# Association between sleep apnea-specific novel hypoxic metrics and disturbances in glucose and lipid metabolism

## TL;DR

This study finds that new hypoxia metrics in sleep apnea are strongly linked to glucose and lipid metabolism issues, suggesting they could predict metabolic problems.

## Contribution

The study introduces novel hypoxic metrics (pRED_3p and SBII) and shows their independent associations with metabolic dysregulation in OSA.

## Key findings

- pRED_3p and SBII are significantly associated with multiple glucose and lipid parameters, including fasting blood glucose and triglycerides.
- Higher quartiles of pRED_3p and SBII correspond to increased odds ratios for metabolic disturbances like hyperinsulinemia and elevated LDL-C.
- The novel hypoxic metrics show consistent linear trends with worsening glucose and lipid metabolism as OSA severity increases.

## Abstract

Obstructive sleep apnea (OSA) has been linked to disturbances in glucose and lipid metabolism. The independent association between sleep apnea–specific novel hypoxic metrics and metabolic dysregulation in OSA, however, remains unclear.

Anthropometric and polysomnographic data were obtained from OSA patients treated. Novel hypoxic indices—percentage of sleep time with the duration of respiratory events causing desaturation (pRED_3p) and sleep breathing impairment index (SBII)—were derived from the SpO2 channel. Biochemical parameters were simultaneously assessed. Multiple linear regression models were applied to examine independent associations of pRED_3p, SBII, and apnea–hypopnea index (AHI) with glucose and lipid profiles. Logistic regression was further performed to estimate odds ratios (ORs) for abnormal glucose and lipid parameters across quartiles of pRED_3p, SBII, and AHI.

After controlling for confounding variables, pRED_3p demonstrated significant associations with fasting blood glucose (FBG) (β=0.122), fasting insulin (FIN) (β=0.410), HOMA-IR (β=0.325), total cholesterol (TC) (β=0.309), triglycerides (TG) (β=0.173), low-density lipoprotein cholesterol (LDL-C) (β=0.260), TC/HDL-C (β=0.182), TG/HDL-C (β=0.121), LDL-C/HDL-C (β=0.195), AI (β=0.182), LCI (β=0.663), visceral adiposity index (VAI) (β=0.115), and lipid accumulation product (LAP) (β=0.139). SBII was independently related to FBG (β=0.079), FIN (β=0.240), HOMA-IR (β=0.191), TC (β=0.179), TG (β=0.115), LDL-C (β=0.139), LDL-C/HDL-C (β=0.081), LCI (β=0.093), and LAP (β=0.098), all with p<0.05. In quartile-based comparisons, higher pRED_3p categories corresponded to progressively increased ORs for elevated FBG (2.372, 4.054, and 4.131), hyperinsulinemia (5.789, 22.644, and 26.188), high HOMA-IR (6.655, 36.637, and 43.807), hypercholesterolemia (2.751, 7.109, and 9.607), hypertriglyceridemia (1.976, 4.248, and 4.412), and elevated LDL-C (3.593, 8.050, and 12.048). Similarly, higher SBII quartiles were associated with increased ORs for elevated FBG (1.863, 3.819, and 3.874), hyperinsulinemia (5.002, 25.085, and 25.942), high HOMA-IR (5.879, 35.603, and 51.799), hypercholesterolemia (3.074, 7.297, and 8.867), hypertriglyceridemia (1.963, 4.101, and 4.757), and elevated LDL-C (3.627, 7.684, and 11.515). All linear trends were positive (p<0.001).

pRED_3p and SBII were associated not only with established glucose and lipid metabolism parameters—including elevated FBG, FIN, HOMA-IR, hypercholesterolemia, hypertriglyceridemia, and elevated LDL-C—but also with composite lipid indices, exhibiting consistent linear trends. Greater OSA severity corresponded to more marked disturbances in glucose and lipid metabolism. These novel hypoxic metrics may serve as predictive indicators for metabolic dysregulation in OSA.