Disparities in Diabetes Distress and Nutrition Management Among Black and Hispanic Adults: A Mixed Methods Exploration of Social Determinants

Abstract

Purpose:

The purpose of this study was to explore self-reported diabetes management strategies, social determinants of health (SDOH), and barriers to care among people with diabetes receiving care in a safety-net setting to identify factors contributing to disparities in outcomes for Black and Hispanic adults and inform future interventions.

Methods:

Sequential, explanatory, mixed methods study comprised a survey of adults with diabetes seen in primary care at a safety-net hospital in New England, followed by qualitative semistructured interviews with a subset of the Black and Hispanic respondents. Descriptive statistics, chi-square and t tests were used to analyze quantitative data. The health equity implementation framework was used to guide qualitative data collection and directed content analysis.

Results:

A total of 496 respondents completed the survey; 48 Black and Hispanic adults participated in interviews. Diabetes-related distress was significantly higher among Black and Hispanic participants compared to White participants. Nutrition management use was significantly lower among Black and Hispanic participants. Qualitative findings suggest that SDOH and lack of education and support, specifically, nutrition and access to self-management resources, contributed to diabetes-related distress and prevented optimal self-management.

Conclusions:

High rates of diabetes-related distress and low rates of nutrition management were identified in Black and Hispanic adults in a safety-net setting. Qualitative interviews demonstrated a relationship between adverse SDOH and lack of nutrition education with diabetes distress and challenges to self-management, potentially contributing to disparities in outcomes. Findings suggest that increased uptake of nutrition therapy and self-management education and support may be critical for improving diabetes outcomes and promoting health equity.

Diabetes is increasingly prevalent and disproportionately burdens minoritized communities, including people from racial and ethnic minority groups and those experiencing poverty.^1,2 In the United States, significant racial and ethnic disparities in diabetes-related outcomes exist.^3,4 Black and Hispanic people with diabetes are less likely to achieve glycemic goals, are more likely to have diabetes-related complications, and have higher mortality than their White counterparts.^5–8

Disparities in diabetes care and outcomes have been shown to be influenced by multiple factors, including therapeutic inertia,⁹ clinician implicit bias,¹⁰ psychosocial distress,¹¹ and social determinants of health (SDOH),^12,13 that is, social, economic, and environmental conditions including access to and use of evidence-based therapies.^14–16 SDOH are also shown to influence diabetes self-management behaviors,^17,18 which consequently impact glycemia. Given these associations, interventions and research addressing adverse SDOH have been prioritized.^19,20

Although the association between adverse SDOH and negative diabetes-related outcomes is well established, gaps in our understanding of how SDOH along with other psychosocial factors impact diabetes self-management remain. Multiple prior qualitative studies have explored barriers to and facilitators of diabetes self-management in populations cared for in urban and safety-net health care settings, with findings identifying the influence of financial barriers²¹; social and medical supports, including trusted clinicians and access to self-management education; and health system resources on effective self-management for people living with diabetes.^22–26 However, among populations who experience high rates of adverse SDOH, such as those seen in safety-net health care settings, combined data examining the prevalence of, experience with, and associations between SDOH, psychosocial distress, and patient self-reported barriers to access and use of specific treatment strategies that may contribute to differences in outcomes are limited.²⁷ Additionally, patient preferences for health-care-system-based interventions to address challenges to diabetes management across different self-identified race and ethnic groups that experience outcome disparities are unclear because prior work has focused specifically on socioeconomic barriers.²⁸ Understanding patient self-reported challenges to diabetes management and preferences for health system interventions is particularly important in safety-net health care settings; these clinics are often challenged with constrained resources to provide care for populations with high rates of SDOH, lower rates of health literacy, and an increased burden of both diabetes and its related complications.^29–32 In safety-net settings, identification of patient-reported barriers to diabetes self-management and preferences for interventions is particularly important with respect to resource allocation and intervention acceptability.

Therefore, to address gaps in the literature the following research questions were posed:

Research Question 1: What are the associations between SDOH, diabetes-related psychosocial distress, and patient self-reported barriers to care access and treatment?

