Abstract
AbstractPurposeDiabetes Mellitus (DM) patients were exposed to subacute risk as a result of the unanticipated lockdown. Furthermore, most DM patients were unable to engage in physical activity during that period. This impediment to proper healthcare management had increased Blood Glucose Levels (BGL). Therefore, initiatives must be adopted to prevent the same result in the second lockdown in 2021 for the well-being of patients.MethodThis statistical analysis aimed to assess the rise in BGL of diabetic patients before and during the lockdown. A survey was conducted among the DM patients in the Bangladeshi cohort, who came from various socioeconomic backgrounds and included both men and women. The statistical modeling, performed with the help of stat-ease software, was conducted by applying the Analysis of Variance (ANOVA) method to Response Surface Methodology (RSM).ResultOut of the 3 models applied (quadratic, main effect and sequential sum of squares for 2 factor interaction (2FI)) in 2 different response vectors the 2FI model was the best suited (p value - 0.0441 and 0.0015). The results yielded by the 2FI model were used to evaluate RSM.ConclusionThe analysis had shown a significant rise in the BGL among the DM patients during the lockdown, and the patients with the higher BMI tend to have a more significant increment in the BGL. Male patients experienced a greater rise in BGL. Furthermore, elderly patients with high Random Blood Glucose (RBG) levels before lockdown were more likely to have high RBG levels during the lockdown.
Publisher
Cold Spring Harbor Laboratory