Joni S. Williams

Influence of Race, Ethnicity and Social Determinants of Health on Diabetes Outcomes

Background: There is strong evidence that race, ethnicity and social determinants of health significantly influence outcomes for patients with diabetes. A better understanding of the mechanisms of these relationships or associations would improve development of cost‐effective, culturally tailored programs for patients with diabetes. Methods: This article reviews the current state of the literature on the influence of race and ethnicity and social determinants of health on process of care, quality of care and outcomes for diabetes, with particular emphasis on the rural South to give an overview of the state of the literature. Results: The literature review shows that racial or ethnic differences in the clinical outcomes for diabetes, including glycemic, blood pressure (BP) and lipid control, continue to persist. In addition, the literature review shows that the role of social determinants of health on outcomes, and the possible role these determinants play in disparities have largely been ignored. Psychosocial factors, such as self‐efficacy, depression, social support and perceived stress, show consistent associations with self‐care, quality of life and glycemic control. Neighborhood factors, such as food insecurity, social cohesion and neighborhood esthetics have been associated with glycemic control. Perceived discrimination has also been associated with self‐care and the psychological component of quality of life. Conclusion: Healthcare professionals need to be skilled in assessing social determinants of health and taking them into consideration in clinical care. In addition, more research is needed to identify the separate and combined influence of race and ethnicity and social determinants of health on process of care, quality of care and outcomes in diabetes, especially in the South, where the burden of disease is particularly high.

Achieving Equity in an Evolving Healthcare System: Opportunities and Challenges

For decades, disparities in health have been well documented in the United States and regrettably, remain prevalent despite evidence and appeals for their elimination. Compared with the majority, racial and ethnic minorities continue to have poorer health status and health outcomes for most chronic conditions, including diabetes mellitus, cardiovascular disease, cancer and end-stage renal disease. Many factors, such as affordability, access and diversity in the healthcare system, influence care and outcomes, creating challenges that make the task of eliminating health disparities and achieving health equity daunting and elusive. Novel strategies are needed to bring about much needed change in the complex and evolving United States healthcare system. Although not exhaustive, opportunities such as (1) developing standardized race measurements across health systems, (2) implementing effective interventions, (3) improving workforce diversity, (4) using technological advances and (5) adopting practices such as personalized medicine may serve as appropriate starting points for moving toward health equity. Over the past several decades, diversity in the U.S. population has increased significantly and is expected to increase exponentially in the near future. As the population becomes more diverse, it is important to recognize the possibilities of new and emerging disparities. It is imperative that steps are taken to eliminate the current gap in care and prevent new disparities from developing. Therefore, we present challenges and offer recommendations for facilitating the process of eliminating health disparities and achieving health equity across diverse populations.

The Association Between Multimorbidity and Quality of Life, Health Status and Functional Disability.

Introduction: Approximately 50% of adults have multimorbidity (MM) that is associated with greater disability, poorer quality of life (QOL) and increased psychological distress. This study assessed the association between MM and QOL, health status and functional disability in U.S. adults. Methods: Cross‐sectional study of 23,789 patients from 2011 Medical Expenditure Panel Survey was conducted. Mean scores were calculated for QOL (physical component score [PCS] and mental component score [MCS]) and proportions for functional limitation (activities of daily living [ADL]; instrumental ADL [IADL] and physical functioning). Health status was assessed by depression and serious psychological distress. Regression models evaluated associations between MM and QOL, functional health status and functional limitations, while adjusting for confounders. Results: Approximately 53% of 45‐64‐year‐olds and 84% of those ≥65‐years‐old had MM. In adjusted models, ≥3 conditions were significantly associated with poorer outcomes—PCS QOL (&bgr; = −9.15; 95% CI: −9.69 to −8.61), MCS QOL (&bgr; = −1.98; 95% CI: −2.43 to −1.52), ADL (odds ratio [OR] = 5.80; 95% CI: 2.27–14.8), IADL (OR = 3.99; 95% CI: 2.31–6.88) and physical functioning (OR = 16.8; 95% CI: 12.0‐23.6) compared with 1–2 conditions. Depression (PCS QOL: &bgr; = −4.02; 95% CI: −4.89 to −3.15; MCS QOL: &bgr; = −12.5; 95% CI: −13.2 to −10.9; ADL: OR = 2.49; 95% CI: 1.65‐3.76; IADL: OR = 2.65; 95% CI: 1.88–3.72; physical functioning: OR = 2.44; 95% CI: 1.99–2.99) and serious psychological distress (PCS QOL: &bgr; = −3.16; 95% CI: −4.30 to −2.03; MCS QOL: &bgr; = −11.8; 95% CI: −12.8 to −10.8; ADL: OR = 1.57; 95% CI: 0.95–2.60; IADL: OR = 1.13; 95% CI: 0.80–1.59 and physical functioning: OR = 1.41; 95% CI: 1.11–1.78) were significantly associated with adverse outcomes. Conclusions: In this nationally representative sample of U.S. adults, MM was significantly associated with poorer QOL, functional health status and physical functioning, when adjusting for relevant confounders. A holistic view of the complexities associated with MM must dictate comprehensive care.

