Association Between the Weight-Adjusted Waist Index and OSA Risk: Insights from the NHANES 2017–2020 and Mendelian Randomization Analyses - Wang H; Yang B; Zeng X; Zhang S; Jiang Y; Wang L; Liao C (Nature and Science of Sleep)
HanYu Wang,1,* BoWen Yang,2,* XiaoYu Zeng,1,* ShiPeng Zhang,1 Yanjie Jiang,3 Lu Wang,1 Chao Liao1,4 1Clinical Medical College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of China; 2Dongguan Hospital, Guangzhou University of Chinese Medicine, Dongguan, Guangdong, People’s Republic of China; 3Department of Neurology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 4Department of Otorhinolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chao Liao, Department of Otorhinolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, No. 37 on the Street of Shi Er Bridge, City Chengdu, Province Sichuan, People’s Republic of China, Email lc_cdutcm@163.comBackground: Obesity is a significant risk factor for obstructive sleep apnea (OSA). The weight-adjusted-waist index (WWI) reflects weight-independent centripetal obesity. Our study aims to evaluate the relationship between WWI and OSA.Methods: The data used in the current cross-sectional investigation are from the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2017 and 2020. We utilized weighted multivariable-adjusted logistic regression to evaluate the relationship between WWI and the risk of OSA. In addition, we applied various analytical methods, including subgroup analysis, smoothing curve fitting, threshold effect analysis and the receiver operating characteristic (ROC) curve. To further explore the relationship, we conducted a MR study using genome-wide association study (GWAS) summary statistics. We performed the main inverse variance weighting (IVW) method along with other supplementary MR methods. In addition, a meta-analysis was conducted to provide an overall evaluation.Results: WWI was positively related to OSA with the full adjustment [odds ratio (OR)=1.14, 95% confidence interval (95% CI): 1.06– 1.23, P< 0.001]. After converting WWI to a categorical variable by quartiles (Q1-Q4), compared to Q1 the highest WWI quartile was linked to an obviously increased likelihood of OSA (OR=1.26, 95% CI: 1.06– 1.50. P=0.01). Subgroup analysis revealed the stability of the independent positive relationship between WWI and OSA. Smoothing curve fitting identified a saturation effect of WWI and OSA, with an inflection point of 11.62. In addition, WWI had the strongest prediction for OSA (AUC=0.745). Sensitivity analysis was performed to verify the significantly positive connection between WWI and stricter OSA (OR=1.18, 95% CI: 1.05– 1.32, P=0.005). MR meta-analysis further supported our results (OR=2.11, 95% CI: 1.94– 2.30, P< 0.001). Sensitivity analysis confirmed the robustness and reliability of these findings.Conclusion: WWI was significantly associated with the risk of OSA, suggesting that WWI could potentially serve as a predictor for OSA.Keywords: weight-adjusted waist circumference index, WWI, obstructive sleep apnea, OSA, National Health and Nutrition Examination Survey, NHANES, Mendelian randomization analysis, cross-sectional study