Objective: The American Diabetes Association has called for more research on distress in adults with type 2 diabetes (T2D). There is a dearth of data on diabetes distress in underserved immigrants. This study aimed to examine prevalence and correlates of diabetes distress among Chinese immigrants with T2D.
Methods: A cross sectional study was conducted among Chinese immigrants with T2D in New York City in 2018. Sociodemographic survey and diabetes distress scale (DDS) were administered face-to-face by bilingual study staff. DDS is a validated 17-item survey to assess diabetes distress and includes 4 subscales: physician, regimen, interpersonal, and emotional-related distress. Responses for each item ranged from 1 (not a problem) to 6 (a very significant problem) with a score greater than 2 indicating a clinically significant and at least a moderate level of distress. Descriptive statistics and multivariable logistic regression modeling were used.
Results: The sample (N=94) was mostly female (60.6%), married (75.5%), retired (57.4%), limited English proficient (86.2%) with a mean age of 70.6 (SD=11.6). The majority of participants had a high school education or less (61.7%) and a household income of ≤$25,000/yr (69.1%). Overall, 23.4% of the participants reported at least a moderate level of distress. The most common sources of distress were emotional burden (33.0%), followed by regimen (30.9%), interpersonal (29.8%), and physician (18.1%). Compared to those who were currently employed, those who were retired had a lower odds of diabetes distress (OR=0.12, 95% CI 0.02-0.83). Age, gender, years living in the US, education, and income were not significant correlates.
Conclusions: We found high rates of diabetes distress and emotional burden among Chinese immigrants with T2D. Given the known link between diabetes distress and poor health outcomes, it may be important to consider screening for diabetes distress and incorporating psychological counseling in diabetes care.
L. Hu: None. X. Xu: None. S. Yang: None. L. Lei: None. H. Bao: None. B. Fan: None. M. Sevick: None.
National Institutes of Health (U54MD000538-15, K99MD012811, R00MD012811, P30DK111022)