Abstract:
Gestational Diabetes Mellitus (GDM) is a form of diabetes that can occur during
pregnancy and is a global public health issue. Women with GDM face elevated risks of
pregnancy and delivery complications, and they and their children are more likely to
develop type 2 diabetes later in life. This study aimed to identify and analyze the risk
factors linked to GDM. It involved constructing a binary logistic regression model to
assess the likelihood of developing GDM based on specific risk factors. This study was
conducted using 200 data was randomly selected from the medical record of pregnant
mothers who were admitted at the Ashraff Memorial Hospital Kalmunai between
January 2021 to December 2022. The statistical analysis was performed using statistical
software (Minitab 21) and P<0.05 was considered significance for all analyzes. Out of
the 200 pregnant mothers studied, it was found that 15.5% (with a 95% confidence
interval ranging from 10.8% to 21.3%) had GDM. The chi-square test revealed
significant associations between prevalence of GDM and factors such as the mother's
age, blood glucose levels, body mass index (BMI), and a family history of diabetes (all
with p-values less than 0.05). Additionally, a binary logistic regression model was
created to assess the relationship between dependent and independent variables. The
results indicated that factors like age, parity (number of children), platelet count (PLT),
and a family history of diabetes were significant predictors of GDM outcomes (all with
p-values less than 0.05). By utilizing this binary logistic regression model, healthcare
professionals can gain a better understanding of the risk factors associated with
gestational diabetes mellitus.
