Associations of Snoring, Daytime Napping and Night Sleep Duration With Hyperuricemia in Rural Chinese Adults: the Henan Rural Cohort Study

Background. Evidence on the association of snoring, daytime napping or sleep duration with hyperuricemia (HUA) was limited, especially in the resources-poor areas. This study aimed to investigate the independent and joint effect of snoring frequency, daytime napping and sleep duration with prevalence of HUA in rural Chinese adults. Methods. 29,643 participants aged 18-79 years were included from baseline survey of the Henan Rural Cohort Study. Sleep variables were assessed using the Pittsburgh Sleep Quality Index (PSQI). Multivariate logistic regression and linear regression models with HUA and serum uric acid level as dependent variables were conducted, respectively. Results. Of the 29,643 included adults, 3498 suffered from HUA. Compared to never snoring, the adjusted odds ratio (OR) and 95% condence interval (CI) of HUA for rare snoring, occasional snoring and habitual snoring were 1.35 (1.17, 1.56), 1.30 (1.14, 1.47) and 1.59 (1.47, 1.73), respectively. Compared with no napping, participants who had daytime napping of 61-90 and >91 min were associated with 29% and 30% increase in prevalence of HUA, respectively. But in night sleep duration groups, no signicant associations were observed (all P>0.05). The positive associations between snoring and HUA were attenuated in older, female adults and those with chronic disease conditions. The joint of habitual snoring and longer daytime napping ( ≥ 61min) increased 63% prevalence on HUA. Conclusion. Snoring or daytime napping may independently increase the prevalence of HUA and serum uric acid (SUA) level. Moreover, habitual snoring and longer daytime napping might be jointly associated with a higher prevalence of HUA.

between snoring and HUA was rarely reported, especially in the resource-poor areas. Only a recent study evaluated the cross-sectional association between snoring and SUA concentration and HUA in China [11], but it was limited in urban adults. Meantime, a growing number of epidemiological studies also have reported that longer sleep duration and daytime napping were independently or jointly associated with an increased prevalence of hyperglycemia, hypertension and incident heart failure and stroke [12][13][14][15], but the association of napping or sleep duration with HUA remain unclear. Additionally, as a sleep disorder marker, whether snoring can confound or modify the association between napping or sleep duration and HUA remains unknown. Thus, the joint association of napping or sleep duration and snoring with HUA also needs to be elucidated.
In recent years, the prevalence of HUA is high [16], meanwhile sleep-related problems such as poor sleep quality and longer napping duration were both prevalent in Chinese rural areas [17][18]. Given these and the scarcity of related data, it is of signi cant public health in uence to explore the relationship of snoring, napping, sleep duration with HUA in rural Chinese population. Therefore, to address the data gap, this study investigated the independent and joint effect of snoring, daytime napping and night sleep duration with prevalence of HUA in rural Chinese adults.

Study population
A total of 39,259 subjects aged 18-79 years were recruited from Henan Rural Cohort Study, which was a prospective study focused on chronic non-communicable diseases. Detailed description of this cohort study design, methods, and participants recruitment have been previously published [19], and the cohort was registered in Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). In short, the study was conducted in Yuzhou, Xinxiang, Tongxu, Yima and Suiping county of Henan Province, with the baseline survey has been completed from July 2015 to October 2017. For the current analysis, after excluding participants who were missing data on SUA level (n=54), had malignant tumor and serious renal disease (n=350), and those with incomplete information about sleep data (n=9212), 29,643 adults (12,128 men and 17,515 women) were included in nal. The protocol of this study was approved by the Zhengzhou University Life Science Ethics Committee. Informed consent was obtained from all participants.

Assessment of potential covariates
The potential covariates including demographic covariates, lifestyle factors and the family history of disease were collected by well-trained staffs using a standardized questionnaire. Demographic covariates included age, gender (male or female), education level ("primary school or below" or "middle school or above"), marital status ("married/cohabitating" or "unmarried/divorced/widowed") and per capita monthly income ("<500 RMB", "500-1000 RMB" or "≥1000 RMB"). Lifestyle factors included smoking status, drinking status, physical activity and dietary pattern. Smoking status was classi ed into never, current, and former groups. Drinking status also was classi ed into never, current, and former groups.
Physical activity was divided into three levels (low, moderate and high) based on the International Physical Activity Questionnaire (IPAQ) [20]. Dietary pattern was categorized four types as previously by using a standard principal component analysis method [21], dietary pattern I with a high intake of red meat, white meat and sh; pattern II with a high intake of vegetables, staple food, and fruits; pattern III with a high intake of grains, nuts, beans, pickles and animal oils; and pattern with milk and eggs. In addition, obesity (yes/no), hypertension (yes/no), T2DM (yes/no) and dyslipidemia status (yes/no) were assessed as previous de nitions [16], family history of gout (yes/no) also was obtained.

