Background: Both proteinuria and obstructive sleep apnea (OSA) are associated with cardiovascular events and consequent mortality. To examine whether age, OSA, diabetes, and obesity are potential predictors of proteinuria, a data-driven analysis was performed to delineate a potential categorical classification algorithm.
Methods: In this cross-sectional community-based cohort study, demographic data, blood pressure, serum biochemical analyses, proteinuria via single dipstick urinalysis, and overnight polysomnographies were measured in 300 males with sedentary work styles.
Results: Sixty-one (20.3 %) of all these participants had proteinuria. Logistic regression analysis showed that glycated hemoglobin (HbA1c), duration of arterial oxygen saturation <90 %, age, and log high-sensitivity C-reactive protein, but not apnea-hypopnea index (AHI), were responsible for 16.7 % of the variance of proteinuria's presence. A decision tree analysis showed that subjects over 49 years old had a higher risk for proteinuria than those subjects of 49 years old, or less. In the over 49-year-old group, subjects with an AHI >21 events/h had a higher risk for proteinuria; whereas in the 49-year-old and less group, subjects with HbA1c >7 %, or with HbA1c ≤7, and body mass index (BMI) >27.4 kg/m(2) had a higher risk for proteinuria than their counterparts.
Conclusions: AHI was the major determinant responsible for the presence of proteinuria in late mid-aged male workers, while HbA1c and BMI were found in the junior subgroup. By algorithmic analysis, this study provides a comprehensive hierarchical model for better understanding of the correlates of proteinuria and sleep apnea.
Keywords: Apnea-hypopnea index; Dipstick urinalysis; Metabolic syndrome; Microalbuminuria; Sleep disordered breathing.