Characteristics of Glucose-Lipid Metabolism in Early Pregnancy Among Overweight and Obese Women and Their Predictive Value for Gestational Diabetes Mellitus

Xia Chen,1 Jianmin Zhang,1 Yuanru Tang,1 Yan Zhang,2 Ziwen Ma,2 Yifan Hu2 1Department of Gynecology, Waitan Street Community Health Service Center, Shanghai, People’s Republic of China; 2Department of Gynecology and Obstetrics, Pudong New Area Health Care Hospital for Women and Child Gynecological Clinic, Shanghai, People’s Republic of ChinaCorrespondence: Jianmin Zhang, Email [email protected]: This study explores the link between women’s pre-pregnancy overweight and obesity and glucose and lipid metabolism in their early pregnancy. It assesses how early pregnancy glucose and lipid levels predict gestational diabetes mellitus (GDM) risk, aiming to offer foundational weight management strategies for overweight and obese women to prevent GDM.Patients and Methods: This study analyzed 2172 pregnant women from 2017 to 2021 at Waitan Street Community Health Service Center, Shanghai, monitoring early pregnancy (7– 10 weeks) glucose and lipid levels (TG, TC, HDL-C, LDL-C, FBG, HbA1c) and 24-week OGTT values. Pre-pregnancy BMI categorized participants into overweight and obese, normal, and underweight groups. We compared early pregnancy glycemic and lipid metrics and GDM incidence across groups, examining the relationship between pre-pregnancy BMI and early pregnancy blood metrics. The overweight and obese cohort was further split into GDM and non-GDM groups, comparing early pregnancy glycolipid indicators and assessing their predictive value for GDM development.Results: In the overweight and obese group, maternal FBG, HbA1c, TG, and LDL-C were higher, while HDL-C was lower than in normal and underweight groups (P< 0.05), with a higher GDM incidence (P< 0.05). Pre-pregnancy BMI positively correlated with FBG, HbA1c, TG, and LDL-C levels (r=0.556, 0.567, 0.686, 0.214; P< 0.05) but not HDL-C. Each 1-unit BMI increase raised GDM risk by 0.204 times (P< 0.05). FBG, TG, and LDL-C had high predictive accuracy for GDM in overweight and obese women, with AUCs of 0.991, 0.994, and 0.935, respectively.Conclusion: Pre-pregnancy overweight and obesity can cause early pregnancy glucose and lipid abnormalities, raising GDM risk. Early testing in such women is a strong predictor for GDM.Keywords: pregnant women, overweight and obesity, pre-pregnancy body mass index, glucose and lipid metabolism, gestational diabetes mellitus

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characteristics of Glucose-Lipid Metabolism in Early Pregnancy Among Overweight and Obese Women and Their Predictive Value for Gestational Diabetes Mellitus

SHILAP Revista de lepidopterología
Gestational Diabetes Research and Management
article

Characteristics of Glucose-Lipid Metabolism in Early Pregnancy Among Overweight and Obese Women and Their Predictive Value for Gestational Diabetes Mellitus

article en

Abstract

Xia Chen,1 Jianmin Zhang,1 Yuanru Tang,1 Yan Zhang,2 Ziwen Ma,2 Yifan Hu2 1Department of Gynecology, Waitan Street Community Health Service Center, Shanghai, People’s Republic of China; 2Department of Gynecology and Obstetrics, Pudong New Area Health Care Hospital for Women and Child Gynecological Clinic, Shanghai, People’s Republic of ChinaCorrespondence: Jianmin Zhang, Email [email protected]: This study explores the link between women’s pre-pregnancy overweight and obesity and glucose and lipid metabolism in their early pregnancy. It assesses how early pregnancy glucose and lipid levels predict gestational diabetes mellitus (GDM) risk, aiming to offer foundational weight management strategies for overweight and obese women to prevent GDM.Patients and Methods: This study analyzed 2172 pregnant women from 2017 to 2021 at Waitan Street Community Health Service Center, Shanghai, monitoring early pregnancy (7– 10 weeks) glucose and lipid levels (TG, TC, HDL-C, LDL-C, FBG, HbA1c) and 24-week OGTT values. Pre-pregnancy BMI categorized participants into overweight and obese, normal, and underweight groups. We compared early pregnancy glycemic and lipid metrics and GDM incidence across groups, examining the relationship between pre-pregnancy BMI and early pregnancy blood metrics. The overweight and obese cohort was further split into GDM and non-GDM groups, comparing early pregnancy glycolipid indicators and assessing their predictive value for GDM development.Results: In the overweight and obese group, maternal FBG, HbA1c, TG, and LDL-C were higher, while HDL-C was lower than in normal and underweight groups (P< 0.05), with a higher GDM incidence (P< 0.05). Pre-pregnancy BMI positively correlated with FBG, HbA1c, TG, and LDL-C levels (r=0.556, 0.567, 0.686, 0.214; P< 0.05) but not HDL-C. Each 1-unit BMI increase raised GDM risk by 0.204 times (P< 0.05). FBG, TG, and LDL-C had high predictive accuracy for GDM in overweight and obese women, with AUCs of 0.991, 0.994, and 0.935, respectively.Conclusion: Pre-pregnancy overweight and obesity can cause early pregnancy glucose and lipid abnormalities, raising GDM risk. Early testing in such women is a strong predictor for GDM.Keywords: pregnant women, overweight and obesity, pre-pregnancy body mass index, glucose and lipid metabolism, gestational diabetes mellitus

SHILAP Revista de lepidopterología
Good health and well-being
Openalex Percentile: Top 42%
Gestational Diabetes Research and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.