Assessment of sleep variables
Sleep quality and related sleep variables were assessed using the Pittsburgh Sleep Quality Index (PSQI), which is a validated self-report questionnaire consisting of 19 elements to assess sleep quality and disturbances [22]. The Chinese version PSQI used by us has been widely used to assess sleep quality with good overall reliability (r=0.82-0.83) and test-retest reliability (r=0.77-0.85) [23]. For the snoring frequency, participants were asked two questions (1) Do you know, or have you ever heard that you snore? (yes or no) and (2) How often do you snore during the past month? (never, rarely snore<1 day per week, occasionally for 1-2 days per week, habitually≥3 days per week) [24]. Daytime napping was assessed by asking participants "Did you take a nap usually over the past year?" Those who answered yes were further asked to report the average daytime napping duration. Napping duration was reclassi ed into 0 min (reference), 1-30 min, 31-60 min, 61-90 min and ≥91 min [18]; in addition, self-reported night sleep duration also was determined based on answers to the questions: "On average how many hours actual sleep duration did you get at night during the past month?" Night Sleep duration was grouped as <5, 5-6, 6-7, 7-8 (reference), 8-9, 9-10, and ≥10 hours [25].
De nition of HUA Blood samples were collected from individual antecubital vein after at least 8h of overnight fasting to measure multiple biochemical indicators. SUA level was measured by ROCHE Cobas C501 automatic biochemical analyzer with enzymatic colorimetric method. De nition of HUA was determined as SUA level >417μmol/L (7.0 mg/dL) and >357μmol/L (6.0 mg/dL) for men and women, respectively [15].

Statistical analysis
All analyses were conducted using IBM SPSS V.19.0 and R 3.5.0. Descriptive statistics included one-way analyses of variance and chi-squared tests were conducted to compare the differences of baseline characteristics according to the HUA status of participants, including demographic and socio-economic characteristics, lifestyle risk factors, and sleeping variables. Multivariable logistic regression models were performed to explore the associations between sleep variables (snoring frequency, daytime napping and night sleep duration) and prevalence of HUA. Interactions were tested by adding interaction terms of these sleep variables by pairwise combination, respectively. Moreover, multivariable linear regression analyses were conducted to evaluate the relationship of these sleep variables with SUA level. Three models were constructed: model 1, age-, sex-adjusted model; model 2, adjusted for age, gender, education level, marital status, average monthly income, smoking status, drinking status, physical activity and dietary pattern; model 3, model 2 plus adjustment for snoring, daytime napping and night sleep duration where applicable.
Based on the results of logistic regression analyses, the subgroup analyses were further conducted to examine whether the signi cant associations between snoring or daytime napping (each 30min increment) and prevalence of HUA were modi ed by age, gender, obesity, hypertension, T2DM and dyslipidemia status. To test the robustness of the results, sensitivity analyses also were performed to repeat the regression analyses by gender or additionally adjusting for family history of gout, obesity, T2DM, hypertension and dyslipidemia conditions. A P-value < 0.05 was considered to be statistically signi cant.

Characteristics of study participants
Among the 29643 participants, 3498 participants (11.80%) with HUA were identi ed (Table 1). In general, compared with non-HUA, those with HUA comprised a greater proportion of men, younger individuals. Besides, participants with HUA had higher education level and per capita monthly income, were more likely to smoke and drink, lower physical activity, had higher snoring frequency and longer daytime napping duration than those without HUA (all P < 0.001). hypertension and dyslipidemia conditions did not substantially change these estimates (Additional le 1: Table S1).

Association between three sleep variables and SUA level
In Table 3, positive associations were also found between snoring frequency or daytime napping and SUA level. After adjusting multiple variables in model 3, those participants with snoring were associated with a 13.30 µmol/L higher SUA level (95% CI, 11.59, 15.01) compared with never snoring. Meantime, each 30 min increment in daytime napping was associated with a 2.87 µmol/L higher SUA level (95% CI, 2.31, 3.42). But the associations of night sleep duration with SUA level were nonsigni cant. Similarly, these results remained materially unchanged in sensitivity analyses in which the models were reassessed by gender or additionally adjusting for family history of gout, obesity, T2DM, hypertension and dyslipidemia conditions (Additional le 1: Table S2).  (Fig. 1). But for the association between napping and HUA in Fig. 2, signi cant difference can be found in most subgroups, the association was only insigni cant in participants aged < 35 (P = 0.495) and those with T2DM (P = 0.162).
Joint associations of sleep variables with HUA In Fig. 3. A and Additional le 1: Table S3, the joint analysis of snoring frequency and daytime napping in total population showed that compared with reference (never snoring and napping group), participants with combined habitually snore (≥ 3 days/week) and daytime napping ≥ 61 min had the highest prevalence of HUA (OR 1.63; 95% CI = 1.41, 1.88). Similarly, as shown in Additional le 1: Figure S1 and Table S4, further analysis strati ed by gender also found the joint associations were consistently exist in both men and women, with the corresponding highest risks were 1.66 (1.33, 2.07) and 1.61 (1.32, 1.97), respectively. But for the combined analyses of snoring frequency and night sleep duration or daytime napping and night sleep duration, no signi cant strong associations can be consistently found in total population (Fig. 3. B and C) and in men and women (Additional le 1: Table S4-8, Figure S2-3).