Research Question 2: What are patient-centered interventions to remediate identified barriers to reduce racial/ethnic disparities in diabetes outcomes?

To answer these questions and use the identified factors to inform implementation of patient-preferred strategies for achieving optimal diabetes management, this study explored self-reported diabetes management strategies, SDOH, and barriers to care to identify contributors to disparities in diabetes outcomes and future targets for intervention. Because quantitative data alone do not capture the intricacy of complex, multidimensional determinants of diabetes self-management, we used a sequential explanatory mixed methods design to contextualize and interpret quantitative results on SDOH and use of management strategies with qualitative data. This mixed methods design provided a deeper understanding of identified disparities by learning from those with lived experience.

Methods

Study Setting

This study was conducted in the general internal medicine practice (GIM) at the largest safety-net health care system in New England. The largest academic primary care practice in the system, GIM employs over 170 physicians, nurse practitioners, and resident trainees to care for approximately 41 000 patients annually. Nearly 75% of patients seen within this health care system are from minoritized backgrounds, including racial and ethnic minority groups and those with low income. Nearly 1 in 4 Black adults has type 2 diabetes (T2DM), and one in five Latino adults has T2DM, compared to roughly 1 in 10 adults at the state and national levels.² Furthermore, a higher proportion of Black (14.8%) and Hispanic (15.5%) adults in GIM had an A1C >9% compared to White adults with T2DM (10.8%).

Study Design

In this cross-sectional study, we used a sequential explanatory mixed methods design, which involved collecting and analyzing quantitative data first, followed by qualitative data to further explain quantitative results. First, we conducted surveys to identify racial and ethnic disparities across a variety of diabetes-related management domains, SDOH, and diabetes-related emotional distress. Next, we conducted in-depth qualitative interviews with a subset of survey respondents to further investigate and contextualize the initial quantitative results. Data integration was performed through a linked sampling technique (i.e., recruiting qualitative interview participants from the sample of survey respondents) and at the interpretation and reporting stages through a joint display, which highlighted the ways in which the qualitative interviews explained quantitative survey results. By presenting our quantitative and qualitative data side by side, the joint display structured our results in a visual comparison that allowed us to integrate the findings, connect them to a theoretical framework, and yield new mixed methods metainferences.³³

Study Participants

Patients who attended medical appointments within GIM between October 2021 and January 2022 were eligible to participate if they were at least 18 years of age, diagnosed with diabetes as identified in the Patient-Centered Medical Home Registry, and had a primary language of English, Spanish, or Haitian Creole as documented in the electronic medical record.

Data Collection: Instrument Development

Survey

A 21-item questionnaire (see supplementary material) was developed to examine factors that could affect outcomes for patients with diabetes, including assessment of diabetes treatment strategies such as medications and nutritional approaches, satisfaction and experience with care, SDOH, and diabetes-related emotional distress. Initially, we also collected sociodemographic information, including race, ethnicity, gender, highest level of education, and housing and food security status, as part of the survey (an additional 6 questions). After a week of pilot testing the survey in clinic, we received feedback from clinic staff and patients that the survey’s length and complexity were burdensome, resulting in a high noncompletion rate. To address this issue, we removed SDOH and demographic questions and reworded all questions to meet a 7-grade reading level. For the remainder of the study, we abstracted demographic data from electronic medical records.

Three questions related to treatment strategies participants use to manage their diabetes currently and historically were included. To assess diabetes treatment satisfaction and experience of care, 2 questions adapted from the Primary Care First-Patient Experience of Care Survey were included.³⁴ Additional questions to examine self-efficacy in diabetes management and health beliefs about diabetes were included.

