The Influence of Health Insurance Stability on Racial/Ethnic Differences in Diabetes Control and Management

An Integrative Review of Social Determinants of Glycemic Targets Achievement in Adults with Type 2 Diabetes in the United States

Several individual social determinants of health have been identified as significant factors contributing to achieving glycemic targets (glycated hemoglobin < 7). However, it remains unclear how these social variables individually or collectively contribute to glycemic targets among adults with type 2 diabetes (T2D) in the United States (U.S.) The purpose of the current integrative review (IR) was to describe and synthesize findings from studies on social determinants of glycemic target achievement in adults with T2D in the U.S. and integrate them into the United States Department of Health and Human Services Conceptual Framework. The databases searched included PubMed, CINAHL Plus with Full Text, Medline with Full Text [EBSCO], Google Scholar, bibliography, and hand searching. A total of 948 records were identified. After excluding duplicates and irrelevant studies based on inclusion and exclusion criteria through title, abstract, and full-text screening, 13 studies were finally included in this IR. The results revealed that race/ethnicity, economic access and stability, educational access and quality, healthcare access and quality, neighborhood and built environment, and social and community context contribute to glycemic target achievement among adult patients with T2D in the U.S. Integrating findings from key studies on social determinants of glycemic health may contribute to developing interventions aimed at reducing and eventually eradicating health disparities for individuals with and at risk for T2D in the U.S.

The association between variability of risk factors and complications in type 2 diabetes mellitus: a retrospective study

The variability in diabetes risk factors, such as uric acid and lipids, may influence the development of complications. This study aimed to investigate the influence of such variability on the occurrence of diabetic complications. A retrospective analysis of electronic medical records was conducted with type 2 diabetic patients who received treatment at a tertiary care hospital in Chengdu, Sichuan Province, between 2013 and 2022. The risk factor variability is presented as the standard deviation (SD). The associations between the variability and complications were examined using a binary logistic regression model. The study included 369 patients with type 2 diabetes. The findings revealed that outpatient special disease management served as a protective factor against the development of complications [OR = 0.53, 95% confidence interval (CI) (0.29-0.10)], particularly for the prevention of diabetic peripheral neuropathy [OR = 0.51, 95% CI (0.30-0.86)]. Variability in total cholesterol (TC-SD) was found to be a risk factor for the development of complications [OR = 2.42, 95% CI (1.18-4.97)] and acted as a risk factor for diabetic peripheral vasculopathy [OR = 2.50, 95% CI (1.25-5.02)]. TC-SD is a risk factor for the occurrence of diabetic peripheral neuropathy and diabetic peripheral vasculopathy, whereas outpatient special disease management functions as a protective factor against complications and diabetic peripheral neuropathy. Thus, in addition to glycaemic control, the regulation of lipid levels should be emphasized, particularly among patients without outpatient special disease management, to delay the onset of complications.

Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions

Background

Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality.

Methods

We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes.

Discussion

Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Healthcare cost coverage inequality and its impact on hypertension and diabetes: A five-year follow-up study in a Malaysian rural community

Background and Aims

Inequality in health care access is a socioeconomic driver for non-communicable disease related risk factors. This study examined the inequality trend in healthcare cost coverage (HCC) compared to private health insurance (PHI) coverage, a subtype of HCC, over 5 years. The study will also determine the association between HCC (and PHI) and the status of hypertension and diabetes diagnosis.

Method

The rich-poor ratio, concentration curve and concentration index were derived to determine the level of inequality. Furthermore, logistic regression was done to determine the association between HCC and the status of hypertension and diabetes.

Results

The PHI group (rich-poor ratio: 1.4 [rich: 454, poor: 314] and 2.6 [rich: 375, poor: 142]; concentration index: 0.123 [95% confidence interval, CI: 0.093-0.153] and 0.144 [95% CI: 0.109-0.178] in 2013 and 2018, respectively) has relatively higher inequality compared with the HCC group (rich-poor ratio: 0.9 [rich: 307, poor: 337] and 1.1 [rich: 511, poor: 475]; concentration index: -0.027 [95% CI: -0.053 to -0.000] and -0.014 [95% CI: -0.033 to 0.006] in 2013 and 2018, receptively). Contrasting to the observation with the HCC group, PHI was associated with higher odds for hypertension (adjusted odds ratio [aOR] = 1.252, p = 0.01, 95% CI: 1.051-1.493) and diabetes (aOR = 1.287, p = 0.02, 95% CI: 1.041-1.590) in 2018.

Conclusion

Over 5 years, the inequality in PHI coverage remained higher compared with HCC, which suggests that the rich enjoyed private healthcare more. Furthermore, those with PHI were more likely to report known hypertension and diabetes in 2018. It is reasonable to assume that those with PHI are more likely to have earlier diagnoses compared to others and are more likely to be aware of their condition. Policymakers need to identify strategies that can narrow the existing gap in quality and type of service between the private and public health sectors.

