Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy
ObjectiveThe prediction of gestational diabetes mellitus (GDM) by body composition-related indicators in the first trimester was analyzed under different body mass index (BMI) values before pregnancy.MethodsThis was a retrospective analysis of pregnant women who were treated, had documented data, an...
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2022.916883/full |
| _version_ | 1811335914676289536 |
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| author | Li Xintong Xu Dongmei Xu Dongmei Zhang Li Cao Ruimin Hao Yide Cui Lingling Chen Tingting Guo Yingying Li Jiaxin |
| author_facet | Li Xintong Xu Dongmei Xu Dongmei Zhang Li Cao Ruimin Hao Yide Cui Lingling Chen Tingting Guo Yingying Li Jiaxin |
| author_sort | Li Xintong |
| collection | DOAJ |
| description | ObjectiveThe prediction of gestational diabetes mellitus (GDM) by body composition-related indicators in the first trimester was analyzed under different body mass index (BMI) values before pregnancy.MethodsThis was a retrospective analysis of pregnant women who were treated, had documented data, and received regular perinatal care at the Third Affiliated Hospital of Zhengzhou University from January 1, 2021, to December 31, 2021. Women with singleton pregnancies who did not have diabetes before pregnancy were included. In the first trimester (before the 14th week of pregnancy), bioelectric impedance assessment (BIA) was used to analyze body composition-related indicators such as protein levels, mineral levels, fat volume, and the waist-hip fat ratio. The Pearman’s correlation coefficient was used to evaluate the linear relationship between the continuous variables and pre-pregnancy body mass index (BMI). In the univariate body composition analysis, the association with the risk of developing GDM was included in a multivariate analysis using the relative risk and 95% confidence interval obtained from logarithmic binomial regression, and generalized linear regression was used for multivariate regression analysis. Furthermore, the area under the curve (AUC) was calculated by receiver operating characteristic (ROC) curves. The optimal cutoff value of each risk factor was calculated according to the Youden Index.ResultsIn a retrospective study consisting of 6698 pregnant women, we collected 1109 cases of gestational diabetes. Total body water (TBW), protein levels, mineral levels, bone mineral content (BMC), body fat mass (BFM), soft lean mass (SLM), fat-free mass (FMM), skeletal muscle mass (SMM), percent body fat (PBF), the waist-hip ratio (WHR), the visceral fat level (VFL), and the basal metabolic rate (BMR) were significantly higher in the GDM group than in the normal group (P<0.05). Under the pre-pregnancy BMI groupings, out of 4157 pregnant women with a BMI <24 kg/m2, 456 (10.97%) were diagnosed with GDM, and out of 2541 pregnant women with a BMI ≥24 kg/m2, 653 (25.70%) were diagnosed with GDM. In the generalized linear regression model, it was found that in all groups of pregnant women, pre-pregnancy BMI, age, gestational weight gain (GWG) in the first trimester, and weight at the time of the BIA had a certain risk for the onset of GDM. In Model 1, without adjusting for confounders, the body composition indicators were all positively correlated with the risk of GDM. In Model 3, total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM. After Model 4 was adjusted for confounders, only the waist-hip ratio was positively associated with GDM onset. Among pregnant women with a pre-pregnancy BMI <24 kg/m2, the body composition-related indicators in Model 2 were all related to the onset of GDM. In Model 3, total body water, soft lean mass, fat-free mass, and the basal metabolic rate were negatively correlated with GDM onset. In the body composition analysis of among women with a pre-pregnancy BMI ≥ 24 kg/m2, only Model 1 and Model 2 were found to show positive associations with GDM onset. In the prediction model, in the basic data of pregnant women, the area under the receiver operating characteristic curve predicted by gestational weight gain for GDM was the largest (0.795), and its cutoff value was 1.415 kg. In the body composition results, the area under the receiver operating characteristic curve of body fat mass for predicting GDM risk was larger (0.663) in all pregnant women.ConclusionsThrough this retrospective study, it was found that the body composition-related indicators were independently associated with the onset of GDM in both the pre-pregnancy BMI <24 kg/m2 and pre-pregnancy BMI ≥24 kg/m2 groups. Body fat mass, the visceral fat level, and the waist-hip ratio had a higher correlation with pre-pregnancy BMI. Total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM after adjusting for some confounders. In all pregnant women, the waist-hip ratio was found to be up to 4.562 times the risk of GDM development, and gestational weight gain had the best predictive power for GDM. Gestational weight gain in early pregnancy, body fat mass, and the waist-hip ratio can assess the risk of GDM in pregnant women, which can allow clinicians to predict the occurrence of GDM in pregnant women as early as possible and implement interventions to reduce adverse perinatal outcomes. |
