Data_Sheet_1_Individual and combined association between nutritional trace metals and the risk of preterm birth in a recurrent pregnancy loss cohort.docx

التفاصيل البيبلوغرافية
العنوان: Data_Sheet_1_Individual and combined association between nutritional trace metals and the risk of preterm birth in a recurrent pregnancy loss cohort.docx
المؤلفون: Yilin Liu, Tingting Wang, Yunpeng Ge, Hongfei Shen, Jiapo Li, Chong Qiao
سنة النشر: 2023
مصطلحات موضوعية: Clinical and Sports Nutrition, Dietetics and Nutrigenomics, Nutritional Physiology, Public Nutrition Intervention, Nutrition and Dietetics not elsewhere classified, Food Chemistry and Molecular Gastronomy (excl. Wine), Food Nutritional Balance, Animal Nutrition, Crop and Pasture Nutrition, preterm birth, recurrent pregnancy loss, nutritional trace metals, Bayesian kernel machine regression, metal mixture
الوصف: Background Recurrent pregnancy loss (RPL) was associated with an elevated risk of pregnancy complications, particularly preterm birth (PTB). However, the risk factors associated with PTB in RPL remained unclear. Emerging evidence indicated that maternal exposure to metals played a crucial role in the development of PTB. The objective of our study was to investigate the individual and combined associations of nutritional trace metals (NTMs) during pregnancy with PTB in RPL. Methods Using data from a recurrent pregnancy loss cohort (n = 459), propensity score matching (1:3) was performed to control for covariates. Multiple logistic regression and multiple linear regression were employed to identify the individual effects, while elastic-net regularization (ENET) and Bayesian kernel machine regression (BKMR) were used to examine the combined effects on PTB in RPL. Results The logistic regression model found that maternal exposure to copper (Cu) (quantile 4 [Q4] vs. quantile 1 [Q1], odds ratio [OR]: 0.21, 95% confidence interval [CI]: 0.05, 0.74) and zinc (Zn) (Q4 vs. Q1, OR: 0.19, 95%CI: 0.04, 0.77) was inversely associated with total PTB risk. We further constructed environmental risk scores (ERSs) using principal components and interaction terms derived from the ENET model to predict PTB accurately (p < 0.001). In the BKMR model, we confirmed that Cu was the most significant component (PIP = 0.85). When other metals were fixed at the 25 th and 50 th percentiles, Cu was inversely associated with PTB. In addition, we demonstrated the non-linear relationships of Zn with PTB and the potential interaction between Cu and other metals, including Zn, Ca, and Fe. Conclusion In conclusion, our study highlighted the significance of maternal exposure to NTMs in RPL and its association with PTB risk. Cu and Zn were inversely associated with PTB risk, with Cu identified as a crucial factor. Potential interactions between Cu and other metals (Zn, Ca, and Fe) further contributed to the understanding of PTB etiology in RPL. ...
نوع الوثيقة: dataset
اللغة: unknown
Relation: https://figshare.com/articles/dataset/Data_Sheet_1_Individual_and_combined_association_between_nutritional_trace_metals_and_the_risk_of_preterm_birth_in_a_recurrent_pregnancy_loss_cohort_docx/24670248
DOI: 10.3389/fnut.2023.1205748.s001
الاتاحة: https://doi.org/10.3389/fnut.2023.1205748.s001
https://figshare.com/articles/dataset/Data_Sheet_1_Individual_and_combined_association_between_nutritional_trace_metals_and_the_risk_of_preterm_birth_in_a_recurrent_pregnancy_loss_cohort_docx/24670248
Rights: CC BY 4.0
رقم الانضمام: edsbas.71C023A1
قاعدة البيانات: BASE
الوصف
DOI:10.3389/fnut.2023.1205748.s001