Association Between the Weight-Adjusted Waist Index and OSA Risk: Insights from the NHANES 2017-2020 and Mendelian Randomization Analyses.

IF 3 2区医学 Q2 CLINICAL NEUROLOGY Nature and Science of Sleep Pub Date : 2024-11-19 eCollection Date: 2024-01-01 DOI:10.2147/NSS.S489433

HanYu Wang, BoWen Yang, XiaoYu Zeng, ShiPeng Zhang, Yanjie Jiang, Lu Wang, Chao Liao

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Abstract

Background: 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.

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体重调整后腰围指数与 OSA 风险之间的关系：NHANES 2017-2020 和孟德尔随机分析的启示。

背景：肥胖是阻塞性睡眠呼吸暂停（OSA）的重要风险因素。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：本次横断面调查使用的数据来自 2017 年至 2020 年间开展的美国国家健康与营养调查（NHANES）。我们利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，我们还采用了多种分析方法，包括亚组分析、平滑曲线拟合、阈值效应分析和接收者操作特征曲线（ROC）。为了进一步探究两者之间的关系，我们利用全基因组关联研究（GWAS）的汇总统计进行了一项 MR 研究。我们采用了主要的逆方差加权（IVW）方法和其他辅助的 MR 方法。此外，我们还进行了荟萃分析，以提供总体评价：经全面调整后，WWI 与 OSA 呈正相关[几率比（OR）=1.14，95% 置信区间（95% CI）：1.06-1.23，PP=0.01]。分组分析显示，WWI 与 OSA 之间的独立正相关关系具有稳定性。平滑曲线拟合确定了 WWI 与 OSA 的饱和效应，拐点为 11.62。此外，WWI 对 OSA 的预测能力最强（AUC=0.745）。敏感性分析证实，WWI 与更严格的 OSA 之间存在显著的正相关（OR=1.18，95% CI：1.05-1.32，P=0.005）。磁共振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=0.005）：WWI与发生OSA的风险明显相关，表明WWI有可能成为OSA的预测因子。

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来源期刊

Nature and Science of Sleep Neuroscience-Behavioral Neuroscience

CiteScore

5.70

自引率

5.90%

发文量

245

审稿时长

16 weeks

期刊介绍： Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep. Specific topics covered in the journal include: The functions of sleep in humans and other animals Physiological and neurophysiological changes with sleep The genetics of sleep and sleep differences The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness Sleep changes with development and with age Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause) The science and nature of dreams Sleep disorders Impact of sleep and sleep disorders on health, daytime function and quality of life Sleep problems secondary to clinical disorders Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health) The microbiome and sleep Chronotherapy Impact of circadian rhythms on sleep, physiology, cognition and health Mechanisms controlling circadian rhythms, centrally and peripherally Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms Epigenetic markers of sleep or circadian disruption.