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Angela Köninger Department of Gynecology and Obstetrics, University of Duisburg-Essen, Essen, Germany

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Antonella Iannaccone Department of Gynecology and Obstetrics, University of Duisburg-Essen, Essen, Germany

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Ensar Hajder Department of Gynecology and Obstetrics, University of Duisburg-Essen, Essen, Germany

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Mirjam Frank Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University of Duisburg-Essen, Essen, Germany

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Boerge Schmidt Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University of Duisburg-Essen, Essen, Germany

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Ekkehard Schleussner Department of Obstetrics, Jena University Hospital, Jena, Germany

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Rainer Kimmig Department of Gynecology and Obstetrics, University of Duisburg-Essen, Essen, Germany

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Alexandra Gellhaus Department of Gynecology and Obstetrics, University of Duisburg-Essen, Essen, Germany

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Hans Dieplinger Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria

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significant risk factor for developing GDM in non-PCOS ( 16 ) as well as in PCOS patients ( 35 , 36 ). In uncomplicated pregnancies, IR increases physiologically and is necessary for proper materno-fetal glucose transfer. In the case of elevated pre-pregnancy

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0064
Volume/Issue:
Volume 8: Issue 5
Open access
Sanna Mustaniemi Public Health Promotion Unit, National Institute for Health and Welfare, Helsinki, Finland
PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

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Marja Vääräsmäki Public Health Promotion Unit, National Institute for Health and Welfare, Helsinki, Finland
PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

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Johan G Eriksson Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Folkhälsan Research Centre, Helsinki, Finland

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Mika Gissler Information Services Department, National Institute for Health and Welfare, Helsinki, Finland
Division of Family Medicine, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden

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Hannele Laivuori Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Department of Obstetrics and Gynaecology, Tampere University Hospital, Tampere, Finland
Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland

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Hilkka Ijäs Public Health Promotion Unit, National Institute for Health and Welfare, Helsinki, Finland
PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

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Aini Bloigu PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

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Eero Kajantie Public Health Promotion Unit, National Institute for Health and Welfare, Helsinki, Finland
PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

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Laure Morin-Papunen PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

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-diabetic mothers were also included in the study. The GDM status of all participants was confirmed by their medical records: 12 women with pre-pregnancy diabetes were excluded. Sixteen women were recruited during two pregnancies, and their latter pregnancy was

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-18-0076
Volume/Issue:
Volume 7: Issue 7
Open access
Chenyu Jiang Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Mi Zhou Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Huai Bai Laboratory of Genetic Disease and Perinatal Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Meng Chen Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Chunyi Yang Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Kaifeng Hu Laboratory of Genetic Disease and Perinatal Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Yujie Wu Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Qingqing Liu Laboratory of Genetic Disease and Perinatal Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Yangyu Zhao Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

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Xinghui Liu Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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Ping Fan Laboratory of Genetic Disease and Perinatal Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

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offspring ( 1 , 3 ). The pathogenesis of GDM is still unclear, but there is growing evidence that genetic variants, advanced maternal age, pre-pregnancy BMI, oxidative stress, chronic inflammation, dyslipidemia, unbalanced hormone secretion, and/or β

Article Type:
Research Article
Collections:
Metabolic Syndrome and Diabetes
DOI:
https://doi.org/10.1530/EC-22-0369
Volume/Issue:
Volume 12: Issue 3
Open access
Yao Su Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Li Chen Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Dong-Yao Zhang Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Xu-Pei Gan Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Yan-Nan Cao Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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De-Cui Cheng Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Wen-Yu Liu Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Fei-Fei Li Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Xian-Ming Xu Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Hong-Kun Wang Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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indicates that they are obese ( 4 ). Pre-pregnancy BMI = weight (kg)/height (m 2 ). A diagnosis of GDM can be confirmed using a 75 g oral glucose tolerance test (OGTT), with blood glucose levels when fasting and 1 and 2 h after ingesting the glucose of ≥5

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0433
Volume/Issue:
Volume 10: Issue 11
Open access
Thorben Hoffmann Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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Yousef Ashraf Tawfik Morcos Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

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Ruth Janoschek Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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Eva-Maria Turnwald Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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Antje Gerken Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

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Annette Müller Center for Pediatric Pathology at the University Hospital Cologne, Cologne, Germany

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Gerhard Sengle Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany
Cologne Center for Musculoskeletal Biomechanics (CCMB), Cologne, Germany

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Jörg Dötsch Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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Sarah Appel Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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Eva Hucklenbruch-Rother Department of Pediatrics, and Adolescent Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany

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. Journal of Clinical Endocrinology and Metabolism 2007 92 969 – 975 . ( https://doi.org/10.1210/jc.2006-2083 ) 12 Van Lieshout RJ Taylor VH Boyle MH . Pre‐pregnancy and pregnancy obesity and neurodevelopmental outcomes in offspring: a systematic

Article Type:
Research Article
Collections:
Bone and Mineral Metabolism
DOI:
https://doi.org/10.1530/EC-22-0069
Volume/Issue:
Volume 11: Issue 3
Open access
Tianze Ding T Ding, Department of Clinical Nutrition, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Peijie Liu P Liu, Department of Clinical Nutrition, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Jie Jia J Jia, Department of Clinical Nutrition, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Hui Wu H Wu, Department of Nutrition, Seventh People’s Hospital of shanghai University of Traditional Chinese Medicine, Shanghai, China

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Jie Zhu J Zhu, Nutrition and Foods Program, School of Family and Consumer Sciences, Texas State University, San Marcos, United States

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Kefeng Yang K Yang, Department of Clinical Nutrition, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Introduction: Gestational diabetes mellitus (GDM) significantly affects pregnancy outcomes. Therefore, it is crucial to develop prediction models since they can guide timely interventions to reduce the incidence of GDM and its associated adverse effects.