The initial survey included 2 questions from the Centers for Medicare & Medicaid Services Accountable Health Communities (AHC) Health-Related Social Needs (HRSN) Screening Tool related to housing and food status.³⁵ These questions were removed from the survey after the first week of administration at the request of practice management to improve survey conciseness. However, we retained 2 questions regarding SDOH that prevented participants from treating their diabetes and accessing diabetes treatment (see supplemental materials). The listed social domains were adopted from the AHC HRSN Screening Tool and included housing instability, food insecurity, transportation problems, financial strain, employment, family and community support, and physical activity.³⁵

The short-form Problem Areas in Diabetes 5-item (PAID-5) scale was included to assess for diabetes-related emotional distress given the association with diabetes self-care behaviors and glycemia.³⁶ Additionally, this was included as a measure given evidence that psychoeducational interventions can both improve glycemic control and ameliorate distress, thereby making elevated rates of diabetes-related emotional distress an actionable finding.³⁷ The PAID-5 was selected given broad use, validation across several languages, and because overall length of the survey was constrained. Responses were scored on a Likert scale with a total score ≥8 (out of 20 possible) suggestive of diabetes-related emotional distress.³⁶

Interview Guide

A semistructured interview guide was developed by trained qualitative researchers (MD, SS, and KCJ) and consisted of 11 major questions, each with several probe questions (see supplemental materials). The Health Equity Implementation Framework (HEIF)³⁸ was selected to guide development of the interview guide and codebook because it integrates i-PARIHS (an implementation science framework)³⁹ and a health care disparities framework to understand, explain, and intervene on disparities in health care at multiple levels. Domains from the HEIF were integrated into the interview guide, including (1) characteristics of the “innovation,” or diabetes treatment strategy (ie, options for treating diabetes and barriers/facilitators for each option); (2) clinical encounter, provider factors (ie, expectations of and experiences with the diabetes care team); and (3) patient factors (ie, the influence of life circumstances, personal demographics, and emotional distress on diabetes treatment). These domains spanned across determinants of disparities in the inner context (local and organizational levels), outer context (health care system), and larger societal context (sociopolitical forces, physical structures, and economies).

In addition to the HEIF, survey results informed the interview guide by identifying salient topics that needed more in-depth exploration, including drivers of diabetes distress, experiences with self-management strategies, facilitators and barriers to treatment, and actionable care delivery suggestions. Both the survey and interview guide were revised by professional experts in diabetes (KLF), implementation science (MD, AW), qualitative methods (MD), health literacy (KK), and practice management (ST, SK-M).

Data Collection

The 21-item paper survey was administered in the clinic; front desk staff identified eligible patients during checkin, asked them their preferred language, and invited them to participate after providing detailed study information. Interested patients gave verbal consent in their preferred language at the time of survey distribution and completed the survey in English, Spanish, or Haitian Creole in the waiting room and/or exam room. An invitation to participate in follow-up interviews was included in the survey. Individuals who agreed to be contacted for an interview and identified as Black and/or Hispanic were recruited to participate in the qualitative stage using a purposive total population sampling strategy.

In-depth telephone interviews in participants’ preferred language were conducted using the semistructured interview guide. Each participant received a $50 gift card in the mail after completion of the interview. The Boston Medical Center/Boston University Medical Campus Institutional Review Board approved all study procedures.

Data Analysis

Quantitative Data

Paper survey results were entered electronically into REDCap.⁴⁰ Participants were divided into 5 racial/ethnic groups based on their self-reported race (Survey Version 1) or that listed in their medical record (Survey Version 2): (1) Hispanic, (2) Black, (3) White, (4) Asian, and (5) other. Surveys were analyzed using descriptive statistics. For each survey item, we compared responses across each category to determine if there were significant differences by race and ethnicity of participants using chi-square tests for categorical data and t tests for normally distributed continuous data. All statistical analyses were conducted with R version 4.1.2 (Vienna, Austria), with statistical significance assessed at α = .05.

Qualitative Data

All interviews were audio-recorded and transcribed verbatim. Interviews were conducted until thematic saturation was reached. We used a consensus qualitative analytic approach and directed content analysis.^41,42 The initial codebook was tested by the qualitative analysts (SS, KCJ, KLF) by independently coding the same interview transcripts and comparing coding results. After each round of consensus coding, the group met to discuss and reconcile coding discrepancies and modify the codebook accordingly. Consensus was achieved after the third transcript was coded, at which point, the codebook was finalized and remaining transcripts were coded independently.

