM-R items and did not demonstrate linear bivariate relations with other psychosocial factors.

CONCLUSIONS

Since different MEIM-R item response patterns were observed across racial/ethnic and gender groups, caution is warranted in using this measure in racially and gender diverse youth with T1D.

Interventions Across the Translational Research Spectrum: Addressing Disparities Among Racial and Ethnic Minoritized Youth with Type 1 Diabetes

Racial and ethnic minoritized youth with type 1 diabetes (T1D) are at elevated risk for health disparities. Few intervention studies have been conducted for these youth and evidence to support best practices to address their needs is lacking. Existing evidence supports the use of brief trials of diabetes technology with structured support from clinic staff, culturally tailored interventions such as language-congruent clinical care, and use of community health workers as promising directions to improve health outcomes. Clinicians and researchers should work collaboratively with community members to improve the quality of T1D intervention science for racial and ethnic minoritized youth.

Endocrine Health and Health Care Disparities in the Pediatric and Sexual and Gender Minority Populations: An Endocrine Society Scientific Statement

Endocrine care of pediatric and adult patients continues to be plagued by health and health care disparities that are perpetuated by the basic structures of our health systems and research modalities, as well as policies that impact access to care and social determinants of health. This scientific statement expands the Society's 2012 statement by focusing on endocrine disease disparities in the pediatric population and sexual and gender minority populations. These include pediatric and adult lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA) persons. The writing group focused on highly prevalent conditions-growth disorders, puberty, metabolic bone disease, type 1 (T1D) and type 2 (T2D) diabetes mellitus, prediabetes, and obesity. Several important findings emerged. Compared with females and non-White children, non-Hispanic White males are more likely to come to medical attention for short stature. Racially and ethnically diverse populations and males are underrepresented in studies of pubertal development and attainment of peak bone mass, with current norms based on European populations. Like adults, racial and ethnic minority youth suffer a higher burden of disease from obesity, T1D and T2D, and have less access to diabetes treatment technologies and bariatric surgery. LGBTQIA youth and adults also face discrimination and multiple barriers to endocrine care due to pathologizing sexual orientation and gender identity, lack of culturally competent care providers, and policies. Multilevel interventions to address these disparities are required. Inclusion of racial, ethnic, and LGBTQIA populations in longitudinal life course studies is needed to assess growth, puberty, and attainment of peak bone mass. Growth and development charts may need to be adapted to non-European populations. In addition, extension of these studies will be required to understand the clinical and physiologic consequences of interventions to address abnormal development in these populations. Health policies should be recrafted to remove barriers in care for children with obesity and/or diabetes and for LGBTQIA children and adults to facilitate comprehensive access to care, therapeutics, and technological advances. Public health interventions encompassing collection of accurate demographic and social needs data, including the intersection of social determinants of health with health outcomes, and enactment of population health level interventions will be essential tools.

Health Disparities Likely Emerge Early in the Course of Type-1 Diabetes in Youth

BACKGROUND

Type-1 diabetes (T1D) management and glycemic control the year after diagnosis affects the long-term trajectory of T1D. Disparities in hemoglobin A1c (HbA1c) based on race, ethnicity, and socioeconomic status (SES) have been well-documented; however, there has been limited investigation into the timeline with which these disparities develop. This study aims to assess differences in HbA1c by race/ethnicity and SES among youth with T1D over 1 year post diagnosis.

METHODS

HbA1c at onset, and 3, 6, 9, and 12 months following diagnosis was collected from youth with T1D between 2016 and 2020. Mixed-effect models examined associations of HbA1c over time with race/ethnicity and SES.

RESULTS

Of 758 patients, 71% identified as white. Mean (± SD) HbA1c was 11.4% ± 2.2% at diagnosis and 7.3% ± 1.2%, 7.3% ± 1.3%, 7.7% ± 1.4%, and 7.9% ± 1.4% at 3, 6, 9, and 12 months, respectively. HbA1c trajectories over time differed significantly by race (adjusting for sex and zip-code education and poverty levels) with Hispanic and black youth demonstrating higher HbA1c 1 year after diagnosis (8.7% vs 7.7%, p < .001) than white youth.

CONCLUSIONS

These data revealed that youth did not meet glycemic targets at 1 year post diagnosis and that racial/ethnic minority youth had higher HbA1c 1 year post diagnosis, highlighting the need to optimize glycemic control and mitigate disparities early. Understanding the time course of these outcomes helps to inform the need for early interventions, particularly in disadvantaged patient populations, to lay the groundwork for improved control. Further research must also be done to better understand overlapping axes of disparities including race, ethnicity, and SES.

Brief assessment of diabetes-specific psychological flexibility in racially and income diverse youth with type 1 diabetes

OBJECTIVE

Diabetes-specific psychological flexibility (the ability to engage in valued behaviors, be open to internal experiences, with present-moment awareness, while living with diabetes) is associated with HbA1c and health-related quality of life in youth with type 1 diabetes (T1D). Having brief diabetes-specific psychological flexibility assessments that perform equivalently across diverse individuals is important for research and clinical work addressing health disparities. The present study aimed to create 9-and 3-item short forms (DAASito-9 and -3) of the Diabetes Acceptance and Action Scale (DAAS-22), and evaluate their validity, reliability, and measurement invariance (MI).

RESEARCH DESIGN AND METHODS

Youth with T1D (n = 179, M_age  = 14.64, 50% female, 56% Black/African American) completed self-report measures at an endocrinology clinic visit. HbA1c was extracted from medical records. One-half of the sample was used to develop the DAASitos with the highest reliability, McDonald's 𝜔 ≥ 0.75, and convergent validity (r ≥ 0.90 to DASS-22). Confirmatory factor analyses evaluated structural validity. MI was assessed across demographic (race, gender, grade, household income) and disease characteristic (illness duration, HbA1c) groups. Correlations with measures of psychological flexibility assessed additional convergent validity, and latent mean differences across groups were evaluated after confirming MI.

RESULTS

MI was supported. The DAASito-9 and -3 were correlated in expected directions with other psychological flexibility measures, HbA1c, and health-related quality of life.

CONCLUSIONS

The psychometric properties of the DAASito-9 and -3 support their use in research and clinical care of diverse youth with T1D. Significant differences in psychological flexibility across race, income, and glycemic health warrant further research and clinical intervention.

Understanding Variation in Longitudinal Data Using Latent Growth Mixture Modeling

OBJECTIVE

This article guides researchers through the process of specifying, troubleshooting, evaluating, and interpreting latent growth mixture models.

METHODS

Latent growth mixture models are conducted with small example dataset of N = 117 pediatric patients using Mplus software.

RESULTS

The example and data show how to select a solution, here a 3-class solution. We also present information on two methods for incorporating covariates into these models.

CONCLUSIONS

Many studies in pediatric psychology seek to understand how an outcome changes over time. Mixed models or latent growth models estimate a single average trajectory estimate and an overall estimate of the individual variability, but this may mask other patterns of change shared by some participants. Unexplored variation in longitudinal data means that researchers can miss critical information about the trajectories of subgroups of individuals that could have important clinical implications about how one assess, treats, and manages subsets of individuals. Latent growth mixture modeling is a method for uncovering subgroups (or "classes") of individuals with shared trajectories that differ from the average trajectory.