Dataset Information

Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies.

ABSTRACT:

Objective

Nowadays, body mass index (BMI) is used to evaluate the risk stratification of obesity-related pregnancy complications in clinics. However, BMI cannot reflect fat distribution or the proportion of adipose to nonadipose tissue. The objective of this study is to evaluate the association of maternal first or second trimester central obesity with the risk of GDM. Research Design and Methods. We searched in PubMed, Embase, and Web of Science for English-language medical literature published up to 12 May 2019. Cohort studies were only included in the search. Abdominal subcutaneous fat thickness, waist circumference, waist-hip ratio or body fat distribution were elected as measures of maternal central obesity, and all diagnostic criteria for GDM were accepted. The random effect meta-analysis was performed to evaluate the relationship between central obesity and the risk of GDM.

Results

A total of 11 cohort studies with an overall sample size of 27,675 women and 2,226 patients with GDM were included in the analysis. The summary estimate of GDM risk in the central obesity pregnant women was 2.76 (95% confidence interval [CI]: 2.35-3.26) using the adjusted odds ratio (OR). The degree of heterogeneity among the studies was low (I ² = 14.4, P = 0.307). The subgroup analyses showed that heterogeneity was affected by selected study characteristics (methods of exposure and trimesters). After adjusting for potential confounds, the OR of adjusted BMI was significant (OR = 3.07, 95% CI: 2.35-4.00).

Conclusions

Our findings indicate that the risk of GDM was positively associated with maternal central obesity.

SUBMITTER: Yao D

PROVIDER: S-EPMC7157762 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies.

Yao Da D Chang Qing Q Wu Qi-Jun QJ Gao Shan-Yan SY Zhao Huan H Liu Ya-Shu YS Jiang Yu-Ting YT Zhao Yu-Hong YH

Journal of diabetes research 20200402

<h4>Objective</h4>Nowadays, body mass index (BMI) is used to evaluate the risk stratification of obesity-related pregnancy complications in clinics. However, BMI cannot reflect fat distribution or the proportion of adipose to nonadipose tissue. The objective of this study is to evaluate the association of maternal first or second trimester central obesity with the risk of GDM. <i>Research Design and Methods</i>. We searched in PubMed, Embase, and Web of Science for English-language medical liter ...[more]

PMID: 32337296

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Project description:Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.

Project description:BackgroundThe association between maternal obesity and preterm birth remains controversial and inconclusive, and the effects of gestational diabetes mellitus (GDM) and preeclampsia (PE) on the relationship between obesity and preterm birth have not been studied. We aimed to clarify the relationship between prepregnancy body mass index (BMI) and the phenotypes of preterm birth and evaluate the mediation effects of GDM and PE on the relationship between prepregnancy BMI and preterm birth.MethodsWe conducted a prospective cohort study of 43,056 women with live singleton births from 2017 through 2019. According to the WHO International Classification, BMI was classified as underweight (BMI < 18.5 kg/m2), normal weight (BMI 18.5-25 kg/m2), overweight (BMI 25-30 kg/m2) and obese (BMI ≥30 kg/m2). Preterm birth was defined as gestational age less than 37 weeks (extremely, < 28 weeks; very, 28-31 weeks; and moderately, 32-36 weeks). The clinical phenotypes of preterm birth included spontaneous preterm birth (spontaneous preterm labor and premature rupture of the membranes) and medically indicated preterm birth. We further analyzed preterm births with GDM or PE. Multivariable logistic regression analysis and causal mediation analysis were performed.ResultsRisks of extremely, very, and moderately preterm birth increased with BMI, and the highest risk was observed for obese women with extremely preterm birth (OR 3.43, 95% CI 1.07-10.97). Maternal obesity was significantly associated with spontaneous preterm labor (OR 1.98; 95% CI 1.13-3.47), premature rupture of the membranes (OR 2.04; 95% CI 1.08-3.86) and medically indicated preterm birth (OR 2.05; 95% CI 1.25-3.37). GDM and PE mediated 13.41 and 36.66% of the effect of obesity on preterm birth, respectively. GDM mediated 32.80% of the effect of obesity on spontaneous preterm labor and PE mediated 64.31% of the effect of obesity on medically indicated preterm birth.ConclusionsMaternal prepregnancy obesity was associated with all phenotypes of preterm birth, and the highest risks were extremely preterm birth and medically indicated preterm birth. GDM and PE partially mediated the association between obesity and preterm birth.

Dataset Information

Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies.

Objective

Results

Conclusions

Publications

Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies.

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