Relationships of sleep traits with prostate cancer risk: A prospective study of 213,999 UK Biobank participants

危险系数 医学 置信区间 午睡 前瞻性队列研究 比例危险模型 队列 失眠症 早晨 队列研究 前列腺癌 内科学 生命银行 计时型 混淆 插补(统计学) 心理学 癌症 精神科 生物信息学 缺少数据 统计 生物 神经科学 数学
作者
Xiaoyan Lv,Yuxin Li,Rong Li,Xiangyun Guan,Li Li,Junli Li,Shucheng Si,Xiaokang Ji,Yingjuan Cao,Fuzhong Xue
出处
期刊:The Prostate [Wiley]
卷期号:82 (9): 984-992 被引量:8
标识
DOI:10.1002/pros.24345
摘要

Abstract Background The effect of sleep on the occurrence of prostate cancer (PCa) remains unclear. This study explored the influence of sleep traits on the incidence of PCa using a UK Biobank cohort study. Methods In this prospective cohort study, 213,999 individuals free of PCa at recruitment from UK Biobank were included. Missing data were imputed using multiple imputation by chained equations. Cox proportional hazards models were used to calculate the adjusted hazard ratios and 95% confidence intervals for PCa (6747 incident cases) across seven sleep traits (sleep duration, chronotype, insomnia, snoring, nap, difficulty to get up in the morning, and daytime sleepiness). In addition, we newly created a healthy sleep quality score according to sleep traits to assess the impact of the overall status of night and daytime sleep on PCa development. E values were used to assess unmeasured confounding. Results We identified 6747 incident cases, of which 344 died from PCa. Participants who usually suffered from insomnia had a higher risk of PCa (hazard ratio [HR]: 1.11; 95% confidence interval [CI]: 1.04–1.19, E value: 1.46). Finding it fairly easy to get up in the morning was also positively associated with PCa (HR: 1.09; 95% CI: 1.04–1.15, E value: 1.40). Usually having a nap was associated with a lower risk of PCa (HR: 0.91; 95% CI: 0.83–0.99, E value: 1.42). Conclusions Fairly easy to get up in the morning and usually experiencing insomnia were associated with an increased incidence of PCa. Moreover, usually having a nap was associated with a lower risk of PCa. Therefore, sleep behaviors are modifiable risk factors that may have a potential impact on PCa risk.
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