Depressive symptoms, serious psychological distress, diabetes distress and cardiovascular risk factor control in patients with type 2 diabetes.

OBJECTIVE This study examined the association between cardiovascular disease (CVD) risk factor control and elevated depressive symptoms (EDS), serious psychological distress (SPD), and diabetes distress (DD) in patients with type 2 diabetes (T2DM). METHODS This was a cross-sectional study of adults seen at an academic medical center and Veterans Affairs Medical Center in the southeastern US. Linear regression models were computed using CVD risk factors as clinically meaningful outcomes (glycosylated hemoglobin A1c (HbA1c); systolic (SBP) and diastolic (DBP) blood pressure; and low-density lipoprotein cholesterol (LDL-C)); EDS, SPD, and DD were primary independent variables. Covariates included sociodemographics and comorbidities. RESULTS The sample consisted of 361 adults. Correlation analyses showed significant relationships between DD and HbA1c, DBP, and LDL-C. Adjusted linear regression models showed DD to be significantly associated with HbA1c and LDL-C, and SPD to be significantly associated only with LDL-C. In the fully adjusted model, DD remained significantly associated with HbA1c (β=4.349; 95% CI (-0.649, 2.222)). CONCLUSIONS In this sample of adults with T2DM, DD and SPD were significantly associated with CVD risk factors; however, after controlling for covariates, only DD was shown to be significantly associated with poor glycemic control. PRACTICE IMPLICATIONS Strategies are warranted to examine the relationship between DD and CVD risk factor control in patients with T2DM.

Pathways for the relationship between diabetes distress, depression, fatalism and glycemic control in adults with type 2 diabetes

BACKGROUND The aim of this study was to examine the mechanism by which depressive symptoms, diabetes distress, and diabetes fatalism together influence diabetes outcomes using structured equation modeling. METHODS 615 adults with type 2 diabetes were recruited from two primary care clinics in the southeastern United States. Psychosocial factors found to be associated with diabetes outcomes were measured using validated questionnaires. Structured equation modeling (SEM) was used to investigate the relationship between diabetes fatalism, depressive symptoms, diabetes distress, self-care and glycemic control. RESULTS The final model (chi2(903)=24,088.91, p<0.0001, R2=0.93, RMSEA=0.05 and CFI=0.90) showed that higher diabetes distress was directly significantly related to a decreased self-care (r=-0.69, p<0.001) and increased HbA1c (r=0.69, p<0.001). There was no significant direct association between depressive symptoms or fatalism, and glycemic control or self-care. There was, however, an indirect association between increased depressive symptoms and increased fatalism, explained through the direct association with diabetes distress in that higher depressive symptoms (0.76, p<0.001) and higher fatalism (0.11, p<0.001) were significantly associated with higher diabetes distress. CONCLUSION Diabetes distress serves as a pathway through which depressive symptoms and fatalism impact both glycemic control and self-care. In addition, pathways between diabetes distress and both self-care behaviors and glycemic control in patients with type 2 diabetes remained separate, suggesting the need to address both psychological and behavioral factors in standard diabetes care, rather than focusing on psychological care primarily through support for self-management and treatment of depression.

Socioeconomic Status and Cardiovascular Risk Control in Adults With Diabetes

Objective: To examine the association between subjective social status (SSS) and objective social status (OSS) and cardiovascular disease (CVD) risk factors in adults with type 2 diabetes. Methods: Adult study participants (N = 358) were recruited from 2 primary care settings. The CVD risk factors included hemoglobin A1c (HbA1c), systolic blood pressure and diastolic blood pressure (DBP) and low‐density lipoprotein cholesterol (LDL‐C). The OSS was assessed by income, education and employment. The SSS was measured using the validated MacArthur Scales of Subjective Social Status to demarcate self‐reported perceptions of having the most money, education and respected job using a ladder scale (1 = rung 1, 10 = rung 10). Multiple linear regression was used to examine associations between CVD risk factors and SSC and OSS controlling for age, sex, race or ethnicity, marital status, employment status, income, study site, comorbidity, education and insurance status. Results: Fully adjusted models showed that rung 2 (P = 0.029), rung 3 (P = 0.032), rung 8 (P = 0.049) and rung 9 (P = 0.032) of the SSS to be significantly associated with poorer DBP. Annual income ≥

Meaning of illness and quality of life in patients with type 2 diabetes.