After initial coding was complete, resulting in smaller analytic units to summarize large amounts of data, we used pattern coding to group the coded units into categories and themes that aligned with constructs from the HEIF. During this process, we used investigator triangulation to both develop the coding taxonomy and improve the reliability of the results.⁴³ NVivo qualitative data analysis software (Nvivo Release 1.6.1; QSR international Pty Ltd) was used to code and organize the data into distilled themes. The team then met to generate final themes and identify representative quotes.

Results

Out of 767 eligible patients, 496 individuals completed the survey (response rate 64.7%). Participant demographics are shown in Table 1. Briefly, approximately 60% of the participants were female, 71% were Black, 11% were Hispanic, and 10% were White. Out of the 496 survey respondents, 33.1% (n = 164) agreed to be contacted for a follow-up interview; 48 participants completed an interview lasting 30 to 60 minutes.

Table 1.

Participant Characteristics^a

Characteristic	Survey respondents (N = 466)	Interview participants (N = 48)
Gender
Male	183 (39.3)	35 (72.9)
Female	276 (59.2)	13 (27.1)
N/A	7 (1.5)
Race/ethnicity
Black or African American	332 (71.2)	40 (83.3)
Hispanic	52 (11.2)	8 (16.7)
White	47 (10.1)
Asian or Pacific Islander	28 (6.0)
Other	9 (1.9)
N/A	29 (6.2)
Age, y (mean)	61.0 (SD = 13.2)	60.4 (SD = 11.9)
Self-reported diabetes treatment
Oral medication	283 (57.1)
Insulin	148 (29.8)
Noninsulin injection medication	119 (24)
Diet	133 (26.8)

^aData are presented as n (%) unless otherwise noted.

Quantitative and qualitative results aligned with the major HEIF domains, including (1) characteristics of management strategies, (2) provider and diabetes care team factors, (3) patient factors, and (4) societal influence. Integrated, mixed methods results on each domain are reported in the following and outlined in Figure 1 and Table 2.

Figure 1.

Adaptation of the health equity implementation framework (HEIF) diagram to display qualitative findings.

Table 2.

Mixed Methods Results Matrix

Domain	Quantitative result	Qualitative theme	Mixed methods metainference
Characteristics of diabetes management strategies	Participants reported using multiple treatment strategies, the most common being pills. Compared to White participants, Black and Hispanic individuals reported significantly lower use of nutrition management.	Participants prefer using nutrition for diabetes management but lack practical nutrition knowledge and guidance on nutrition behavior change.	Qualitative data revealed possible reasons for the quantitative finding that Black and Hispanic participants use nutrition management less frequently than White participants. Qualitative data highlighted that although Black and Hispanic participants prefer using nutrition to medication, they lack knowledge on practical nutrition management.
Provider factors	Participants reported high satisfaction with primary care diabetes treatment, regardless of race/ethnicity.	Participants are most satisfied with their diabetes treatment when care is (1) patient-centered, (2) practical, and (3) tailored.	Qualitative data revealed the specific characteristics of diabetes treatment that contribute to the high satisfaction of care indicated by the quantitative data.
Patient factors	Participants reported high levels of diabetes distress, especially among Hispanic and Black individuals.	Participants face significant emotional distress related to living with diabetes, which is likely driven by (1) treatment-related concerns, (2) social determinants of health, and (3) psychological effects.	Confirmed by both quantitative and qualitative data, Black and Hispanic participants experience high levels of diabetes-related emotional distress. Qualitative data reveal that diabetes-related emotional distress, especially fear of complications, can be overwhelming and limit self-care. However, having strong social support can help ameliorate distress and improve self-management.
Societal influence	The majority of participants, regardless of race/ethnicity, reported social challenges to managing their diabetes. The most frequently reported challenge was food, followed by exercise, medication, and finances.	The high financial burden of diabetes self-management strategies is a major challenge, negatively impacting participants’ abilities to (1) eat healthy, (2) exercise, and (3) pay for medication and glucose monitoring devices.	Both quantitative and qualitative data suggested that participants face social determinants of health that challenge their diabetes management. Qualitative data suggested that financial barriers underlie the other social determinants reported quantitatively, including food, exercise, and medication.

