Study population
The current research is a cross-sectional analysis based on the data of the West China Natural Population Cohort Study (WCNPCS) collected from May 2019 to June 2021. The data was collected from three regions of Sichuan Province, the most populous province in Western China, including Mianzhu, Longquan, and Pidu. This study aim to establish a large-scale prospective follow-up natural population cohort and collect various information of community participants in order to evaluate the health status of the general population in Western China.
A total of 36,075 participants aged 18 to 65 were included in this study. Participants were further excluded for lack of sleep quality and LUTS/BPH disease information (n = 1,102) and sleep quality score data (n = 23,149). Our final analysis sample was 11,824 participants (Fig. 1). Specific general information (e.g., demographics, social-economic, education level and physical activities) was obtained through face-to-face interviews. Participants were further recruited for physical examination to collect biological samples, which were conducted by trained medical personnel in specially equipped mobile examination centers (MECs). Participants were recruited on a voluntary basis, and each participant signed and obtained informed consent before the survey. All research protocols were in accordance with the 1975 Helsinki Declaration and the applicable amendments at the time of the survey. The study protocol was approved by the ethics committee of West China Hospital of Sichuan University. The study was registered in China Clinical Trial Registration Center (Registration No. ChiCTR1900024623, 2019/07/19).
Measurement Of Sleep Quality
A PSQI questionnaire translated into Chinese was used to evaluate sleep quality. It is a standard self-report, including a 19-item questionnaire designed to collect a person's subjective feelings about sleep habits for more than one month [14]. Each item is divided into four levels, with scores ranging from 0 to 3. PSQI has been used to diagnose sleep disorders in many clinical applications and has been proved to have good reliability, validity and sensibility [15, 16]. It estimates several different aspects of sleep, which affect seven aspects of sleep problems, including subjective sleep quality, sleep latency, sleep duration, habitual sleep frequency, sleep disorders, use of sleep drugs and daytime dysfunction [14]. The sum constitutes the global sleep quality score (ranging from 0 to 21), and the higher score mean the worse sleep quality. The global PSQI score is divided by 7 points, which can distinguish poor or good sleep. It has high diagnostic sensitivity and specificity in Chinese population (98.3% and 90.2% respectively) [7].
Measurement Of Luts/bph
In addition, males were asked, “Have you ever been diagnosed with prostate hyperplasia?” Related symptoms of prostatic hyperplasia, including difficulty urinating, increased nocturia, urinary incontinence, were explained to all the participants. In WCNPCS study, symptoms were mainly assessed based on participant self-report, which was also commonly used in previous studies [17–19].
Covariates
Information about sociodemographic characteristics and lifestyle factors was collected through questionnaire survey. For continuous covariates including age (year), body mass index (BMI, kg / m2), waist-to-hip ratio (WHR), the patient health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7) and creatinine (Crµmol/L). For categorical covariates including education level (primary school, junior school, high school college or graduate), marital status (married, unmarried, divorced or widowed), smoking status (current, occasionally, ever or never), drinking status (yes, ever or no), coffee and tea intake (1–2 times/week, 3–5 times/week or > 5 times/week), comorbidity index, diabetes mellitus (DM) (yes, prediabetes or no) and physical activity (suffcient, not suffcient or inactive). Diabetes mellitus, congestive heart failure, coronary artery disease, chronic obstructive pulmonary disease (chronic bronchitis and/or emphysema) and hypertension, cancer consisted of comorbid conditions. The number of subjects reported conditions were then combined to generate an ordinal comorbidity index. Exclusive diabetes was excluded and the total number of reported diseases was merged to create a sequential comorbidity index [20]. Individuals with a PHQ-9 score ≥ 10 are considered to have depressive symptoms [21]. Calculate the average intake of coffee or tea in the dietary interview in a week to indicate the intake of caffeine (times / week, classification).
Statistical analysis
Chi-square analysis was used to assess characteristic differences between participants with or without a history of LUTS/BPH. The current study showed that men with sleep disorders are more likely to report daytime LUTS [20]. In order to make the results more reliable and exclude the direct impact of daytime LUTS on sleep, we also made a regression analysis between sleep disorders and daytime LUTS as continuous variables and categorical variables, respectively. Multivariate logistic regression analysis was used to examine the odds ratio (or) and 95% confidence interval (CI) of the risk of LUTS/BPH. The independent variable in this study is the presence or absence of LUTS/BPH status, and sleep quality (PSQI global score ≤ 7 or > 7) and seven components of PSQI were used as independent variables. ORs and 95% CI were calculated. Meanwhile, we regard the PSQI global score as a continuous variable and conduct multiple logistic regression again as a sensitivity analysis. The ORs were adjusted for age in the minimum adjustment model (Model I). In the fully-adjusted model (Model II), the ORs is adjusted for age, BMI, educational level, marital status, smoking status, drinking status, coffee intake, tea intake, WHR, PHQ-9, GAD-7, comorbidity index, DM, physical activity and Cr. Subgroup analysis was stratified by age. The statistical software packages R (http://www.R-project.org, The R Foundation) and EmpowerStats (http://www.empowerstats.com, X&Y Solutions, Inc., Boston, MA) were used in the above statistical analyses. A p-value < 0.05 was considered statistically significant.