| Title: | Risk stratification of diabetes and hypertension using body mass index (BMI) & waist circumference (WC) |
| Lead Institution: | KISTI |
| Principal investigator: | Dr Hyojung Paik |
Application 69112
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About
In this research, we're going to delineate the boundaries of such thresholds of BMI (Body Mass Index) and WC (Waist Circumference) using machine learning algorithms to find out risk groups for diabetes and hypertension more precisely. This project was planned as a 36 months project consisting of five steps. First, we will use the baseline data of all participant (i.e. age, sex, life-or-death information and other demography) Second, we will determine type 2 diabetes and hypertension cases. Third, we will cluster the study population based on age, BMI and WC Fourth and Fifth, we will identify the subpopulation as a categorized risk group by merging the clusters from 3 and will estimate the prevalence of diseases are compared between risk groups. Our results will provide a system that stratifies the risk of type 2 diabetes and hypertension using BMI and WC. The system will identify the risk groups more precisely that previous stratification based on simple discretization of BMI or WC with a certain threshold. And, the risk stratification can be used for the genetic study of diabetes and hypertension. For example, genetic difference between the stratification might implicate pleiotropic effect of genetic loci that are related to BMI, WC, diabetes, and hypertension.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7087 | Analysis of the docking property of host variants of hACE2 for SARS-CoV-2 in a large cohort | Hyojung Paik (+2) | 2022 | PLOS Computational Biology |
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