Modeling Pregnancy Induced Hypertension among Pregnant Woman in Jimma University Specialized Hospital
Journal Title: IOSR Journal of Mathematics(IOSR-JM) - Year 2019, Vol 15, Issue 1
Abstract
Many longitudinal studies generate a dataset having two or more longitudinal repeated biomarkers measurement, which often depend on each other. In Gestational hypertension study the two important markers are gestational systolic blood pressure (GSBP) and diastolic blood pressure (GDBP) are collected simultaneously from a pregnant woman every visit. In such studies, evolution of the biomarkers over time and the association between them are commonly of interest. The aim of the analysis was to determine joint evolution and association of pregnancy induced systolic and diastolic blood pressure over time and determining their associated risk factors. The association among the two sequences is captured by correlated normal random effects included to account correlation between two outcomes In this study, we propose a joint random-effects model which enables two or more longitudinal repeated biomarker measurements to be modeled together while taking account of association between them. We apply these methods to a pregnancy induced hypertension among antenatal care follow up pregnant woman in Jimma University specialized hospital. Under joint analysis, two aspects of the relation were investigated: the association between the evolutions and the evolution of association. Results of the joint model suggested a very strong association between the evolutions of GSBP & GDBP and a slowly decreasing evolution of the association over gestational age. Sex of fetus, family history of pregnancy induced hypertension, gestational age, age of mother and number of Gravida are identified as associated risk factors. Joint model is able to address the same questions as separate model with more accuracy by addressing additional questions that may be of great interest to the researcher, such as the association of evolution and the evolution of association of the responses.
Authors and Affiliations
Abdulfeta Shafi Mohammednur, Neima Ridwan Abdo
Keywords
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- EP ID EP443068
- DOI 10.9790/5728-1501012228.
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