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Bayes Conditional Probability-Based Causation Analysis between Gestational Diabetes Mellitus (GDM) and Pregnancy-Induced Hypertension (PIH): A Statistic Case Study in Harbin, China

Both gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH) would influence the gestation significantly. However, the causation between these two symptoms remains speculative. 16,404 pregnant women were identified in Harbin, China, in this study. We investigated and evaluated t...

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Published in:Journal of diabetes research 2022, Vol.2022, p.2590415-7
Main Authors: Diao, Dan, Diao, Fang, Xiao, Bin, Liu, Ning, Zheng, Dan, Li, Fengjuan, Yang, Xu
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description Both gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH) would influence the gestation significantly. However, the causation between these two symptoms remains speculative. 16,404 pregnant women were identified in Harbin, China, in this study. We investigated and evaluated the causal effect of GDM on PIH based on the Bayes conditional probability. The statistical results indicated that PIH might cause GDM, but not vice versa. Also, this case study demonstrated that the decrease temperature might also cause hypertension during pregnancy, and the prevalence rate of GDM increased with age. However, the prevalence of diabetes did not show a remarkable difference in varied areas and ages. This study could provide some essential information that will help to investigate the mechanism for GDM and PIH.
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subjects Bayes Theorem
Causality
China - epidemiology
Diabetes, Gestational - epidemiology
Eclampsia
Female
Gestational diabetes
Humans
Hypertension
Hypertension, Pregnancy-Induced - epidemiology
Hypertension, Pregnancy-Induced - etiology
Insulin resistance
Pregnancy
Probability
Risk Factors
title Bayes Conditional Probability-Based Causation Analysis between Gestational Diabetes Mellitus (GDM) and Pregnancy-Induced Hypertension (PIH): A Statistic Case Study in Harbin, China
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