Dataset Information

Prevalence and predictors of gestational diabetes mellitus in rural Assam: a cross-sectional study using mobile medical units.

ABSTRACT: OBJECTIVE:To determine the prevalence and predictors of gestational diabetes mellitus (GDM) in rural Assam, India using a network of Mobile Medical Units. STUDY DESIGN:A field-based cross-sectional study. SETTINGS:Rural areas of Assam state, India. PARTICIPANTS:A total of 1410 pregnant women in gestational age of 24-28 weeks INTERVENTION: Identification of pregnant women in 24-28 weeks of pregnancy from villages and administering them Government of India recommended oral glucose tolerance test for GDM confirmation. PRIMARY AND SECONDARY OUTCOME MEASURES:Presence of gestational diabetes among pregnant women, risk factors and predictors of GDM. RESULTS:A total of 1212 pregnant women underwent the oral glucose tolerance test. One hundred and ninety-eight women were ineligible due to existing chronic diseases or very high blood glucose level before the test. The overall GDM prevalence in Assam was 16.67% (95% CI 14.61% to 18.89%). Women aged 26-30 years (adjusted odds ratio, aOR 1.70; CI 1.14 to 2.52), who passed 10th class (aOR 1.58; CI 1.05 to 2.37), belonging to Muslim religion (aOR 1.52; 95%?CI 1.05 to 2.21) and above poverty line (aOR 1.38; 95%?CI 1.00 to 1.91) had significantly increased likelihood of developing GDM compared with respective baseline groups (p<0.05). Body mass index, gravida and being non-anaemic were non-significant risk factors for GDM. Family history of diabetes (aOR 1.82; 95%?CI 1.08 to 3.06) and smoking (aOR 1.61; 95%?CI 1.10 to 2.35) were significant and independent predictors of GDM. CONCLUSION:The prevalence of GDM in rural Assam is high. The mobile medical units may play a significant role in the implementation of GDM screening, diagnosis, treatment to ensure better maternal and foetal health outcomes in rural Assam.

SUBMITTER: Chanda S

PROVIDER: S-EPMC7656912 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence and predictors of gestational diabetes mellitus in rural Assam: a cross-sectional study using mobile medical units.

Chanda Subrata S Dogra Vishal V Hazarika Najeeb N Bambrah Hardeep H Sudke Ajit Kisanrao AK Vig Anupa A Hegde Shailendra Kumar SK

BMJ open 20201110 11

<h4>Objective</h4>To determine the prevalence and predictors of gestational diabetes mellitus (GDM) in rural Assam, India using a network of Mobile Medical Units.<h4>Study design</h4>A field-based cross-sectional study.<h4>Settings</h4>Rural areas of Assam state, India.<h4>Participants</h4>A total of 1410 pregnant women in gestational age of 24-28 weeks INTERVENTION: Identification of pregnant women in 24-28 weeks of pregnancy from villages and administering them Government of India recommended ...[more]

PMID: 33172942

Similar Datasets

Project description:BackgroundGestational diabetes mellitus (GDM) remains a global public health problem, which affects the well-being of mothers and their children in sub-Saharan Africa (SSA). Studies conducted in different geographical areas provide varied results on its prevalence and predictors. Understanding the extent and predictors of GDM in SSA is important for developing effective interventions and policies. Thus, this review aimed to investigate the prevalence of GDM and its predictive factors in sub-Saharan Africa.MethodsWe followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards in this review. An extensive search of the PubMed, Web of Sciences and EMBASE databases was carried out covering papers from 2012 to 2022 to assess the prevalence and predictors of GDM. Microsoft Excel 2019 was utilised for study management. GraphPad Prism Version 8.0 and the MedCalc statistical software were employed for data analysis. The findings were analysed using textual descriptions, tables, forest plots and heat maps.ResultsUsing 30 studies with 23,760 participants that satisfied the inclusion criteria, the review found the overall prevalence of GDM in SSA to be 3.05% (1.85%-4.54%). History of preterm delivery, alcohol consumption, family history of diabetes, history of stillbirths, history of macrosomia, overweight or obesity and advanced mother age were all significant predictors of gestational diabetes. Additionally, various biomarkers such as haemoglobin, adiponectin, leptin, resistin, visfatin, vitamin D, triglycerides and dietary intake type were identified as significant predictors of GDM.ConclusionIn sub-Saharan Africa, there is a high pooled prevalence of gestational diabetes mellitus. In the light of the predictors of GDM identified in this review, it is strongly recommended to implement early screening for women at risk of developing gestational diabetes during their pregnancy. This proactive approach is essential for enhancing the overall well-being of both mothers and children.

Project description:BackgroundPregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM/T2DM and compared to pregnancy outcome.MethodsSixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP® Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor.ResultsThe gestational age at delivery was 2 weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM + T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC = 0.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM + T2DM compared to controls (AUC = 0.90). The model also revealed that the triacylglycerols C17:2/36:4 and C18:1/34:1 are the best predictors of pre-term delivery (≤ 37 weeks) (AUC = 0.84).ConclusionsThis study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.

Project description:BackgroundEquitable access to healthcare for rural, tribal, and underprivileged people has been an emerging area of interest for researchers, academicians, and policymakers worldwide. Improving equitable access to healthcare requires innovative interventions. This calls for clarifying which operational model of a service innovation needs to be strengthened to achieve transformative change and bring sustainability to public health interventions. The current study aimed to identify the components of an operational model of mobile medical units (MMUs) as an innovative intervention to provide equitable access to healthcare.MethodsThe study empirically examined the impact of scalability, affordability, replicability (SAR), and immunization performance on the sustainability of MMUs to develop a framework for primary healthcare in the future. Data were collected via a survey answered by 207 healthcare professionals from six states in India. Partial least squares structural equation modeling (PLS-SEM) was conducted to empirically determine the interrelationships among various constructs.ResultsThe standardized path coefficients revealed that three factors (SAR) significantly influenced immunization performance as independent variables. Comparing the three hypothesized relationships demonstrates that replicability has the most substantial impact, followed by scalability and affordability. Immunization performance was found to have a significant direct effect on sustainability. For evaluating sustainability, MMUs constitute an essential component and an enabler of a sustainable healthcare system and universal health coverage.ConclusionThis study equips policymakers and public health professionals with the critical components of the MMU operational model leading toward sustainability. The research framework provides reliable grounds for examining the impact of scalability, affordability, and replicability on immunization coverage as the primary public healthcare outcome.

Dataset Information

Prevalence and predictors of gestational diabetes mellitus in rural Assam: a cross-sectional study using mobile medical units.

Publications

Prevalence and predictors of gestational diabetes mellitus in rural Assam: a cross-sectional study using mobile medical units.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets