AI Article Synopsis

  • In southeastern Ohio, the prevalence of diabetes is significantly higher than the national average, leading to increased levels of diabetes distress and major depressive disorder among patients.
  • The study aimed to assess diabetes distress, clinically significant depressive symptoms, and their effects on A1c levels, self-care behaviors, and diabetes quality of life among local patients with diabetes.
  • Researchers used various validated questionnaires to gather data from 325 participants, analyzing the relationships between depressive symptoms, diabetes distress, and overall diabetes management and quality of life.

Article Abstract

Context: In rural southeastern Ohio, the prevalence of diabetes is 19.9%, nearly double the national average of 10.5%. Despite the high rate of diabetes, its impact on the region is understudied; one such understudied topic is psychosocial difficulties. People with diabetes experience disproportionately higher rates of major depressive disorder (MDD), clinically significant depressive symptoms, and diabetes distress. Diabetes distress refers to the negative emotional experience of living with diabetes. It reflects an individual's worries, concerns, and fears about living a chronic and progressive disease.

Objectives: To assess the prevalence of diabetes distress as well as comorbid, clinically significant depressive symptoms and diabetes distress among patients in southeastern Ohio; and to assess impact of depressive symptoms and diabetes distress on A levels, diabetes self care behaviors, and diabetes quality of life (DQOL).

Methods: In this cross sectional survey study, individuals aged 18 years and older, diagnosed with type 1 (T1D) or type 2 (T2D) diabetes, who were able to read and speak English, and living in southeastern Ohio were invited to participate. Participants completed the Diabetes Distress Scale for T2D or T1D, the Patient Health Questionnaire-9, the Self Care Inventory-Revised, and the DQOL Scale as part of the study survey. Participants completed the survey via an online questionnaire service or mailed packets. Chi square tests determined the comorbidity of clinically significant depressive symptoms and high diabetes distress levels by type of diabetes. Multiple regression models examined the relationships among clinically significant depressive symptoms, diabetes distress scores, A levels, self care behaviors, and DQOL scores. Statistical significance was defined as a p<0.05.

Results: A total of 325 adults participated (mean ± standard deviation [SD] age, 41.6 ± 19.2 years; 131 (40.7%) with T1D; 194 (59.7%) with T2D; mean ± SD A, 7.5 ± 1.6%; mean ± SD duration, 12.4 ± 9.6 years). Of the 325 participants, 70 (21.5%) indicated clinically significant depressive symptoms, with 29 (22.3%) T1D participants and 41 (21.0%) T2D participants reporting clinically significant depressive symptoms. A total of 92 (28.3%) participants reported high diabetes distress (39 (30.5%) T1D participants and 53 (27.5%) T2D participants). Forty-eight participants (15.0%) screened positive for both clinically significant depressive symptoms and high diabetes distress. Regression models showed that higher diabetes distress scores were associated with fewer self care behaviors (T1D, =-0.268, p=0.030; T2D, =-0.312, p<0.001) and lower DQOL (T1D, =0.726, p<0.001; T2D, =0.501, p<0.001). Further, more depressive symptoms were associated with lower DQOL in participants with T2D (=0.363, p<0.001). Higher diabetes distress scores were not associated with higher A levels in participants with T1D or T2D; however, increased depressive symptoms were associated with higher A levels in participants with T2D (=0.390, p<0.001).

Conclusions: Findings showed that adults in southeastern Ohio experienced high levels of diabetes distress and co-occurring clinically significant depressive symptoms that were within range of data from previous studies. These findings highlight the importance of routine screening for both clinically significant depressive symptoms and diabetes distress. Future longitudinal research is needed to confirm these findings and examine the evolution of these relationships over time.

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Source
http://dx.doi.org/10.1515/jom-2021-0091DOI Listing

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