Study Supports Call for Geographically Tailored Diabetes Care Interventions

Adult patients with diabetes living in more deprived and rural areas of the United States are significantly less likely to receive high-quality care for their condition compared with patients residing in less deprived and urban areas, according to new findings of a cross-sectional study.

Results were published in JAMA Network Open and underscore the need for geographically targeted efforts to improve care quality and health outcomes for this population, researchers stressed.

Currently, 34 million individuals in the United States, or 13% of the population, are living with diabetes, and in 2017, a total of $237 billion was spent on direct medical costs associated with the disease, authors explained. However, as US obesity rates continue to climb, associated conditions like diabetes and cardiovascular complications are expected to follow suit in the coming years.

Historically, racial and ethnic minority groups, low-income individuals, and rural residents have experienced disproportionately larger diabetes-related complications, due in part to suboptimal control of hyperglycemia, hypertension, and other cardiovascular risk factors. Past research has also revealed that rural areas have a 17% higher prevalence of diabetes compared with urban areas.

Furthermore, “the complex interactions among multiple behavioral, social, and economic factors in a patient's ability to self-manage and access necessary care,” complicate diabetes management, authors noted.

Using the area deprivation index (ADI), investigators sought to elucidate the association between area-level deprivation and diabetes care quality. ADI is calculated based on 4 domains outside of the health care setting: income, housing, employment, and education.

Researchers also utilized national rurality data and the D5 composite metric of optimal diabetes care to compare patients. Optimal diabetes care based on the D5 metric is defined as “a hemoglobin A1c (A1C) level that is less than 8%; a blood pressure (BP) reading that is less than 140/90 mm Hg; statin use that is appropriate for the patient’s age, low-density lipoprotein cholesterol (LDL-C) level, and history of cardiovascular disease; aspirin use that is appropriate in the setting of ischemic vascular disease; and abstinence from tobacco use.”

Electronic health record (EHR) data were collected from a total of 31,934 patients aged 18 or older who resided in Minnesota, Iowa, and Wisconsin. All individuals had an established diagnosis of diabetes and received primary care at 75 Mayo Clinic and Mayo Clinic Health System primary care practices.

Altogether, patients had a mean (SD) age of 59 (11.7) years and more than 90% were White; just over 40% of patients achieved the D5 metric of optimal diabetes care.

Analyses revealed:

• 4090 patients (12.8%) resided in the least deprived quintile (quintile 1) of block groups and 1614 (5.1%) lived in the most deprived quintile (quintile 5).
• 9193 patients (28.8%) lived in rural areas and 2299 (7.2%) in highly rural areas.
• Odds of meeting the D5 metric were lower for individuals residing in quintile 5 vs quintile 1 block groups (odds ratio [OR], 0.72; 95% CI, 0.67-0.78).
• Patients residing in rural (OR, 0.84; 95% CI, 0.73-0.97) and highly rural (OR, 0.81; 95% CI, 0.72-0.91) zip codes were less likely to attain the D5 metric compared with those in urban areas.
• Patients who attained the D5 metric compared with those who did not (n = 18,796) often were older (aged 65-75 years: 6536 [49.9%] vs 6425 [34.2%]), women (6119 [46.6%] vs 8170 [43.5%]), and White individuals (12,190 [92.8%] vs 16,990 [90.4%]).

“Within the D5 metric, the most variability was observed for the glycemic control and no tobacco use components,” researchers said, as “the odds of meeting the no tobacco use metric decreased progressively as deprivation increased.”

Higher rates of diabetes have been documented in lower income neighborhoods, those with lower educational attainment, single-parent households, and crowded housing. Additional factors that impact these rates are greater comorbidity burdens, lower health literacy, and higher food insecurity coupled with lower financial resources.

“These spatial social determinants of health are associated with the risk of developing diabetes, barriers to optimal self-management, and greater risk of diabetes-related complications,” authors wrote.

By addressing some of the structural factors that impede optimal care, clinics, health systems, and others can help improve diabetes management in these populations. Meaningful actions could include screening for social determinants of health and supporting food banks with nutritional options.

Payers can also play an important role in this effort by reducing patient cost-sharing responsibilities for diabetes-related care, reimbursing social services and support programs, and lowering insurance premiums for patients who adhere to treatment recommendations and improve their health, researchers suggested.

The use of survey data when calculating ADI scores leads to a potential nonresponse bias, marking a limitation to the analysis. Findings may also not be generalizable to the wider US population because of lower racial and ethnic minority group representation. However, results are representative of the upper Midwest region of the United States and rural communities across the country, authors concluded.

Reference

Kurani SS, Lampman MA, Funni SA, at al. Association between area-level socioeconomic deprivation and diabetes care quality in US primary care practices. JAMA Netw Open. Published online December 29, 2021. doi:10.1001/jamanetworkopen.2021.38438