This hospital-based case-control study was conducted in the Out-Patient Department (OPD) and wards of Obstetrics and Gynaecology Department, Pariyaram Medical College Hospital, Pariyaram, Kannur during the period July 2015 to February 2016. Ethical clearance was obtained from the Institutional Ethical Clearance Committee for the conduct of the study. All pregnant women who attended the OPD and wards of Obstetrics and Gynaecology during the study period, who gave written informed consent were included and those with high risk pregnancies, previous history of diabetes mellitus were excluded from the study. Consecutive sampling was done with a sample size of 128 (64 cases and 64 controls), enough to detect an odds ratio of 3.7, assuming the prevalence of obesity among controls to be 14.3% with 80% power and 5% level of significance.

After obtaining the informed consent, each study subject was interviewed. Biodata, obstetric history and anthropometric measurements {height in meter (m), pre-pregnancy weight in kilograms (kg) and BMI (weight/ height²) in kg/m²} were noted from the study subjects. Pre-pregnancy BMI (BMI recorded during first antenatal visit) categorised according to WHO [7]. Values of OGTT which was done during their antenatal visits (first and second trimester) were collected and noted. OGTT estimation was done in central laboratory of Pariyaram Medical College Hospital, which was analysed by enzymatic UV test (Hexokinase method) for the quantitative determination of glucose in human serum and plasma on OLYMPUS analysers. A woman was considered to have GDM if the 2-hour plasma glucose value >140 mg/dL with the 75 gram oral glucose (DIPSI guidelines, a modified version of the WHO criterion) and rest of the women who had OGTT values within normal limits were classified as normal glucose tolerant (controls) [8]. Data obtained were tabulated and statistically analysed.

Descriptive statistics like mean, standard deviation, frequency and Inferential statistics like independent t-test and chi-square test were used. All statistical analysis was performed using SPSS version 13.0 software. A p-value of <0.05 was considered as significant.

The mean age in women with GDM was found to be 29.38±5.01 years and that in controls was found to be 26.25±4.21 years.

In the comparison of BMI, the mean±SD value in women with GDM was found to be 26.38±2.74 kg/m² and that in controls was 22.26±1.54 kg/m², which was found to be statistically significant [Table/Fig-1].

[Table/Fig-1]:

Comparison of BMI (kg/m²) among cases and controls.

Chi-square value (χ²) = 50.009, df=1, p≤0.001

Forty one (93.2%) women with GDM had BMI ≥25 kg/m² (overweight and obese) compared to three (6.8%) in controls, which was found to be statistically significant (χ² value=50.01, df=1, p≤0.001). Majority of the controls (n=60) had normal BMI compared to cases (n=23) [Table/Fig-1].

The results showed an increased risk of GDM associated with increasing BMI. Identifying such modifiable risk factors associated with GDM helps in strengthening maternal health programs by focusing on the prevention and control of obesity during the pre-pregnancy period and introducing corrective therapeutic interventions such as exercise and dietary modification.

The mean±SD value of BMI in women with GDM was found to be higher (26.38±2.74 kg/m²) compared to controls (22.26±1.54 kg/m²), which was statistically significant. Forty one (93.2%) women with GDM had BMI ≥25 kg/m² (overweight and obese) compared to three (6.8%) in controls. In a study conducted by Bhat M et al., BMI ≥25 kg/m² (overweight and obese) was significantly higher in cases (37.9%) compared to controls (14.3%) [9]. Seshiah V et al., observed a linear increase in the prevalence of GDM with increasing BMI in a study conducted in India [8]. A prospective longitudinal study on glucose metabolism in obese women with GDM by Catalano PM concluded that obese Gestational Diabetics had greater insulin resistance compared to normal weight women with GDM [4].

Obesity was recognised as a high risk factor necessitating early testing of glucose intolerance by the Organising Committee of the Fourth International Conference on GDM [10]. Naylor CD et al., developed a selective screening approach instead of the previously recommended universal screening for diagnosis of GDM. BMI was one of the factors on which the scoring system for categorisation of women into low, intermediate and high risk groups was based. This approach resulted in a 34.6% reduction in the number of screening tests performed without any decrease in the detection rate of GDM [11]. The American Diabetes Association (ADA) now recommends selective screening for GDM and obesity is a high risk factor [12].

Obesity is an important risk factor in the development of GDM. Obesity itself causes some degree of insulin resistance. Increased BMI associated with GDM leads to a state of insulin resistance additive to insulin resistance of GDM. Of all factors associated with GDM, obesity is a modifiable factor to a certain extent. Several mechanisms have been suggested for the increased insulin resistance in obese women with GDM. Obesity mediates a systemic inflammatory response in our body which includes insulin resistance and glucose dysregulation [9]. Plasma Free Fatty Acids (FFA) resulting from dietary fat supply and increased lipolysis in fat tissue may directly induce insulin resistance or could be channelled preferentially into triglycerides. Increased FFA uptake or lipolysis of intramyocellular lipid can inhibit insulin action via decreased insulin receptor substrate (IRS)-1 phoshorylation. Overweight and obesity has been increasing in incidence among the reproductive age group women over the past few decades in the developing countries. Catalano PM observed down regulation of IRS-1 and PPAR-γ in obese gestational diabetics more than that in non-obese GDM [4]. According to Willer KA et al., increased intramyocellular lipid concentration was found to occur in women with previous GDM and is considered as a parameter of insulin resistance that predicts type 2 diabetes [13]. Insulin resistance is much more affected by the overweight and obese women compared with lean or average weight women.

Being a hospital-based case control study, it could have been biased to a certain extent. Further studies including larger samples will substantiate our study and the results can be generalised.

The GDM was found to be significantly associated with pre-pregnancy BMI. Appropriate interventions and risk factor modifications are recommended to prevent GDM and its complications. This study also suggests that we should pay more attention to the pre-pregnancy BMI to prevent long-term health implication of GDM on maternal and fetal health.