Risk factor and regression analysis for diabetes

Wandi Su; Yi Wang

doi:10.1117/12.2669384

24 March 2023 Risk factor and regression analysis for diabetes

Wandi Su, Yi Wang

Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126114Y (2023) https://doi.org/10.1117/12.2669384
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom

Abstract

The fundamental structure of the metabolic syndrome has been clarified based on factor analysis and a multivariate correlation approach. However, the danger of diabetes in pregnant women (e.g., perinatal mortality and congenital deformity rates) has been extensively studied in research regarding gestational diabetes mellitus to date. There is little information on whether being pregnant might make one more likely to get diabetes. The number of pregnancies and other metabolic measurement variables were analyzed using factor analysis in the current study in terms of the data from the 307 participants National Institute of Diabetes and Digestive and Kidney Diseases. The purpose of this study was to investigate the attribution of the factors and other metabolic measuring indicators and determine the relationship between these clusters and the risk of diabetes. According to the analysis, all eight fundamental components were noteworthy indicators of diabetes advancement. The discoveries bolster the rising theory that pregnancies are related. It is argued that pregnancy may increment a woman’s hazard of creating diabetes. These results shed light on guiding further exploration of treatment and prevention for diabetes.

Citation Download Citation

Wandi Su and Yi Wang "Risk factor and regression analysis for diabetes", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126114Y (24 March 2023); https://doi.org/10.1117/12.2669384

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available