75,000 was significantly associated with lower LDL‐C (P = 0.021). Employment was associated with lower HbA1c (P = 0.036), but higher LDL‐C (P = 0.002). Conclusions: The SSS and OSSS levels are differentially associated with HbA1c, DBP and LDL‐C. Findings provide new information about patients’ perspectives of the relationship between social status and diabetes‐related outcomes.

A Patient and Provider Research Agenda on Diabetes and Hypertension Management

BACKGROUND Investigations into personal factors influencing quality of life are important for those developing strategies to support patients with diabetes. This study aimed to investigate the influence of meaning of illness on quality of life in patients with type 2 diabetes. METHODS Veterans from primary care clinics in the southeastern United States completed a questionnaire including questions from the validated 5-scale Meaning of Illness Questionnaire (MIQ). Unadjusted and adjusted linear regression models investigated the physical and mental components of quality of life with the 5 MIQ factors. RESULTS The sample comprised 302 Black and White veterans. The physical component of quality of life (PCS) was positively associated with type of stress/attitude of harm (β = 2.43, CI: 0.94 to 3.93) and challenge/motivation/hope (β = 3.02, CI: 0.40 to 5.64) after adjustment, whereas the mental component of quality of life (MCS) was positively associated with the degree of stress/change in commitment (β = 2.58, CI: 0.78 to 4.38), and negatively associated with challenge/motivation/hope (β = -2.55, CI: -4.99 to -0.11). CONCLUSION Attitudes of challenge, motivation and hope had opposite effects on mental and physical components of quality of life in this sample of veterans. Additionally, whereas, the type of stress and attitude towards harm or loss was associated with the physical component, the degree of stress and change in commitments was associated with the mental component. This suggests addressing the meaning of an illness may be complex but is an important consideration in improving both physical and mental components of quality of life in patients with type 2 diabetes.

Meaning of illness and self-care in patients with type 2 diabetes.

INTRODUCTION A demonstration project in Richmond, Virginia involved patients and other stakeholders in the creation of a research agenda on dietary and behavioral management of diabetes and hypertension. Given the impact of these diseases on morbidity and mortality, considerable research has been directed at the challenges patients face in chronic disease management. The continuing need to understand disparities and find evidence-based interventions to improve outcomes has been fruitful, but disparities and unmet needs persist. METHODS The Stakeholder Engagement in Question Development (SEED) method is a stakeholder engagement methodology that combines engagement with a review of available evidence to generate research questions that address current research gaps and are important to patients and other stakeholders. Using the SEED method, patients and other stakeholders participated in research question development through a combination of collaborative, participatory, and consultative engagement. Steps in the process included: (1) identifying the topic and recruiting participants; (2) conducting focus groups and interviews; (3) developing conceptual models; (4) developing research questions; and (5) prioritizing research questions. RESULTS Stakeholders were involved in the SEED process from February to August 2015. Eighteen questions were prioritized for inclusion in the research agenda, covering diverse domains, from healthcare provision to social and environmental factors. Data analysis took place September to May 2016. During this time, researchers conducted a literature review to target research gaps. CONCLUSIONS The stakeholder-prioritized, novel research questions developed through the SEED process can directly inform future research and guide the development of evidence that translates more directly to clinical practice.

Behavioral Health and Diabetes

Purpose The purpose of this study was to assess the relationship between meaning of illness, diabetes knowledge, self-care understanding, and behaviors in a group of individuals with type 2 diabetes. Methods Patients diagnosed with type 2 diabetes completed questionnaires with measures for diabetes knowledge, self-care understanding, diet adherence, and control problems based on the validated Diabetes Care Profile, as well as a 5-factor Meaning of Illness Questionnaire (MIQ) measure. Linear regression investigated the associations between self-care outcomes and the 5 MIQ factors. Results After adjustment for possible confounders, both diabetes self-care understanding and diet adherence were negatively and significantly associated with little effect of illness. Control problems were negatively associated with degree of stress/change in commitments. Diabetes knowledge was not significantly associated with meaning of illness. Conclusion Aspects of the meaning attributed to illness were significantly associated with self-care in patients with type 2 diabetes. Therefore, cognitive appraisals may explain variances observed in self-care understanding and behaviors. Based on these results, it is important to understand the negative effect that diabetes could have when promoting self-care understanding and diet adherence. In addition, it shows that helping patients address the stress and changing commitments that result from diabetes may help decrease the amount of diabetes control problems, even if there is little effect on diabetes understanding. Taking these differences into account may help in creating more personalized and effective self-care education plans.