Social Factors That Could Influence the Success of Diabetes Management 

Many psychological, social and neighborhood factors can negatively impact diabetes management, but there’s one thing that can cause the most harm. 

Diabetes is one of the nation’s largest growing diseases and is in the top ten of the leading causes of death in the United States.  Many determinants contribute to poor diabetes control outside of pharmaceutical failure.  The study from Walker et al. evaluates some of the social constraints that could lead to poor management of diabetes in the elderly population.   

The World Health Organization has recognized that social determinants have contributed to complications of diabetes.  These social determinants that are inflicted on patients with diabetes are often categorized as socioeconomic circumstances, psychosocial factors, neighborhood environment, and political, economic, and cultural drivers.    

The longitudinal study, The Health and Retirement Study, was conducted from 2006 through 2014.  Participants of the study must have been aged ≥50 years, and participated in blood-based biomarker data collection in the first enhanced face-to-face interview.  It included a total of 2,662 participants following exclusion from those who didn’t have Hemoglobin A1c (HbA1c) values measured. For the duration of the study, 5,028 interviews were conducted along with HbA1c test results, which were done biennially. The primary outcome of this study was the glycemic control for those who reported being told that they had diabetes by their physician.  Measurements of the HbA1c values were also taken throughout the study from the participants, which were used in a longitudinal repeated-measures analysis. 

The biennial core interviews and RAND data sets were used to measure the social determinant factors of participants. Questions measuring financial hardships were as followed: difficulty paying bills, food insecurity, and medication cost nonadherence.  The scales measuring psychosocial factors were: religiosity, efficacy over health, social support, depression, and loneness.  Neighborhood factors included in determining social constraints were: neighborhood social cohesion, social participation, neighborhood physical disorder, and perceived everyday discrimination.  Answer choices were ranged on various scales or could have been answered with a yes or no depending on the question asked. The biennial core interviews and RAND data sets also gathered information about the participant’s demographics. This included the following details: age, race, marital status, education completion, household income, health insurance coverage, comorbidity count, emotional/psychiatric diagnosis, and BMI.   

For the analyses that were unadjusted, the data showed that there were significant relationships between higher HbA1c over time and difficulty paying bills (0.23[95%CI0.15,0.32]),medication cost nonadherence (0.28 [0.18, 0.39]), food insecurity (0.21 [0.04, 0.38]), depression (0.03 [0.01, 0.04]), negative social support (0.09 [0.001, 0.17]), and loneliness (0.11 [0.04, 0.18]). Also, the data showed that there were significant relationships between lower HbA1c over time and efficacy over health (20.02 [20.03, 20.001]) and social cohesion (20.04 [20.06, 20.01]). The first model incorporated financial hardship and social determinant variables, difficulty paying bills (0.19 [0.10, 0.28]) and medication cost nonadherence (0.27[0.15, 0.38]). The data showed that these factors were independently associated with increasing HbA1c over time. Before there was any adjustment incorporated for demographics, the data revealed that social cohesion was also independently associated with lower HbA1c over time (20.05 [20.10, 20.001]); in contrast, neither medication cost nonadherence nor social cohesion showed any significance when adjustments were made for age, sex, race/ethnicity, education, and income. When the adjustments were incorporated for demographics, comorbidity count, and health insurance, difficulty paying bills (0.13 [0.02, 0.24]) and higher religiosity scores (0.04[0.001,0.08]) the data revealed that these factors were independently associated with increasing HbA1c over time. 

This longitudinal study found that financial hardship factors such as difficulty paying bills were more contributory to increasing HbA1c levels, more so than psychosocial and neighborhood factors.  This study highlights that many of the financial barriers could be stemming from the diagnosis itself and the difficulty affording diabetic supplies, multiple medications, and purchasing healthy foods. The psychosocial and neighborhood factors have shown to have a relationship with glycemic control over time.  Religiosity overall did not prove to correlate with HbA1c levels, but the type of religiosity did explain some significance.  If one’s religious belief system implies that a diagnosis such as diabetes is a punishment from God, this belief could harm the glycemic control of those patients.  However, after the adjustment for multiple social determinant factors, difficulty paying the bills remains the most significant factor in increasing HbA1c over time, which suggests that financial hardship is explicitly an essential determinant of diabetes outcomes.  

Practice Pearls: 

• Patients who are facing financial hardships are probably the most likely to have poor health outcomes and especially glycemic control.   
• Factors such as age, sex, race/ethnicity, education, and income did not show significance to increasing HbA1c. 
• This focus is on participants age ≥50; the data could be different for a younger subset of participants.  

Walker, Rebekah J., et al. “The Longitudinal Influence of Social Determinants of Health on Glycemic Control in Elderly Adults With Diabetes.” Diabetes Care, American Diabetes Association, 6 Feb. 2020, care.diabetesjournals.org/content/early/2020/02/06/dc19-1586. 

Chardae Whitner, 2020 PharmD. Candidate, Lake Erie College of Osteopathic Medicine