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| spelling | doaj.art-a7f01f4002b94a26ba528b8772895f602022-12-22T02:37:33ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922022-10-011310.3389/fendo.2022.916883916883Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancyLi Xintong0Xu Dongmei1Xu Dongmei2Zhang Li3Cao Ruimin4Hao Yide5Cui Lingling6Chen Tingting7Guo Yingying8Li Jiaxin9Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Perinatal Health, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaAnesthesiology, Xinxiang Medical University, Xinxiang, ChinaDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, ChinaDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, ChinaDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, ChinaDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, ChinaObjectiveThe prediction of gestational diabetes mellitus (GDM) by body composition-related indicators in the first trimester was analyzed under different body mass index (BMI) values before pregnancy.MethodsThis was a retrospective analysis of pregnant women who were treated, had documented data, and received regular perinatal care at the Third Affiliated Hospital of Zhengzhou University from January 1, 2021, to December 31, 2021. Women with singleton pregnancies who did not have diabetes before pregnancy were included. In the first trimester (before the 14th week of pregnancy), bioelectric impedance assessment (BIA) was used to analyze body composition-related indicators such as protein levels, mineral levels, fat volume, and the waist-hip fat ratio. The Pearman’s correlation coefficient was used to evaluate the linear relationship between the continuous variables and pre-pregnancy body mass index (BMI). In the univariate body composition analysis, the association with the risk of developing GDM was included in a multivariate analysis using the relative risk and 95% confidence interval obtained from logarithmic binomial regression, and generalized linear regression was used for multivariate regression analysis. Furthermore, the area under the curve (AUC) was calculated by receiver operating characteristic (ROC) curves. The optimal cutoff value of each risk factor was calculated according to the Youden Index.ResultsIn a retrospective study consisting of 6698 pregnant women, we collected 1109 cases of gestational diabetes. Total body water (TBW), protein levels, mineral levels, bone mineral content (BMC), body fat mass (BFM), soft lean mass (SLM), fat-free mass (FMM), skeletal muscle mass (SMM), percent body fat (PBF), the waist-hip ratio (WHR), the visceral fat level (VFL), and the basal metabolic rate (BMR) were significantly higher in the GDM group than in the normal group (P<0.05). Under the pre-pregnancy BMI groupings, out of 4157 pregnant women with a BMI <24 kg/m2, 456 (10.97%) were diagnosed with GDM, and out of 2541 pregnant women with a BMI ≥24 kg/m2, 653 (25.70%) were diagnosed with GDM. In the generalized linear regression model, it was found that in all groups of pregnant women, pre-pregnancy BMI, age, gestational weight gain (GWG) in the first trimester, and weight at the time of the BIA had a certain risk for the onset of GDM. In Model 1, without adjusting for confounders, the body composition indicators were all positively correlated with the risk of GDM. In Model 3, total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM. After Model 4 was adjusted for confounders, only the waist-hip ratio was positively associated with GDM onset. Among pregnant women with a pre-pregnancy BMI <24 kg/m2, the body composition-related indicators in Model 2 were all related to the onset of GDM. In Model 3, total body water, soft lean mass, fat-free mass, and the basal metabolic rate were negatively correlated with GDM onset. In the body composition analysis of among women with a pre-pregnancy BMI ≥ 24 kg/m2, only Model 1 and Model 2 were found to show positive associations with GDM onset. In the prediction model, in the basic data of pregnant women, the area under the receiver operating characteristic curve predicted by gestational weight gain for GDM was the largest (0.795), and its cutoff value was 1.415 kg. In the body composition results, the area under the receiver operating characteristic curve of body fat mass for predicting GDM risk was larger (0.663) in all pregnant women.ConclusionsThrough this retrospective study, it was found that the body composition-related indicators were independently associated with the onset of GDM in both the pre-pregnancy BMI <24 kg/m2 and pre-pregnancy BMI ≥24 kg/m2 groups. Body fat mass, the visceral fat level, and the waist-hip ratio had a higher correlation with pre-pregnancy BMI. Total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM after adjusting for some confounders. In all pregnant women, the waist-hip ratio was found to be up to 4.562 times the risk of GDM development, and gestational weight gain had the best predictive power for GDM. Gestational weight gain in early pregnancy, body fat mass, and the waist-hip ratio can assess the risk of GDM in pregnant women, which can allow clinicians to predict the occurrence of GDM in pregnant women as early as possible and implement interventions to reduce adverse perinatal outcomes.https://www.frontiersin.org/articles/10.3389/fendo.2022.916883/fullbody mass indexgestational diabetesbioelectrical impedance assessmentbody compositionbody fat mass |
| spellingShingle | Li Xintong Xu Dongmei Xu Dongmei Zhang Li Cao Ruimin Hao Yide Cui Lingling Chen Tingting Guo Yingying Li Jiaxin Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy Frontiers in Endocrinology body mass index gestational diabetes bioelectrical impedance assessment body composition body fat mass |
| title | Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| title_full | Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| title_fullStr | Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| title_full_unstemmed | Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| title_short | Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| title_sort | correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy |
| topic | body mass index gestational diabetes bioelectrical impedance assessment body composition body fat mass |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2022.916883/full |
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