Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, Beijing, China, 100191.
J Affect Disord. 2022 Aug 1;310:1-9. doi: 10.1016/j.jad.2022.04.136. Epub 2022 May 2.
Evidence about associations of pollutants with sleep is limited, and most of studies focused on individual sleep behaviors, neglecting their interrelation. We aimed to assess the relationship between ambient air pollution and road traffic noise with overall sleep health.
The study included 378,223 participants from the UK Biobank. Including five sleep behaviors (chronotype, sleep duration, insomnia, snoring, and daytime sleepiness) to construct overall sleep pattern. Ambient air pollution exposure was estimated using Land Use Regression model. Road traffic noise exposure was estimated using a simplified version of the Common Noise Assessment Methods model. Using multinomial and binary logistic regression models to identify the associations between pollutants with overall and individual sleep behaviors, respectively.
Participants were derived in three sleep patterns: healthy (n = 140,490), intermediate (n = 220,627), and poor (n = 17,106). After adjustment for potential confounders, compared with the lowest quartile of PM, the highest quartile had higher odds of intermediate and poor compared to healthy sleep pattern [OR (95% CI) for poor: 1.28 (1.21-1.36); for intermediate: 1.11 (1.09-1.14)]. We observed similar relationships for PM, PM, PM, NO, and NO. In unadjusted model, compared with low exposure of L, high L exposure had higher odds of intermediate and poor compared to healthy sleep pattern [OR (95% CI) for poor: 1.13 (1.06-1.20); for intermediate: 1.03 (1.00-1.06)]. However, such associations disappeared after further adjustment for potential confounders.
Long-term ambient air pollution is associated with overall sleep health. Road traffic noise itself is weakly associated with overall sleep health.
有关污染物与睡眠之间关联的证据有限，且大多数研究都集中在个体睡眠行为上，而忽略了它们之间的相互关系。我们旨在评估环境空气污染和道路交通噪声与整体睡眠健康之间的关系。
该研究纳入了来自英国生物库的 378223 名参与者。通过包含五种睡眠行为（睡眠类型、睡眠时间、失眠、打鼾和白天嗜睡）来构建整体睡眠模式。使用土地利用回归模型来估计环境空气污染暴露。使用简化版的通用噪声评估方法模型来估计道路交通噪声暴露。使用多项和二项逻辑回归模型分别识别污染物与整体和个体睡眠行为之间的关联。
参与者分为三种睡眠模式：健康（n=140490）、中等（n=220627）和较差（n=17106）。在调整潜在混杂因素后，与 PM 最低四分位数相比，PM 最高四分位数与中等和较差睡眠模式的关联更高[较差睡眠模式的比值比（95%可信区间）：1.28（1.21-1.36）；中等睡眠模式：1.11（1.09-1.14）]。我们观察到 PM、PM、PM、NO 和 NO 也存在类似的关系。在未调整模型中，与低 L 暴露相比，高 L 暴露与健康睡眠模式相比，中等和较差睡眠模式的关联更高[较差睡眠模式的比值比（95%可信区间）：1.13（1.06-1.20）；中等睡眠模式：1.03（1.00-1.06）]。然而，在进一步调整潜在混杂因素后，这些关联消失了。
长期环境空气污染与整体睡眠健康有关。道路交通噪声本身与整体睡眠健康的关联较弱。