Doman 1: Characteristics of Diabetes Management Strategies

Diabetes management strategies self-reported by participants are shown in Table 1. The only statistically significant racial and ethnic differences in reported rates of strategies were for nutrition. Compared to the 46.8% (n = 22) of White respondents who reported using nutrition to manage diabetes, there were significantly lower rates of nutrition management reported by Black patients (P = .003) and Hispanic patients (P = .007), with rates of 26.1% (n = 92) and 21.2% (n = 11), respectively.

Qualitative Theme: Participants Prefer Using Nutrition for Diabetes Management but Lack Practical Nutrition Knowledge and Guidance on Dietary Behavior Change

Participants shared that they saw nutrition management as a preferable strategy for managing diabetes as compared to pharmacotherapy.

I didn’t want to be on more medication, and before my A1C was bad, I didn’t want it to get worse so I started to tell myself like, okay, let me get ahead of this, let me eat as healthy as I can … I can lose weight and get my numbers lower, so I don’t have to get on more medication. (PID15)

However, education and guidance on how to implement nutritional changes is lacking.

The toughest thing for me was like learning how to eat in a different way … I wish that there were more resources around like behavior modification, because it just took me so long to get to this point … like classes to help you change your habits that will provide that support, because we know it’s a struggle to like, have to learn how to eat in a different way, how to think about food in a different way. (PID26)

Domain 2: Provider Factors

Across all racial and ethnic groups, participants reported high satisfaction with diabetes treatment in primary care. Overall, 91.1% (n = 452) of survey respondents agreed that they were “satisfied with [their] current primary care treatment,” 94.1% (n = 467) agreed that their “primary care team listens to [them] carefully,” and 93.1% (n = 462) agreed that their “primary care team explains [their] diabetes care plan clearly.” There were no statistically significant differences by race or ethnicity in this domain.

Qualitative Theme: Participants Are Most Satisfied With Their Diabetes Treatment When Care Is (1) Patient-Centered, (2) Practical, and (3) Tailored

Participants emphasized that a patient-centered approach that is thorough and supportive fosters a positive provider-patient relationship.

I love [Dr. Name] because she’s real, she takes the time, and she speaks truth … there’s a lot of doctors that will just give you your diagnosis and tell you to go away. Do the best you can. But with her she’s been Godsent … we talk, and things are really explained. So, that’s why I don’t stress or worry about anything, because I know, what I don’t understand, I ask questions. You know and I get the answer. (PID45)

Diabetes education and clinical guidance that are practical and tailored lead to self-efficacy and confidence in participant diabetes self-management.

I think like there should be like, not only a cooking class but like a class to remind people who have diabetes that way to balance their life as well because taking medication every day may not be easy. (PID13)

What makes a visit helpful is when I go in person to see my diabetes specialist and he’s like okay, these are your numbers, this is specifically what you can do to make them better. (PID15)

Domain 3: Patient Factors

Despite high satisfaction with diabetes treatment, there was a high prevalence of diabetes distress among survey respondents, with 62.1% (n = 308) of respondents scoring ≥8 on the PAID-5 scale. The median PAID-5 score among all respondents was 10. There were differences in both median PAID-5 score and prevalence of diabetes-related emotional distress across race and ethnicity. The differences between White and Hispanic participants were statistically significant, with median PAID-5 score among White respondents of 6, compared to 13 among Hispanic respondents (P = .009); 48.9% (n = 23) of White individuals had scores suggestive of distress (≥8), compared to 73.1% (n = 38) of Hispanic individuals (P < .001). Black participants had a comparatively high median PAID-5 score of 10 and high prevalence of diabetes-related emotional distress (60.9%, n = 215), but the differences between Black and White participants were not statistically significant. Among the subgroup of Hispanic and Black individuals selected for qualitative interviews, the majority (n = 31, 64.6%) had PAID-5 score suggestive of diabetes distress based on their survey responses.

