Gestational diabetes mellitus and pregnancy outcomes at a tertiary care centre of eastern Uttar Pradesh

Singh, Shalini; Chaurasia, Amrita; Khare, Monisha; Srivastava, Yashi

doi:10.33545/gynae.2019.v3.i5e.369

Cited by 1 publication

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“…The diversity of prevalence of GDM was not only found in different states of the country, but this diversity can also be seen in different parts of Uttar Pradesh. The prevalence of GDM was seen in 26% in eastern Uttar Pradesh [12] , 13.45 in Kanpur Nagar [25] , 13.9% in Lucknow [1] , 9.7% in Saifai [26] , 6.72% in western Uttar Pradesh [27] . Moreover, the prevalence has been shown to be higher in urban India as compared to the rural parts.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of gestational diabetes mellitus and associated risk factors among rural pregnant women attending antenatal care

Jaiswal¹,

Shankar²,

Jaiswal³

2022

Int. J. Clin. Obstet. Gynaecol.

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Background: The prevalence of Gestational Diabetes Mellitus (GDM) is increasing continuously worldwide and in recent years it is emerging as a major public health challenge in India. GDM is a common complication during pregnancy that can fatally affect the outcome of pregnancy, hence early diagnosis and appropriate measures are essential. The present study was conducted to estimate the prevalence and associated risk factors affecting GDM in rural, Uttar Pradesh, India. Methods: A cross-sectional community based study was conducted among 605 pregnant women registered at Primary Health Center (PHC) of Harhua block of Varanasi district Uttar Pradesh. Following DIPSI Guideline, One step OGTT with two hours after taking 75 gm oral glucose irrespective of last meal was used and screen by Glucometer. The plasma glucose level of ≥140 mg/dL was taken as cutoff for confirm the GDM in pregnant women. Statistical analysis was performed using SPSS version 20 Software. Results: The mean age of pregnant women was found to be 24.39 ± 3.17, ranging between 17 and 36 years. 46 out of 605 pregnant women (7.6%) were diagnosed as having GDM. The age (X 2 =42.42; P<.01), educational status (X 2 =16.72; P<.01) and BMI (X 2 = 53.58; p<.01) of pregnant women were significantly associated with prevalence of GDM. Moreover higher age (AOR= 9.33, 95% CI: 3.20-27.19; p<.01) and obesity (AOR= 17.96, p<.01) were seen as significant and strong predictor of GDM. Conclusions: This study has shown the prevalence of GDM in all socio-demographic categories, especially in pregnant women with high age and high BMI. GDM can lead to type-2 diabetes in pregnant women later on after delivery. Proper awareness about antenatal care and use of mobile medical units in the screening and diagnosis of GDM can play an important role in ensuring better maternal and fetal health.

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