Age Disparities Among Patients With Type 2 Diabetes and Associated Rates of Hospital Use and Diabetic Complications

Determinants of disparities of diabetes-related hospitalization rates in Florida: a retrospective ecological study using a multiscale geographically weighted regression approach

BACKGROUND

Early diagnosis, control of blood glucose levels and cardiovascular risk factors, and regular screening are essential to prevent or delay complications of diabetes. However, most adults with diabetes do not meet recommended targets, and some populations have disproportionately high rates of potentially preventable diabetes-related hospitalizations. Understanding the factors that contribute to geographic disparities can guide resource allocation and help ensure that future interventions are designed to meet the specific needs of these communities. Therefore, the objectives of this study were (1) to identify determinants of diabetes-related hospitalization rates at the ZIP code tabulation area (ZCTA) level in Florida, and (2) assess if the strengths of these relationships vary by geographic location and at different spatial scales.

METHODS

Diabetes-related hospitalization (DRH) rates were computed at the ZCTA level using data from 2016 to 2019. A global ordinary least squares regression model was fit to identify socioeconomic, demographic, healthcare-related, and built environment characteristics associated with log-transformed DRH rates. A multiscale geographically weighted regression (MGWR) model was then fit to investigate and describe spatial heterogeneity of regression coefficients.

RESULTS

Populations of ZCTAs with high rates of diabetes-related hospitalizations tended to have higher proportions of older adults (p < 0.0001) and non-Hispanic Black residents (p = 0.003). In addition, DRH rates were associated with higher levels of unemployment (p = 0.001), uninsurance (p < 0.0001), and lack of access to a vehicle (p = 0.002). Population density and median household income had significant (p < 0.0001) negative associations with DRH rates. Non-stationary variables exhibited spatial heterogeneity at local (percent non-Hispanic Black, educational attainment), regional (age composition, unemployment, health insurance coverage), and statewide scales (population density, income, vehicle access).

CONCLUSIONS

The findings of this study underscore the importance of socioeconomic resources and rurality in shaping population health. Understanding the spatial context of the observed relationships provides valuable insights to guide needs-based, locally-focused health planning to reduce disparities in the burden of potentially avoidable hospitalizations.

Investigation of predictors of severity of diabetes complications among hospitalized patients with diabetes in Florida, 2016-2019

BACKGROUND

Severe diabetes complications impact the quality of life of patients and may lead to premature deaths. However, these complications are preventable through proper glycemic control and management of risk factors. Understanding the risk factors of complications is important in guiding efforts to manage diabetes and reduce risks of its complications. Therefore, the objective of this study was to identify risk factors of severe diabetes complications among adult hospitalized patients with diabetes in Florida.

METHODS

Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Adapted Diabetes Complications Severity Index (aDCSI) scores were computed for 1,061,140 unique adult patients with a diagnosis of diabetes. Severe complications were defined as those with an aDCSI ≥ 4. Population average models, estimated using generalized estimating equations, were used to identify individual- and area-level predictors of severe diabetes complications.

RESULTS

Non-Hispanic Black patients had the highest odds of severe diabetes complications compared to non-Hispanic White patients among both males (Odds Ratio [OR] = 1.20, 95% Confidence Interval [CI]: 1.17, 1.23) and females (OR = 1.27, 95% CI: 1.23, 1.31). Comorbidities associated with higher odds of severe complications included hypertension (OR = 2.30, 95% CI: 2.23, 2.37), hyperlipidemia (OR = 1.29, 95% CI: 1.27, 1.31), obesity (OR = 1.24, 95% CI: 1.21, 1.26) and depression (OR = 1.09, 95% CI: 1.07, 1.11), while the odds were lower for patients with a diagnosis of arthritis (OR = 0.81, 95% CI: 0.79, 0.82). Type of health insurance coverage was associated with the severity of diabetes complications, with significantly higher odds of severe complications among Medicare (OR = 1.85, 95% CI: 1.80, 1.90) and Medicaid (OR = 1.83, 95% CI: 1.77, 1.90) patients compared to those with private insurance. Residing within the least socioeconomically deprived ZIP code tabulation areas (ZCTAs) in the state had a protective effect compared to residing outside of these areas.