Qualitative interviews identified several patient-related factors as potential drivers for the high rates of diabetes distress in this population, including the psychological effects of living with diabetes (ie, fear of existing and future diabetes-related complications) and social support.

Qualitative Theme: Psychological Distress Related to Living With Diabetes, Particularly Fear of Existing and Future Comorbidities and Complications, Is Prevalent and Impacts Self-Care

The fear of what the effects of diabetes have on your body … it crosses my mind, makes me afraid. You know as much as you’re doing this, you’re dieting, you don’t know the other organs that it will still affect … they said it can cause kidney problems, you can’t do this, it can affect your eyes. (PID23)

Participants highlighted the ways in which these negative emotions impact their diabetes self-management through reduced self-care.

Some people go as far as like not wanting to take their medicine, or even being in the denial of having diabetes. Like I was for years before I actually started taking care of myself. (PID8)

Although participants highlighted how diabetes-related emotional distress negatively impacts self-care, they identified social support networks, including friends, family, and coworkers, as a source of positive emotional and practical support for a variety of diabetes self-management activities.

Qualitative Theme: Social Support Helps Address Diabetes-Specific Self-Management Challenges

[My family members] make sure that I remember to take my medication every day, always ask how is it going … am I using the resources provided to me, making sure that I don’t eat anything that I’m not supposed to that has too much carbs, or too much, you know, red meat or whatever it is that the doctor suggests with the nutritionist. (PID13)

Domain 4: Societal Influence

In addition to inner context and patient-level factors, determinants in the societal context were also identified as contributors for the high prevalence of diabetes distress among Black and Hispanic participants. Across both survey versions, 67.9% (n = 337) of respondents reported SDOH that challenged diabetes management. The most frequently reported challenge was “food/diet,” which was identified as a barrier by 33.1% (n = 164) of respondents. In the first survey version with 377 respondents (>75% of the sample), we included a food security question adopted from the Centers for Medicare & Medicaid Services AHC HRSN Screening Tool: “(29) Within the past year, you worried that your food would run out before you got money to buy more.” In response to this question, 11.6% (n = 39) reported often true, 27.8% (n = 93) reported sometimes true, and 60.6% (n = 203) reported never true.

Additionally, 27.0% (n = 134) of participants selected “exercise,” 23.0% (n = 114) selected “medication,” and 12.9% (n = 64) selected “finances” as challenges to managing their diabetes. The majority of respondents (53.0%, n = 263) also reported external barriers to accessing primary care, including competing demands (19.2%, n = 95), COVID-19-related concerns (13.1%, n = 65), transportation (12.9%, n = 64), and lack of time (9.1%, n = 45). There were no statistically significant differences across race and ethnicity in reported rates of SDOH.

Qualitative Theme: The High Financial Burden of Diabetes Self-Management Strategies Is a Major Challenge, Negatively Impacting Participants’ Abilities to (1) Eat Healthy, (2) Exercise, and (3) Obtain Medication and Glucose Monitoring Devices

Eating healthy is expensive … so most of the time you get stuck eating the cheaper like bullshit. (PID10)

It would be nice if there was some type of program connected to a gym or two … that can help us have a better discount. (PID17)

So far, the only problems I’ve had is paying for [medication] … because I don’t have $210 to throw out, and I just stay to my insulin and wait for the Trulicity and everything to come through. I was 2 months without. (PID4)

Discussion

In this mixed methods study, we identified disparities in the use of dietary management for diabetes and in rates of diabetes-related emotional distress among Black and Hispanic people with diabetes cared for in a large, urban, academic, safety-net primary care practice in the United States. Although participants expressed high satisfaction with diabetes care, qualitative interviews identified multiple challenges contributing to disparities in nutrition management of diabetes, including lack of diabetes and nutrition specific education and adverse SDOH. Qualitative interviews identified these factors and fears about development of complications as contributors to diabetes-related emotional distress.