Examining Health Inequities in A1C Control over Time across Individual, Geospatial, and Geopolitical Factors among Adults with Type 2 Diabetes: Analyses of a Sample from One Commercial Insurer in a Southern State

INTRODUCTION

Type 2 diabetes impacts millions and poor maintenance of diabetes can lead to preventable complications, which is why achieving and maintaining target A1C levels is critical. Thus, we aimed to examine inequities in A1C over time, place, and individual characteristics, given known inequities across these indicators and the need to provide continued surveillance.

METHODS

Secondary de-identified data from medical claims from a single payer in Texas was merged with population health data. Generalized Estimating Equations were utilized to assess multiple years of data examining the likelihood of having non-target (>7% and ≥7%, two slightly different cut points based on different sources) and separately uncontrolled (>9%) A1C. Adults in Texas, with a Type 2 Diabetes (T2D) flag and with A1C reported in first quarter of the year using data from 2016 and 2019 were included in analyses.

RESULTS

Approximately 50% had A1Cs within target ranges (<7% and ≤7%), with 50% considered having non-target (>7% and ≥7%) A1Cs; with 83% within the controlled ranges (≤9%) as compared to approximately 17% having uncontrolled (>9%) A1Cs. The likelihood of non-target A1C was higher among those individuals residing in rural (vs urban) areas (P < .0001); similar for the likelihood of reporting uncontrolled A1C, where those in rural areas were more likely to report uncontrolled A1C (P < .0001). In adjusted analysis, ACA enrollees in 2016 were approx. 5% more likely (OR = 1.049, 95% CI = 1.002-1.099) to have non-target A1C (≥7%) compared to 2019; in contrast non-ACA enrollees were approx. 4% more likely to have non-target A1C (≥7%) in 2019 compared to 2016 (OR = 1.039, 95% CI = 1.001-1.079). In adjusted analysis, ACA enrollees in 2016 were 9% more likely (OR = 1.093, 95% CI = 1.025-1.164) to have uncontrolled A1C compared to 2019; whereas there was no significant change among non-ACA enrollees.

CONCLUSIONS

This study can inform health care interactions in diabetes care settings and help health policy makers explore strategies to reduce health inequities among patients with diabetes. Key partners should consider interventions to aid those enrolled in ACA plans, those in rural and border areas, and who may have coexisting health inequities.

Definitions of successful aging among middle-aged Latinas residing in a rural agricultural community

INTRODUCTION

Latinos are the fastest growing aging population in the U.S. However, there has been limited attention to conceptualizing successful aging among Latinos, especially those residing in rural communities. Latinos are the largest racial or ethnic group residing in rural underserved communities and rural Latinos experience significant structural barriers to access the conditions they need to age well. The goal of this study is to make unique contributions to the successful aging literature by describing what successful aging means for middle-aged Latinas residing in a rural community.

METHODS

This qualitative paper used inductive thematic content analysis to examine definitions of successful aging among Latina women (n = 40) residing in an underserved agricultural community and entering mid-life (mean = 49 years old; age range 40-64).

RESULTS

With regards to definitions of successful aging, four themes emerged: 1) Having good health; 2) maintaining an active lifestyle; 3) the wellbeing of one's children; and 4) being independent.

DISCUSSION

Participants' definitions of successful aging aligned to some extent with existing frameworks, specifically related to health and independence. However, middle-aged Latina participants' unique definitions of successful aging also diverged from existing frameworks, especially around the wellbeing of their children and the importance of work as a way of maintaining an active lifestyle. More research is needed to understand the unique social context and circumstances of middle-aged Latinos residing in rural communities and how they influence their aging journeys. This can provide important information for the development of culturally sensitive services, interventions, and policies to help Latinos age well.

A study of factors influencing long-term glycemic variability in patients with type 2 diabetes: a structural equation modeling approach

Aim

The present study aims to utilize structural equation modeling (SEM) to investigate the factors impacting long-term glycemic variability among patients afflicted with type 2 diabetes.

Method

The present investigation is a retrospective cohort study that involved the collection of data on patients with type 2 diabetes mellitus who received care at a hospital located in Chengdu, Sichuan Province, over a period spanning from January 1, 2013, to October 30, 2022. Inclusion criteria required patients to have had at least three laboratory test results available. Pertinent patient-related information encompassing general demographic characteristics and biochemical indicators was gathered. Variability in the dataset was defined by standard deviation (SD) and coefficient of variation (CV), with glycosylated hemoglobin variation also considering variability score (HVS). Linear regression analysis was employed to establish the structural equation models for statistically significant influences on long-term glycemic variability. Structural equation modeling was employed to analyze effects and pathways.

Results

Diabetes outpatient special disease management, uric acid variability, mean triglyceride levels, mean total cholesterol levels, total cholesterol variability, LDL variability, baseline glycated hemoglobin, and recent glycated hemoglobin were identified as significant factors influencing long-term glycemic variability. The overall fit of the structural equation model was found to be satisfactory and it was able to capture the relationship between outpatient special disease management, biochemical indicators, and glycated hemoglobin variability. According to the total effect statistics, baseline glycated hemoglobin and total cholesterol levels exhibited the strongest impact on glycated hemoglobin variability.