Methods: A total of 554 pregnant women were selected and their sociodemographic characteristics, clinical data and dietary data were collected. Dietary data was investigated by a validated semi-quantitative food frequency questionnaire (FFQ). We applied random forest mean decrease impurity for feature selection and the models are built using Logistic Regression, XGBoost, and LightGBM algorithms. The prediction performance of different models was compared by Accuracy, Sensitivity, Specificity, Area Under Curve (AUC) and Hosmer-Lemeshow test.

Results: Blood glucose, age, pre-pregnancy body mass index (BMI), triglycerides and high-density lipoprotein cholesterol (HDL) were the top five features according to the feature selection. Among the three algorithms, XGBoost performed best with an AUC of 0.788, LightGBM came second (AUC = 0.749), and Logistic Regression performed the worst (AUC = 0.712). In addition, XGBoost and LightGBM both achieved a fairly good performance when dietary information was included, surpassing their performance on the non-dietary dataset (0.788 vs. 0.718 in XGBoost; 0.749 vs. 0.726 in LightGBM).

Conclusion: XGBoost and LightGBM algorithms outperform Logistic Regression in predicting GDM among the Chinese pregnant women. In addition, dietary data may have a positive effect on improving model performance, which deserves more in-depth investigation with larger sample size.

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-24-0169
Volume/Issue:
Accepted Manuscripts
Open access
Ling-Jun Li Division of O&G, KK Women’s and Children’s Hospital, Singapore, Singapore
O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore

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Izzuddin M Aris Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore

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Lin Lin Su Department of O&G, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

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Yap Seng Chong Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
Department of O&G, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

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Tien Yin Wong O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore

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Kok Hian Tan Division of O&G, KK Women’s and Children’s Hospital, Singapore, Singapore
O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore

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Jie Jin Wang O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore

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maternal education, household income, family history of diabetes, parity, pre-pregnancy weight, smoking and alcohol drinking in the past one year and physical activity in the past three months. Weight gain between baseline and follow-up visits (5-year

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-17-0359
Volume/Issue:
Volume 7: Issue 3
Open access
Stine Linding Andersen Department of Clinical Biochemistry, Aalborg University Hospital, Aalborg, Denmark
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark

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Louise Knøsgaard Department of Clinical Biochemistry, Aalborg University Hospital, Aalborg, Denmark
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark

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Aase Handberg Department of Clinical Biochemistry, Aalborg University Hospital, Aalborg, Denmark
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark

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Peter Vestergaard Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
Department of Endocrinology, Aalborg University Hospital, Aalborg, Denmark
Steno Diabetes Center North Jutland, Aalborg University Hospital, Aalborg, Denmark

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Stig Andersen Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
Department of Geriatrics, Aalborg University Hospital, Aalborg, Denmark

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( 17 ). Thus, the MBR holds information on maternal height and pre-pregnancy body weight as well as smoking status in the first trimester of pregnancy including the number of cigarettes smoked per day. This study included all live-birth pregnancies

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0376
Volume/Issue:
Volume 10: Issue 9
Open access
Beibei Zhu School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Yan Han School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Fen Deng School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Kun Huang School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Shuangqin Yan Ma’anshan Maternal and Child Health Care Center, Ma’anshan, Anhui, China

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Jiahu Hao School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Peng Zhu School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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Fangbiao Tao School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

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model. Stratified analyses of the associations between thyroid markers and the risk of GDM were conducted according to pre-pregnancy BMI, parity, smoking status, TPOAb and TgAb status using logistic regression. The multiplicative interaction term was

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0088
Volume/Issue:
Volume 10: Issue 7
Open access
Xin He Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Qin Yan Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Chazhen Liu Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Zhengyuan Wang Department of Nutrition Hygiene, Division of Health Risk Factor Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Ping Liao Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Tong Liu Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Zehuan Shi Department of Nutrition Hygiene, Division of Health Risk Factor Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Qi Song Department of Nutrition Hygiene, Division of Health Risk Factor Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Xueying Cui Department of Nutrition Hygiene, Division of Health Risk Factor Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Wenjing Wang Laboratory of Functional Medicine, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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Jiajie Zang Department of Nutrition Hygiene, Division of Health Risk Factor Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China

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participants provided written informed consent. The study recruited pregnant women at different trimesters living in Shanghai for the past 6 months. On enrollment, we obtained demographic information (e.g. maternal age, pre-pregnancy height and weight, parity

Article Type:
Research Article
Collections:
Thyroid
DOI:
https://doi.org/10.1530/EC-21-0599
Volume/Issue:
Volume 11: Issue 4
Open access