CONCLUSIONS

Racial, ethnic, and socioeconomic disparities in the severity of diabetes complications exist among hospitalized patients in Florida. The observed disparities likely reflect challenges to maintaining glycemic control and managing cardiovascular risk factors, particularly for patients with multiple chronic conditions. Interventions to improve diabetes management should focus on populations with disproportionately high burdens of severe complications to improve quality of life and decrease premature mortality among adult patients with diabetes in Florida.

Perceptions of the Healthcare System Among Black Men with Previously Undiagnosed Diabetes and Prediabetes

OBJECTIVE

Given the significant disparities in diabetes burden and access to care, this study uses qualitative interviews of Black men having HbA1c levels consistent with previously undiagnosed diabetes or prediabetes to understand their perceptions of the healthcare system.

RESEARCH DESIGN AND METHODS

We recruited Black men from Black-owned barbershops in Brooklyn, NY, who were screened using point-of-care HbA1c tests. Among those with HbA1c levels within prediabetes or diabetes thresholds, qualitative interviews were conducted to uncover prevalent themes related to their overall health status, health behaviors, utilization of healthcare services, and experiences with the healthcare system. We used a theoretical framework from the William and Mohammed medical mistrust model to guide our qualitative analysis.

RESULTS

Fifty-two Black men without a prior history of diabetes and an HbA1c reading at or above 5.7% were interviewed. Many participants stated that their health was in good condition. Some participants expressed being surprised by their abnormal HbA1c reading because it was not previously mentioned by their healthcare providers. Furthermore, many of our participants shared recent examples of negative interactions with physicians when describing their experiences with the healthcare system. Finally, several participants cited a preference for incorporating non-pharmaceutical options in their diabetes management plans.

CONCLUSION

To help alleviate the disparity in diabetes burden among Black men, healthcare providers should take a more active role in recognizing and addressing their own implicit biases, engage in understanding the specific healthcare needs and expectations of each patient, and consider emphasizing non-medication approaches to improve glycemic control.

Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study

OBJECTIVES

This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes.

DESIGN, SETTING AND PARTICIPANTS

We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes.

PRIMARY OUTCOME AND METHODS

We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas.

RESULTS

We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

A Multi-Method Study of Patient Reach and Attendance in a Pragmatic Trial of Diabetes Shared Medical Appointments

Shared medical appointments (SMAs) are an evidence-based approach to diabetes care in primary care settings, yet practices can struggle to ensure participation, especially among racial and ethnic minority and low-income patients. We conducted a multimethod evaluation of reach and attendance in the Invested in Diabetes study of the comparative effectiveness of two SMA delivery models (standardized and patient-driven) in two practice settings (federally qualified health centers [FQHCs] and clinics serving more commercially insured patients). Through this study, 22 practices reached 6.2% of patients with diabetes through SMAs over 3 years, with good attendance for both practice types and both SMA delivery models. FQHCs were especially successful at enrolling underserved populations and improved attendance with virtual SMAs.

Expanding Diabetes Screening to Identify Undiagnosed Cases Among Emergency Department Patients

Introduction: Diabetes screening traditionally occurs in primary care settings, but many who are at high risk face barriers to accessing care and therefore delays in diagnosis and treatment. These same high-risk patients do frequently visit emergency departments (ED) and, therefore, might benefit from screening at that time. Our objective in this study was to analyze one year of results from a multisite, ED-based diabetes screening program. Methods: We assessed the demographics of patients screened, identified differences in rates of newly diagnosed diabetes by clinical site, and the geographic distribution of high and low hemoglobin A1c (HbA1c) results. Results: We performed diabetes screening (HbA1c) among 4,211 ED patients 40-70 years old, with a body mass index ≥25, and no prior history of diabetes. Of these patients screened for diabetes, 9% had a HbA1c result consistent with undiagnosed diabetes, and nearly half of these patients had a HbA1c ≥9.0%. Rates of newly diagnosed diabetes were notably higher at EDs located in neighborhoods of lower socioeconomic status. Conclusion: Emergency department-based diabetes screening may be a practical and scalable solution to screen high-risk patients and reduce health disparities experienced in specific neighborhoods and demographic groups.