Conclusion

The factors that have a significant impact on the variation of glycosylated hemoglobin include glycosylated hemoglobin itself, lipids, uric acid, and outpatient special disease management for diabetes. The identification and management of these associated factors can potentially mitigate long-term glycemic variability, thereby delaying the onset of complications and enhancing patients' quality of life.

Decision Making and Blood Sugar Indicators in Older African American Adults

Objectives: Decision making is a modifiable behavior associated with health outcomes. We investigated the association of decision making with blood sugar indicators in older community-dwelling African American adults. Methods: Participants were 328 older African American adults from community-based studies (mean age = 78). Decision making was assessed using a performance-based measure (range: 0-12). Blood sugar indicators were non-fasting hemoglobin A1c and blood glucose. Using regression, we assessed the relationship between decision making and each blood sugar indicator, controlling for demographics. We additionally examined if an association varied by known diabetes diagnosis. Results: Lower decision making was associated with higher HbA1c (b: -0.05, p-value: .03), but not blood glucose. In an interaction analysis, the association of lower decision making with higher levels of HbA1c was present only among individuals with known diabetes (b (with diabetes): -0.13, p-value: <.01). Discussion: Decision making may contribute to glycemic control in African American older adults with diabetes.

Bridging the LatinX community care gap

PURPOSE OF REVIEW

To summarize current developments aimed at improving diabetes care utilizing novel and culturally sensitive strategies to bridge the care gap in the LatinX community.

RECENT FINDINGS

There is more than a decade of literature describing disparities in diabetes care and outcomes particularly involving ethnic and racial minorities leading to higher incidence of acute and long-term complications. Social determinants of health including language and cultural barriers in the LatinX community are important determining factors. We found three novel strategies reported in the current literature aimed at closing the diabetes care gap in LatinX patients: community-based efforts: community health workers (CHWs) and peer-led; shared medical and educational models; and adapting telehealth group appointments.

SUMMARY

Here we review relevant but limited published articles found in the literature addressing the diabetes care gap in the LatinX community utilizing cost effective, novel and culturally sensitive strategies and reinforce the importance of continued work and publications on this very important field.

Racial disparities in triple negative breast cancer: toward a causal architecture approach

BACKGROUND

Triple negative breast cancer (TNBC) is an aggressive subtype of invasive breast cancer that disproportionately affects Black women and contributes to racial disparities in breast cancer mortality. Prior research has suggested that neighborhood effects may contribute to this disparity beyond individual risk factors.

METHODS

The sample included a cohort of 3316 breast cancer cases diagnosed between 2012 and 2020 in New Castle County, Delaware, a geographic region of the US with elevated rates of TNBC. Multilevel methods and geospatial mapping evaluated whether the race, income, and race/income versions of the neighborhood Index of Concentration at the Extremes (ICE) metric could efficiently identify census tracts (CT) with higher odds of TNBC relative to other forms of invasive breast cancer. Odds ratios (OR) and 95% confidence intervals (CI) were reported; p-values < 0.05 were significant. Additional analyses examined area-level differences in exposure to metabolic risk factors, including unhealthy alcohol use and obesity.

RESULTS

The ICE-Race, -Income-, and Race/Income metrics were each associated with greater census tract odds of TNBC on a bivariate basis. However, only ICE-Race was significantly associated with higher odds of TNBC after adjustment for patient-level age and race (most disadvantaged CT: OR = 2.09; 95% CI 1.40-3.13), providing support for neighborhood effects. Higher counts of alcohol and fast-food retailers, and correspondingly higher rates of unhealthy alcohol use and obesity, were observed in CTs that were classified into the most disadvantaged ICE-Race quintile and had the highest odds of TNBC.

CONCLUSION

The use of ICE can facilitate the monitoring of cancer inequities and advance the study of racial disparities in breast cancer.

Diabetes Control During Massachusetts Insurance Reform

Racial/ethnic disparities in glycemic control-a key diabetes outcome measure-continue to widen, even though the overall prevalence of glycemic control in the US has improved. Health insurance coverage may be associated with improved glycemic control, but few studies examine effects during a period of policy change. We assessed changes in glycemic control by racial/ethnic groups following the Massachusetts Health Insurance Reform for patients at two urban safety-net academic health systems between January 2005 and December 2013. We analyzed outcomes for three measures of poor glycemic control: 1) lack of a hemoglobin A1C (A1C) measure during a 6-month period; 2) A1C >8%; 3) A1C >9% before, during, and after implementation of insurance reform. We did not find increased rates of A1C monitoring or control following insurance reform overall or for specific racial/ethnic groups. We found evidence of worsened, not improved, glycemic control in some racial/ethnic groups in the post-reform period. The expansion of affordable insurance coverage was not associated with improved glycemic control in vulnerable populations.