Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.
Journal:
The journal of nursing research : JNR
PMID:
40162697
Abstract
BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysregulation, including obesity, elevated blood glucose levels, dyslipidemia and hypertension. Using an approach to early prediction of MetS risk in hospital employees that takes into account the differing effects of gender may be expected to improve cardiovascular disease-related health outcomes.