Food Insecurity Is Associated With Dysfunctional Eating Behaviors Among Adults in Puerto Rico

OBJECTIVE

To examine the association between food insecurity and dysfunctional eating behaviors among adults in Puerto Rico.

METHODS

Data from 865 participants were obtained from baseline interviews from the Puerto Rico Observational Study of Psychosocial, Environmental, and Chronic Disease Trends (PROSPECT) cohort. The association between food insecurity and emotional eating (EE) and uncontrolled eating (UE) (categorized as no/moderate/high) was examined using multinomial logistic models. Potential mediation by perceived stress was explored.

RESULTS

The prevalence of food insecurity was 20.3%. Compared with adults with food security, adults with food insecurity had higher odds of both moderate EE (odds ratio [OR], 1.91; 95% confidence interval [CI], 1.18-3.09) and high EE (OR, 2.85; 95% CI, 1.75-4.64), and both moderate UE (OR, 1.78; 95% CI, 0.91-3.50) and high UE (OR, 3.28; 95% CI, 1.70-6.33). Perceived stress slightly attenuated these associations.

CONCLUSIONS AND IMPLICATIONS

Food insecurity was associated with a higher likelihood of engaging in dysfunctional eating behaviors. Interventions alleviating food insecurity or stress might help adults sustain healthy eating behaviors.

COVID-19 and diabetes in 2020: a systematic review

Attempts were made to review the literature on diabetic patients who experience complications when they contract COVID-19, and to determine whether ethnicity and other risk factors play an important role in the development of symptoms and their severity, as well as responding to medications. A literature search was performed using five keywords, namely COVID-19, diabetes, ethnicity, medications, and risk factors between January 2019 and December 2020 using electronic databases such as PubMed, Science Direct, Google Scholar, Springer Link, and Scopus. Forty studies were included. The review indicated that diabetes was a significant risk factor for poorer outcomes and increased mortality associated with COVID-19. There were several risk factors for diabetic patients that increased their likelihood of poorer outcomes associated with COVID-19. These included black and Asian ethnicity, male sex with high BMI. In conclusion, patients with diabetes of black or Asian origin with high BMI, male sex, and older age had an increased risk of poorer outcomes associated with COVID-19. This highlights the importance of considering the history of the patient in prioritising care and treatment.

Trends and Demographic Disparities in Diabetes Hospital Admissions: Analyses of Serial Cross-Sectional National and State Data, 2008-2017

OBJECTIVE

To analyze national and state-specific trends in diabetes-related hospital admissions and determine whether disparities in rates of admission exist between demographic groups and geographically dispersed states.

RESEARCH DESIGN AND METHODS

We conducted serial cross-sectional analyses of the National Inpatient Sample (2008, 2011, 2014, and 2016) and State Inpatient Databases for Arizona, Florida, Kentucky, Iowa, Maryland, Nebraska, New Jersey, New York, North Carolina, Utah, and Vermont for 2008, 2011, 2014, and 2016/2017 among adult patients with type 1 and type 2 diabetes-related ICD codes (ICD-9 [250.XX] or ICD-10 [E10.XXX, E11.XXX, and E13.XXX]. We measured hospitalization rates for people with diabetes (all-cause hospitalizations) and for admissions with a primary diagnosis of diabetes or diabetes-related complications (diabetes-specific hospitalizations) per 10,000 people per year.

RESULTS

Nationally, all-cause and diabetes-specific hospitalizations declined by 3.1% (95% CI -5.5, -0.7) and 19.1% (95% CI -21.6, -16.6), respectively, over 2008 to 2016. The analysis of individual states showed that diabetes-specific admissions in individuals ≥65 years old declined during this time (16.3-48.8% decrease) but increased among patients 18-29 years old (10.5-81.5% increase) and that rural diabetes-specific admissions decreased in just over half of the included states (15.2-69.2% decrease). There were no differences in changes in admission rates among different racial/ethnic groups.

CONCLUSIONS

Overall, rates of diabetes-related hospitalizations decreased over 2008 to 2016/2017, but there were large state-level differences across subgroups of patients. The rise in diabetes hospitalizations among young adults is a cause for concern. These state- and subpopulation-level differences highlight the need for state-level policies and interventions to address disparities in diabetes health care use.

Heritability Estimation and Environmental Risk Assessment for Type 2 Diabetes Mellitus in a Rural Region in Henan, China: Family-Based and Case-Control Studies

Objective: The prevalence of type 2 diabetes mellitus (T2DM) varies greatly in different regions and populations. This study aims to assess the heritability and environmental risk factors of T2DM among rural Chinese adults.

Methods: Thousand five hundred thirty three participants from 499 extended families, which included 24 nuclear families, were recruited in the family-based study to assess the heritable risk of T2DM. Heritability of T2DM was estimated by the Falconer method. Using conditional logistic regression model, couple case-control study involving 127 couples were applied to assess the environmental risk factors of T2DM.

Results: Compared with the Henan Rural Cohort, T2DM was significantly clustered in the nuclear families (OR: 8.389, 95% CI: 5.537–12.711, P < 0.001) and heritability was 0.74. No association between the heredity of T2DM and sex was observed between the extended families and the Henan Rural Cohort. Besides, results from the couple case-control study showed that physical activity (OR: 0.482, 95% CI: 0.261–0.893, P = 0.020) and fat intake (OR: 3.036, 95% CI: 1.070–8.610, P = 0.037) was associated with T2DM, and the proportion of offspring engaged in medium and high physical activity was higher than that of mothers in mother-offspring pairs.

Conclusion: People with a family history of T2DM may have a higher risk of developing T2DM, however, there was no difference in genetic risk between males and females. Adherence to active physical activity and low fat intake can reduce the risk of T2DM.

Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020

BACKGROUND

Availability of SARS-CoV-2 testing in the United States (U.S.) has fluctuated through the course of the COVID-19 pandemic, including in the U.S. state of Illinois. Despite substantial ramp-up in test volume, access to SARS-CoV-2 testing remains limited, heterogeneous, and insufficient to control spread.

METHODS

We compared SARS-CoV-2 testing rates across geographic regions, over time, and by demographic characteristics (i.e., age and racial/ethnic groups) in Illinois during March through December 2020. We compared age-matched case fatality ratios and infection fatality ratios through time to estimate the fraction of SARS-CoV-2 infections that have been detected through diagnostic testing.

RESULTS

By the end of 2020, initial geographic differences in testing rates had closed substantially. Case fatality ratios were higher in non-Hispanic Black and Hispanic/Latino populations in Illinois relative to non-Hispanic White populations, suggesting that tests were insufficient to accurately capture the true burden of COVID-19 disease in the minority populations during the initial epidemic wave. While testing disparities decreased during 2020, Hispanic/Latino populations consistently remained the least tested at 1.87 tests per 1000 population per day compared with 2.58 and 2.87 for non-Hispanic Black and non-Hispanic White populations, respectively, at the end of 2020. Despite a large expansion in testing since the beginning of the first wave of the epidemic, we estimated that over half (50-80%) of all SARS-CoV-2 infections were not detected by diagnostic testing and continued to evade surveillance.

CONCLUSIONS

Systematic methods for identifying relatively under-tested geographic regions and demographic groups may enable policymakers to regularly monitor and evaluate the shifting landscape of diagnostic testing, allowing officials to prioritize allocation of testing resources to reduce disparities in COVID-19 burden and eventually reduce SARS-CoV-2 transmission.

Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020

Background

Availability of SARS-CoV-2 testing in the United States (U.S.) has fluctuated through the course of the COVID-19 pandemic, including in the U.S. state of Illinois. Despite substantial ramp-up in test volume, access to SARS-CoV-2 testing remains limited, heterogeneous, and insufficient to control spread.

Methods

We compared SARS-CoV-2 testing rates across geographic regions, over time, and by demographic characteristics (i.e., age and racial/ethnic groups) in Illinois during March through December 2020. We compared age-matched case fatality ratios and infection fatality ratios through time to estimate the fraction of SARS-CoV-2 infections that have been detected through diagnostic testing.

