Wang HanYu, Yang BoWen, Zeng XiaoYu, Zhang ShiPeng, Jiang Yanjie, Wang Lu, Liao Chao
Clinical Medical College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Dongguan Hospital, Guangzhou University of Chinese Medicine, Dongguan, Guangdong, People's Republic of China.
Nat Sci Sleep. 2024 Nov 19;16:1779-1795. doi: 10.2147/NSS.S489433. eCollection 2024.
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.
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.
WWI was positively related to OSA with the full adjustment [odds ratio (OR)=1.14, 95% confidence interval (95% CI): 1.06-1.23, <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. =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, =0.005). MR meta-analysis further supported our results (OR=2.11, 95% CI: 1.94-2.30, <0.001). Sensitivity analysis confirmed the robustness and reliability of these findings.
WWI was significantly associated with the risk of OSA, suggesting that WWI could potentially serve as a predictor for OSA.
肥胖是阻塞性睡眠呼吸暂停（OSA）的一个重要风险因素。体重调整腰围指数（WWI）反映了与体重无关的向心性肥胖。我们的研究旨在评估WWI与OSA之间的关系。
当前横断面调查中使用的数据来自2017年至2020年进行的美国国家健康与营养检查调查（NHANES）。我们使用加权多变量调整逻辑回归来评估WWI与OSA风险之间的关系。此外，我们应用了各种分析方法，包括亚组分析、平滑曲线拟合、阈值效应分析和受试者工作特征（ROC）曲线。为了进一步探索这种关系，我们使用全基因组关联研究（GWAS）汇总统计数据进行了孟德尔随机化（MR）研究。我们采用了主要的逆方差加权（IVW）方法以及其他补充MR方法。此外，还进行了荟萃分析以提供总体评估。
在完全调整后，WWI与OSA呈正相关[比值比（OR）=1.14，95%置信区间（95%CI）：1.06 - 1.23，P<0.001]。通过四分位数（Q1 - Q4）将WWI转换为分类变量后，与Q1相比，WWI最高的四分位数与OSA的可能性明显增加相关（OR = 1.26，95%CI：1.06 - 1.50，P = 0.01）。亚组分析揭示了WWI与OSA之间独立正相关关系的稳定性。平滑曲线拟合确定了WWI与OSA之间的饱和效应，拐点为11.62。此外，WWI对OSA具有最强的预测能力（曲线下面积[AUC]=0.74)。进行敏感性分析以验证WWI与更严重OSA之间的显著正相关（OR = 1.18，95%CI：1.05 - 1.32，P = 0.005）。MR荟萃分析进一步支持了我们的结果（OR = 2.11，95%CI：1.94 - 2.30，P<0.001）。敏感性分析证实了这些发现的稳健性和可靠性。
WWI与OSA风险显著相关，表明WWI可能潜在地作为OSA的一个预测指标。
