Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.

Journal: Clinical nutrition ESPEN

PMID: 39396701

Abstract

BACKGROUND AND AIM: Carbonated sugar-sweetened beverages (CSSB) intake has been increasingly linked to metabolic diseases. To investigate the association between CSSB intake and metabolic syndrome (MetS) risk, and the interaction between genetic predisposition to CSSB intake and dietary patterns.

Authors

Sunmin Park

Department of Bioconvergence, Hoseo University, Asan 31499, Korea.
Da Sol Kim

Dept. of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, Asan, South Korea.
Suna Kang

Dept. of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, Asan, South Korea.

Keywords

Adult Carbonated Beverages Cohort Studies Diet Feeding Behavior Female Gene-Environment Interaction Genetic Predisposition to Disease Genome-Wide Association Study Humans Machine Learning Male Metabolic Syndrome Middle Aged Polymorphism, Single Nucleotide Risk Factors Sugar-Sweetened Beverages

External Resources

View on PubMed Access via DOI PubMed (39396701)

Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals