Understanding the Profiles of Blood Glucose Monitoring Among Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in Shandong, China

Abstract

Background: Blood glucose monitoring is essential in diabetic care and management. Monitoring using glucometers in home and in laboratories by professionals in certain health institutes were the common methods of blood glucose monitoring in clinical practice. This study aimed to characterize the profiles of blood glucose monitoring in the view of the discrepancy in methods and frequency conducted by the patients with type 2 diabetes mellitus (T2DM) in China, and to explore factors influencing the profiles. Methods: A cross-sectional, community-based study was conducted in Shandong province, China, with a multi-stage stratified sampling. A total of 2166 T2DM patients completed the structured questionnaires about the real-world status of blood glucose monitoring and other questions composed of demographic and clinical characteristic as well as the diabetes-related cognitive scales. Latent profile analysis (LPA) was used to identify the underlying profiles of blood glucose monitoring based on self-reported frequency of blood glucose monitoring through different methods. Univariate and multivariate logistic regression were used to analyze the characteristics of the profiles and to explore the factors associated with it. Results: Among the 2166 participants, the mean frequency of blood glucose monitoring was 2.77 times (standard deviation: 7.67) per month. LPA indicated that five-class model was the best solution for classifying the latent groups of blood glucose monitoring: Class 1 “Low frequency in all”, Class 2 “High frequency in hospitals”, Class 3 “High frequency in primary health institutes”, Class 4 “High frequency in pharmacies”, and Class 5 “High frequency in self-monitoring”. The proportions of the patients in class 1, class 2, class 3, class 4, and class 5 were 88.1% (n=1909), 1.3% (n=28), 3.1% (n=67), 6.1% (n=133) and 1.3% (n=29), respectively. Multivariate logistic regression showed that participants who had higher income (OR: 1.58, 95% CI: 1.04∼ 2.41, p< 0.05), had diabetes complication(s) (OR=1.37, 95% CI: 1.03∼ 1.02, p=0.03) and had a good knowledge of blood glucose control (OR=1.59, 95% CI: 1.17∼ 2.16, p< 0.01) were more likely to have high frequency of blood glucose monitoring (in class 2, 3, 4, 5), and the rural patients were less likely to had high frequency of blood glucose monitoring (OR=0.47, 95% CI: 0.35∼ 0.63, p< 0.01). Conclusion: Low frequency dominates the characteristics of the profiles of blood glucose monitoring among T2DM patients in China, though distinct blood glucose monitoring groups can be identified by LPA. Educational and financial supports were recommended to increase the frequency of blood glucose monitoring in patients with T2DM, focusing on the patients with low socioeconomic status.