Results

By the end of 2020, initial geographic differences in testing rates had closed substantially. Case fatality ratios were higher in non-Hispanic Black and Hispanic/Latino populations in Illinois relative to non-Hispanic White populations, suggesting that tests were insufficient to accurately capture the true burden of COVID-19 disease in the minority populations during the initial epidemic wave. While testing disparities decreased during 2020, Hispanic/Latino populations consistently remained the least tested at 1.87 tests per 1000 population per day compared with 2.58 and 2.87 for non-Hispanic Black and non-Hispanic White populations, respectively, at the end of 2020. Despite a large expansion in testing since the beginning of the first wave of the epidemic, we estimated that over half (50-80%) of all SARS-CoV-2 infections were not detected by diagnostic testing and continued to evade surveillance.

Conclusions

Systematic methods for identifying relatively under-tested geographic regions and demographic groups may enable policymakers to regularly monitor and evaluate the shifting landscape of diagnostic testing, allowing officials to prioritize allocation of testing resources to reduce disparities in COVID-19 burden and eventually reduce SARS-CoV-2 transmission.

Does the Encounter Type Matter When Defining Diabetes Complications in Electronic Health Records?

BACKGROUND

Electronic health records (EHRs) and claims records are widely used in defining type 2 diabetes mellitus (T2DM) complications across different types of health care encounters.

OBJECTIVE

This study investigates whether using different EHR encounter types to define diabetes complications may lead to different results when examining associations between diabetes complications and their risk factors in patients with T2DM.

RESEARCH DESIGN

The study cohort of 64,855 adult patients with T2DM was created from EHR data from the Research Action for Health Network (REACHnet), using the Surveillance Prevention, and Management of Diabetes Mellitus (SUPREME-DM) definitions. Incidence of coronary heart disease (CHD) and stroke events were identified using International Classification of Diseases (ICD)-9/10 codes and grouped by encounter types: (1) inpatient (IP) or emergency department (ED) type, or (2) any health care encounter type. Cox proportional hazards regression was used to estimate associations between diabetes complications (ie, CHD and stroke) and risk factors (ie, low-density lipoprotein cholesterol and hemoglobin A1c).

RESULTS

The incidence rates of CHD and stroke in all health care settings were more than twice the incidence rates of CHD and stroke in IP/ED settings. The age-adjusted and multivariable-adjusted hazard ratios for incident CHD and stroke across different levels of low-density lipoprotein cholesterol and hemoglobin A1c were similar between IP/ED and all settings.

CONCLUSION

While there are large variations in incidence rates of CHD and stroke as absolute risks, the associations between both CHD and stroke and their respective risk factors measured by hazard ratios as relative risks are similar, regardless of alternative definitions.

Community-Based Hemoglobin A1C Testing in Barbershops to Identify Black Men With Undiagnosed Diabetes

This cross-sectional study evaluates the use of hemoglobin A_1c testing at barbershops owned by black individuals for timely diagnosis of diabetes among black men and suggests appropriate methods for care.

Knowledge Visualizations to Inform Decision Making for Improving Food Accessibility and Reducing Obesity Rates in the United States

The aim of this article is to promote the use of knowledge visualization frameworks in the creation and transfer of complex public health knowledge. The accessibility to healthy food items is an example of complex public health knowledge. The United States Department of Agriculture Food Access Research Atlas (FARA) dataset contains 147 variables for 72,864 census tracts and includes 16 food accessibility variables with binary values (0 or 1). Using four-digit and 16-digit binary patterns, we have developed data analytical procedures to group the 72,684 U.S. census tracts into eight and forty groups respectively. This value-added FARA dataset facilitated the design and production of interactive knowledge visualizations that have a collective purpose of knowledge transfer and specific functions including new insights on food accessibility and obesity rates in the United States. The knowledge visualizations of the binary patterns could serve as an integrated explanation and prediction system to help answer why and what-if questions on food accessibility, nutritional inequality and nutrition therapy for diabetic care at varying geographic units. In conclusion, the approach of knowledge visualizations could inform coordinated multi-level decision making for improving food accessibility and reducing chronic diseases in locations defined by patterns of food access measures.