Type 2 Diabetes Mellitus Related Distress in Thailand.
Kongprai TunsuchartPeerasak LerttrakarnnonKriengkrai SrithanaviboonchaiSurinporn LikhitsathianSombat SkulphanPublished in: International journal of environmental research and public health (2020)
This study aimed to investigate prevalence and factors potentially associated with diabetes-related distress (DRD) among type 2 diabetes mellitus (T2DM) patients in a primary health care center in Thailand. This cross-sectional study was conducted with a total of 370 patients with T2DM. Data were collected at primary health care centers in Hang Dong District, Chiang Mai Province, Thailand. DRD was assessed using the Diabetes Distress Scale (DDS-17). The association between sociodemographic characteristics and other factors with DRD was analyzed using the Fisher t-test, Chi-square test, and Pearson's correlation coefficient test. The association between Hemoglobin A1c (HbA1c) and DRD was analyzed using multiple linear regression analysis. The participants had a mean age of 60.95 ± 7.96, and most were female (68.1%). Of the participants with DRD, 8.9% had moderate to high levels of distress. Education level and family support were significantly associated with the overall level of DRD. Additionally, HbA1c and co-morbidity were also significantly associated with DRD, as were emotional burden and regimen distress. Multiple linear regression analysis found that increased HbA1c was positively associated with increased DRD after adjusting for age, sex, education, duration of T2DM, co-morbidity, diabetic complications, and family support. Screening with DRD may be beneficial in T2DM patients.
Keyphrases
- glycemic control
- end stage renal disease
- type diabetes
- newly diagnosed
- ejection fraction
- healthcare
- chronic kidney disease
- cardiovascular disease
- prognostic factors
- peritoneal dialysis
- south africa
- machine learning
- computed tomography
- adipose tissue
- electronic health record
- big data
- drug induced
- patient reported outcomes
- magnetic resonance
- diffusion weighted imaging
- artificial intelligence