Back

Diabetes-related Distress and the Association to Hypertension and Cardiovascular Disease Among Individuals Living with Type 2 Diabetes in Rural areas in Vietnam

Sahl, A. S.; Khong Thi, D.; Nguen Duc, T.; Huyen, D.; Sondergaard, J.; Nielsen, J.; Bygbjerg, I. C.; Gammeltoft, T.; Meyrowitsch, D. W.

2023-02-08 public and global health
10.1101/2023.02.06.23285554 medRxiv
Show abstract

ObjectiveThe prevalence of diabetes has been rising in rural areas of Vietnam over the last years to the extend where it has become a public health burden. Individuals with diabetes-related distress (DRD) is in greater risk of adverse health outcomes e.g. lower blood sugar control and polypharmacy. The objective of this study is to assess the association between hypertension and cardiovascular disease (CVD) and the occurrence of DRD among individuals with type 2 diabetes (T2D) in rural areas of Vietnam. MethodThis is a cross-sectional study of 806 individuals who had been receiving treatment for T2D at a district hospital in the northern Vietnamese province Thai Binh. Based on self-reported data DRD was assessed through Problem Areas in Diabetes scale 5 (PAID5) and defined as a score of 8 or above. The occurrence of the comorbid conditions hypertension and CVD were self-reported. ResultsAmong 806 individuals with T2D 37.7% of the men and 62.3% of the women presented with DRD. Out of the total group 35.6% reported hypertension, 7.3% reported CVD and 21.2% reported a combination of hypertension and CVD. The results of the multivariate analyses showed that the odds ratio of DRD was significantly higher (OR=1.67, CI95: 1.11-2.52) in the group who reported a combination of hypertension and CVD. ConclusionAmong individuals with T2D in rural areas of Vietnam there is an increased risk of DRD if a combination of hypertension and cardiovascular disease is also present. Hence, considering diabetes-related comorbidities can be useful in order to successfully identify individuals in risk of DRD.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.