advances in LC-MS have enabled broad profiling of urinary N-glycopeptides, yet normal demographic variation remains insufficiently defined. This gap complicates biomarker studies, as physiological differences can be mistaken for disease signals. This study aimed to characterize age and sex effects on intact urinary N-glycopeptides in healthy adults and construct a demographic reference resource suitable for biomarker development. Methods: Urinary N-glycopeptides from 108 healthy adults (aged 20 to 60 years) were profiled using a standardized LC MS workflow following hydrophilic interaction liquid chromatography enrichment. Intact N glycopeptides were quantified at the protein, site, glycan, and peptide levels. Covariate-adjusted principal component analysis and change point detection were applied to characterize demographic structure. Glycopeptides not associated with age or sex were identified and used to construct a demographic reference set with defined quantitative ranges.