Association Between the Nutritional Inflammatory Index and Obstructive Sleep Apnea Risk: Insights from the NHANES 2015–2020 and Mendelian Randomization Analyses DOI Open Access
M. C. Lin,

KaiweiSa Abuduxukuer,

L. Ye

и другие.

Healthcare, Год журнала: 2025, Номер 13(7), С. 783 - 783

Опубликована: Апрель 1, 2025

Background/Objectives: Current approaches to monitoring obstructive sleep apnea (OSA) risk primarily focus on structural or functional abnormalities, often neglecting systemic metabolic and physiological factors. Resource-intensive methods, such as polysomnography (PSG), limit their routine applicability. This study aimed evaluate composite nutritional-inflammatory indices derived from blood markers identify feasible for OSA management explore association with risk. Methods: Data 9622 adults in the NHANES (2015-2020) GWAS datasets were analyzed using logistic regression, restricted cubic splines, machine learning, Mendelian randomization (MR). These techniques employed associated Random forest modeling identified body mass index (BMI) albumin (ALB) key components of advanced lung cancer inflammation (ALI). Causal relationships between ALI validated MR. Results: was significantly OSA, individuals highest tertile exhibiting a 59% higher likelihood (OR = 1.59, 95% CI: 1.38-1.84; p < 0.001). BMI ALB contributors confirmed causal factors (BMI: OR 1.91, 1.80-2.02; ALB: 1.11, 1.04-1.19). Age, gender, neutrophil-to-lymphocyte ratio (NLR) also significant predictors. Conclusions: identifies potential assessing Integrating statistical modeling, inference highlights utility improving clinical practice.

Язык: Английский

Association Between the Nutritional Inflammatory Index and Obstructive Sleep Apnea Risk: Insights from the NHANES 2015–2020 and Mendelian Randomization Analyses DOI Open Access
M. C. Lin,

KaiweiSa Abuduxukuer,

L. Ye

и другие.

Healthcare, Год журнала: 2025, Номер 13(7), С. 783 - 783

Опубликована: Апрель 1, 2025

Background/Objectives: Current approaches to monitoring obstructive sleep apnea (OSA) risk primarily focus on structural or functional abnormalities, often neglecting systemic metabolic and physiological factors. Resource-intensive methods, such as polysomnography (PSG), limit their routine applicability. This study aimed evaluate composite nutritional-inflammatory indices derived from blood markers identify feasible for OSA management explore association with risk. Methods: Data 9622 adults in the NHANES (2015-2020) GWAS datasets were analyzed using logistic regression, restricted cubic splines, machine learning, Mendelian randomization (MR). These techniques employed associated Random forest modeling identified body mass index (BMI) albumin (ALB) key components of advanced lung cancer inflammation (ALI). Causal relationships between ALI validated MR. Results: was significantly OSA, individuals highest tertile exhibiting a 59% higher likelihood (OR = 1.59, 95% CI: 1.38-1.84; p < 0.001). BMI ALB contributors confirmed causal factors (BMI: OR 1.91, 1.80-2.02; ALB: 1.11, 1.04-1.19). Age, gender, neutrophil-to-lymphocyte ratio (NLR) also significant predictors. Conclusions: identifies potential assessing Integrating statistical modeling, inference highlights utility improving clinical practice.

Язык: Английский

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