Despite clinical practice guideline recommendations⁴⁴ and evidence for the benefit of diabetes self-management education and support⁴⁵ and medical nutrition therapy,⁴⁶ our qualitative interviews suggest that these services are underused, in line with prior studies of newly diagnosed Medicare and commercially insured people with diabetes.^47,48 Importantly, however, our qualitative interviews reveal that access to diabetes self-management education and support and medical nutrition therapy are preferred and desired by Black and Hispanic adults with diabetes as resources for management of diabetes and are considered by patients to be an integral component of a patient-centered and tailored diabetes management program. These findings raise the question of clinician-level factors that may influence referrals to diabetes self-management education and support and medical nutrition therapy that requires further study.

In comparison to prior studies, our findings demonstrate substantially higher rates of diabetes-related emotional distress. Diabetes-related emotional distress was prevalent in 62% of our sample, as compared to the approximately 36% prevalence previously reported in a meta-analysis,⁴⁹ and higher than the rate reported in a study of individuals with food insecurity.⁵⁰ Our findings of the highest rates of diabetes-related emotional distress among Hispanic adults, followed by Black adults and lowest in White adults, is consistent with prior literature demonstrating differences in diabetes by race and ethnicity.⁵¹ Furthermore, this study adds to the understanding of prevalence of diabetes-related emotional distress in adults from racial and ethnic minority groups because in comparison to other cross-sectional evaluations of US adults with diabetes measuring diabetes-related emotional distress, this study had a much greater proportion of non-White participants, with >80% of the sample identifying as Black or Hispanic.

Although additional attention must be paid to addressing structural determinants of disparities in diabetes outcomes, this study identifies opportunities for health care systems to better support and care for people with diabetes. Based on the results of our study, improved clinical and social support may help address challenges related to managing and living with diabetes for minoritized groups disproportionately impacted by diabetes. These findings are consistent with the literature, suggesting that psychoeducational interventions³⁷—including those with foundations in diabetes self-management education and support—are effective at addressing diabetes-specific emotional distress and treatment outcomes, including glycemia. Additionally, our qualitative findings suggest that a focus on increasing referral rates and attendance to visits for diabetes self-management education and support offerings and medical nutrition therapy, both evidence-based and guideline-recommended interventions,⁴⁴ would be both consistent with patient preferences for diabetes management and may address drivers of diabetes-related emotional distress in this patient population.

This study has several strengths and weaknesses. The survey was offered in English, Spanish, and Haitian Creole—the 3 most common primary languages spoken in the primary care practice—and therefore captured a broad and diverse set of patient experiences. This study helps to fill gaps in the literature regarding prevalence of diabetes-related emotional distress and self-reported challenges and preferences for diabetes management in individuals from minoritized communities served by safety-net health care settings in the United States. Additionally, the explanatory sequential design allowed for increased depth of understanding of disparities in management strategies that can influence downstream glycemic outcomes for minoritized people with diabetes.

However, there are several limitations to this study. First, glycemic data were not collected from patients because this study was not intended to examine the association of management strategies or barriers to care with glycemia. Second, participants were recruited from those who attended in-person visits and therefore limited the sample population, especially during the COVID-19 virus state of emergency, and excluded individuals who face additional adverse SDOH barriers to presenting for in-person care. Additionally, although we aimed to achieve a proportional representation to the clinic population with diabetes, which is 60% Black, 18% Hispanic, and 10% White, Black patients were overrepresented and Hispanic patients underrepresented in our survey sample. To improve survey brevity and match the health literacy of the patient population, the only validated survey measure included was the PAID-5 scale.³⁶ Survey adaptations contributed to the high response rate. Finally, because this study was conducted at a single internal medicine primary care clinic affiliated with an urban, academic, safety-net hospital, our findings may not be generalizable, although they are likely transferrable to other urban safety-net settings.

Conclusion

Our study identified racial and ethnic disparities in diabetes-related emotional distress and in use of nutritional management strategies for diabetes management, driven in part by insufficient diabetes and nutrition education and guidance. Evidence-based interventions, including diabetes self-management education and support, medical nutrition therapy, and peer support interventions, align with patient-reported needs and values and should be prioritized by safety-net health care settings to address identified challenges with diabetes self-management, improve glycemia and quality of life for people with diabetes, and promote diabetes health equity.