使用結構方程模型探討男性過夜班輪班工作與蛋白尿之關聯

中文摘要研究目的：雖然動物實驗已證實生理時鐘的干擾與腎臟損傷相關，但針對人類過夜班輪班工作者與腎臟病變之間關聯性的研究仍屬有限。因此，本研究旨在探討過夜班輪班工作是否與蛋白尿的發生有關，而蛋白尿為慢性腎臟病的早期指標之一。研究方法及資料：本研究為橫斷式社區型隊列研究，共招募451名男性參與者（平均年齡46.2±7.4歲），其中226名為過夜班輪班工作者，另225名為非過夜班工作的對照組。所有受試者均接受全面健康評估，包括身體測量（如身高、體重、腰圍與臀圍）、血壓監測、實驗室檢驗（涵蓋心臟代謝指標、肝腎功能、糖化血色素與胰島素阻抗）、尿液試紙檢測蛋白尿、整夜睡眠多項生理功能檢查、心肺耐力測試及肺功能檢查。在統計分析方面，首先以多變項逐步邏輯迴歸分析探索與蛋白尿相關的獨立變項。接著建構結構方程模型（structural equation model, SEM），以進一步評估Rotating Shift Work（過夜班輪班工作）對Proteinuria（蛋白尿）的直接與間接影響路徑，並納入潛在變項如Sleep-Disordered Breathing（睡眠呼吸障礙）、Obesity（肥胖）、Hypertension（高血壓）、Poor Glycemic Control（糖代謝異常）與Low Physical Fitness（低體適能）。結構方程模型經驗證性分析後，其適配度以決定係數（R²）進行評估，並報告各變項與Proteinuria的標準化總效應（β值）及其統計顯著性。研究結果：多變項逐步邏輯回歸分析顯示，蛋白尿與白日（睡眠後）舒張壓、胰島素阻抗（胰島素阻抗指數 [homeostatic model assessment -insulin resistance, HOMA-IR]）及低體適能（反向最大攝氧量, reversed VO2max）之間具有直接相關性。結構方程模型進一步揭示，Rotating Shift Work與Proteinuria之間存在間接關聯，透過Sleep-Disordered Breathing（呼吸中止-低通氣指數 [apnea-hypopnea index, AHI]、氧氣飽和度下降）、Obesity（身體質量指數 [body mass index, BMI]、腰臀比 [waist-hip ratio, WHR] ）、Hypertension、Poor Glycemic Control（糖化血色素 [glycated hemoglobin, HbA1c]、HOMA-IR）及Low Physical Fitness（reversed VO2max）等因素發揮作用。驗證性SEM模型（R²= 0.91）顯示，Proteinuria的直接影響因素為Hypertension、Poor Glycemic Control及Low Physical Fitness（β= 0.105~0.145，所有p值<0.05），而Rotating Shift Work（β=0.1）、Sleep-Disordered Breathing（β=0.03）及Obesity（β=0.115）則通過這些因素間接影響Proteinuria的發生。結論與建議：本研究透過三層式SEM呈現出晝夜節律紊亂對腎臟健康的潛在威脅，並指出其可能透過一系列交織的生理機轉影響腎功能。此結果為過夜班輪班工作者之腎臟疾病風險提供了重要參考依據，並強調應關注此族群的健康管理與早期介入策略。

AbstractBackground:Although animal studies have demonstrated a link between circadian rhythm disruption and renal injury, research on the association between shift work and kidney disease in humans remains limited. This study aimed to investigate whether overnight rotating shift work is associated with proteinuria, an early marker of chronic kidney disease (CKD).Methods:This cross-sectional, community-based cohort study recruited 451 male participants (mean age: 46.2 ± 7.4 years), including 226 overnight rotating shift workers and 225 non-overnight shift workers as controls. All participants underwent comprehensive health assessments, including anthropometric measurements (e.g., height, weight, waist and hip circumference), blood pressure monitoring, laboratory tests (covering cardiometabolic, hepatic, and renal function markers, HbA1c, and insulin resistance index), urine dipstick analysis for proteinuria, overnight polysomnography, cardiopulmonary exercise testing, and pulmonary function testing. Statistical analysis included multivariable stepwise logistic regression to identify independent variables associated with proteinuria. Structural equation modeling (SEM) was then used to assess both direct and indirect pathways between Rotating Shift Work and Proteinuria, incorporating latent variables such as Sleep-Disordered Breathing, Obesity, Hypertension, Poor Glycemic Control, and Low Physical Fitness. Model fit was evaluated using the coefficient of determination (R²), and standardized total effects (β values) with statistical significance were reported.Results:Multivariable logistic regression analysis indicated that proteinuria was directly associated with daytime (post-sleep) diastolic blood pressure, insulin resistance (HOMA-IR), and low physical fitness (reversed VO2max). The SEM further revealed that Rotating Shift Work had an indirect association with Proteinuria, mediated by Sleep-Disordered Breathing (apnea-hypopnea index [AHI], oxygen desaturation), Obesity (body mass index [BMI], waist-hip ratio [WHR]), Hypertension, Poor Glycemic Control (HbA1c, HOMA-IR), and Low Physical Fitness (reversed VO2max). The Confirmatory SEM model showed good fit (R² = 0.91), with Hypertension, Poor Glycemic Control, and Low Physical Fitness emerging as direct predictors of Proteinuria (β = 0.105–0.145, all p < 0.05). Meanwhile, Rotating Shift Work (β = 0.1), Sleep-Disordered Breathing (β = 0.03), and Obesity (β = 0.115) exerted indirect effects through these mediators.Conclusion:This study utilized a hierarchical SEM approach to elucidate how circadian rhythm disruption may contribute to renal dysfunction via multiple interrelated physiological pathways. The findings highlight the potential renal health risks among shift workers and underscore the importance of early intervention and targeted health management for this population.