Association between sleep quality and urolithiasis among general population in Western China: a cross-sectional study

The current research was a cross-sectional analysis based on the data of the West China Natural Population Cohort Study (WCNPCS) obtained between May 2019 and June 2021. The data was collected from the three most populous regions of Sichuan Province (Mianzhu, Longquan, and Pidu) in Western China. The WCNPCS cohort was established in 2019–2021 with a total of 36,075 participants from West China. The WCNPCS cohort was established in 2019–2021 with a total of 36,075 participants from West China. The subjects of WCNPCS are selected from the permanent adult residents of the cooperative community by sequential cluster sampling. The trained full-time staff will carry out face-to-face questionnaire survey, physical examination, biological sample collection and special examination. WCNPCS aims to establish a large-scale forward-looking natural population cohort.

Participants were recruited into the present study on a voluntary basis. Each of them obtained and signed an informed consent before the survey was undertaken. Face-to-face interviews and collection of bio-specimens including serum and urine was conducted by trained medical staff. The specimens were analyzed in the medical laboratory according to the standard experimental procedures (Fig. 1).

A questionnaire survey of 36,075 people was conducted and those without complete information of PSQI (1102 participants) or kidney stones (536 participants) were finally excluded from this study. Therefore, a total of 34,437 participants were lastly included in the study.

All the applied study protocols were in accordance with the Declaration of Helsinki of 1975 with applicable revisions at the time of the present investigation. Approval of the used study protocols was provided by the ethical committee of West China Hospital of Sichuan University and the study was registered with the Chinese Clinical Trial Registry (registration No. ChiCTR1900024623) on July 19, 2019.

Translated PSQI was used to assess the sleep quality. The PSQI is a standard self-reporting questionnaire consisting of 19 items designed to collect the subjective nature of a person’s sleep habits within a month [15]. The PSQI quadruple scale for each entry ranges from 0 to 3. Furthermore, PSQI has been used in several cases to diagnose sleep disorders and proved to have good reliability and validity [16‐18].

The translated PSQI assesses different aspects of sleep and reflects seven aspects of sleep problems. The aspects include subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction [15]. The sum of the assessed sleep aspects constitutes a global sleep quality score ranging from 0 to 21 and the higher the score, the lower the sleep quality.

The global PSQI score is higher than 7 and hence can distinguish between people with poor sleep quality and those who sleep well. In Chinese population, the score has high diagnostic sensitivity and specificity of 98.3 and 90.2%, respectively [19].

In WCNPCS study, survey participants who answered yes to the question, “Have you ever had a kidney stone?” were considered to have a history of urolithiasis. Potential covariates were identified a priori based on literature review. Continuous variables included in the present study consisted of age, BMI, waist to hip ratio (WHR), Patient Health Questionnaire-9 (PHQ9) score, Generalized Anxiety Disorder (GAD-7) score, and Serum creatinine (Cr).

On the other hand, categorical variables included in this study were: gender (male/female), marital status, education, smoking history, alcohol intake, coffee intake, and tea intake. Smoking is defined as smoking more than 100 cigarettes in a lifetime and drinking is defined as more than 30 g per week in the last 12 months. This definition has been verified in some previous studies [20]. Comorbid conditions of the current study included 1) Diabetes mellitus (DM), 2) congestive heart failure, 3) chronic obstructive pulmonary disease (emphysema and/or chronic bronchitis), 4) coronary artery disease, 5) cancer, and6) hypertension. The total number the reported conditions of the participants, in exception of diabetes, which was separately assessed, was later combined to create an ordinal comorbidity index [21].

The assessed characteristics of the participants were described as mean ± standard deviations (mean ± SD), median (interquartile range) or percentage counts. Chi-square analyses were used to examine the differences of the characteristics among the participants with or without a history of urolithiasis. Multivariable logistic regression analyses were utilized to examine the odds ratios (ORs) and 95% confidence intervals (CIs) for the risk factors of urolithiasis. Urolithiasis status was used as a dependent variable, whereas the sleep quality (Global PSQI score ≤ 7 or > 7) and the seven components of the PSQI (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction) were used as independent variables.

The ORs and 95% CIs were calculated whereby ORs were adjusted for age in a minimally-adjusted model (Model 1). The ORs were further adjusted for age, BMI, education, marital status, Smoking, drinking, coffee, tea, WHR, PHQ9, GAD7, comorbidity index, DM, physical activity, and Cr in a fully-adjusted model (Model 2). Subgroup analyses were performed and stratified by gender. As metabolic syndrome has a certain influence on the occurrence of stones, we also carried out a corresponding stratified analysis of metabolic syndrome. The P values for interaction were tested using the likelihood ratio test. 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 for described statistical analyses. Statistical significant difference was set at P-value < 0.05.

A total of 34,437 participants who meet the inclusion and exclusion criteria were recruited into this study. The various characteristics of the participant are as presented in Table 1 according to urolithiasis history. The average age of the participants with no renal stones was 56.155 ± 12.156 years (SD). The average age of participants with renal stones was 56.156 ± 10.954 years (SD), and 12.2% of the participants were found with urolithiasis.

To explore the association of sleep quality with urolithiasis, it was observed that the total PSQI scores of the participants with a history of urolithiasis were significantly higher than those without the history. Results of the current study showed that the risk of urolithiasis was significantly increased with an elevated component PSQI score in sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance and daytime dysfunction. In addition, it was found that there was the decrease in component PSQI score in the subjective sleep quality (P < 0.05; Table 2). Results of logistic regression analyses on the associations between the PSQI scores and the prevalence of urolithiasis in participants of the present study were as shown in Table 3. Results from the crude model showed that the prevalence of urolithiasis was positively associated with the PSQI scores. Further, the total PSQI scores were still observed to have a significant positive correlation with the prevalence of urolithiasis after adjustments were made for the confounding variables (OR: 1.178; 95% (CI) = 1.083–1.282; p < 0.001). In detail, as shown in Table 3, the risk of urolithiasis was significantly increased with the elevated component PSQI score in Sleep latency (OR: 1.217; 95% (CI) =1.082–1.368; P < 0.01), Sleep duration (OR: 1.219; 95% (CI) =1.056–1.408; P < 0.01), Habitual sleep efficiency (OR: 1.181; 95% (CI) =1.066–1.309; P < 0.01) and Daytime dysfunction (OR: 1.446; 95% (CI) =1.186–1.763; P < 0.001).

The outcomes of subgroup analyses which explored the relationship between PSQI score and urolithiasis stratified by metabolic syndrome of the participants were as shown in Supplementary Tables 2&3. the relationship between sleep and urolithiasis in this population (OR: 1.181; 95% CI: 0.964–1.448; P = 0.10804) is not as significant as that in non-metabolic syndrome participants (OR: 1.174; 95% CI: 1.069–1.288; P < 0.001). The outcomes of subgroup analyses which explored the relationship between PSQI score and urolithiasis stratified by gender of the participants were as shown in Table 4. It was found that there was a higher correlation between PSQI score and urolithiasis among female participants (OR: 1.043; 95% CI: 1.027–1.059; P < 0.001) as compared with that of male participants (OR: 1.029; 95% CI: 1.010–1.049; P = 0.0034). Moreover, it was observed that there was a significant interaction between sleep quality and gender (P for interaction = 0.0354).