Discussion
In the large sample study, we observed that both snoring frequency and daytime napping were independently associated with increased prevalence of HUA and elevated SUA level. In addition, subgroup analysis showed that the positive associations between snoring and HUA were attenuated in older, female participants and those with chronic disease conditions. More importantly, a joint effect of habitual napping and longer daytime napping (≥ 61 min) increased 63% prevalence for HUA. To our knowledge, this study is the rst one exploring the independent and joint association between snoring and daytime napping with HUA in rural Chinese adults.
Some existing studies indicated that patients with sleep apnea have a high blood uric acid levels and prevalence of HUA [26][27][28][29]. In a large epidemiological sample in Brazil, a strong association was found between uric acid levels and OSA even after adjustment for confounding factors such as gender, age, BMI, social class, ethnicity, cholesterol, triglycerides, blood pressure and glucose [26]. Another study conducted in overweight children and adolescents demonstrated a relationship between the severity of sleep apnea and increased levels of SUA, independent of abdominal adiposity [27]. Pływaczewski et al.
has found that HUA is frequent in both males and females with OSA [28][29]. In addition, recent several studies also demonstrated sleep apnea is independently associated with an increased risk of incident gout [29], which is a common in ammatory arthritis caused by HUA. As a highly prevalent condition associated with OSA and sleep disturbance in bed partners, snoring is commonly considered as a mild form of sleep apnea or a useful screening tool for OSA [11,31]. However, studies about the association between soring and SUA level or HUA were limited. A recent study found that self-reported habitual snoring was associated with higher SUA concentration, but it was only conducted in Chinese urban adults [11].
The current study found that snoring was independently associated with increased SUA level and risk of HUA in rural Chinese adults, which addressed the data gap in rural area. Meanwhile, the positive associations between snoring and HUA were attenuated in participants with chronic disease conditions (obesity, T2DM, hypertension and dyslipidemia). In accordance with our ndings, a previous study also found the association between snoring and HUA was attenuated in participants with some clinical outcomes such as depression, diabetes, hypertension, and high-cholesterol levels [31]. Although the association was attenuated, it still remained signi cant after further adjustment of these chronic disease conditions (Additional le 1: Table S1), which suggested those habitual snorers may be related with these chronic diseases. In addition, snoring may play an independently important role in the development of HUA [11]. The biologic mechanisms linking snoring to the HUA were unclear. Some main hypotheses were that habitual snoring is usually accompanied by OSA. First, OSA-induced hypoxemia can cause a rise in adenosine triphosphate (ATP) degradation which eventually increases purine concentrations, leading to elevated blood uric acid level [32]. Second, excretion of lactic acid, generated during the hypoxic episodes in OSA, could result in a higher renal reabsorption of uric acid [33].
In this study, we also observed that daytime napping was independently associated with increased SUA level and risk of HUA. Many studies have reported that daytime napping or sleep duration was associated with metabolic diseases [12][13][14][15]. But few studies have evaluated the relationship of sleep variables such as daytime napping and night sleep duration with HUA. Only a survey from the National Health and Nutrition Examination indicated a positive relationship of multiple sleep variables including snoring, snorting, and daytime sleepiness, with prevalence of HUA [34], meantime night sleep duration was not associated with HUA, which is consistent with our results. However, the effect of napping on HUA was not explored in the above-mentioned survey. As the rst study to explore association between napping and HUA in Chinese rural adults, we also further found the joint effect of snoring frequency and napping duration on HUA. Some previous study had found the combined effect of napping or sleep quality and night sleep duration on some metabolic diseases [15,35]. Similarly, in the current study, we observed that habitual snoring (≥ 3 days/week) combined with longer daytime napping (≥ 61 min) increased 63% risk of HUA in total participants (66% for men and 63% for men), though no signi cant joint effects of snoring frequency and night sleep duration or daytime napping and night sleep duration existed. Biological mechanisms underlying the joint effects are not clear, but this emphasizes the adverse health consequences of snoring and daytime napping, as well as jointly predicted HUA prevalence. We speculated that snoring as a sleep disorder marker may partly contribute the adverse effects of longer daytime napping on HUA. In addition, the exact mechanism underlying the association between the napping and HUA also remains unclear. One potential biological pathway is through in ammation, as Janna et al reported that increased napping is an independent predictor of in ammation in adults [36].
Previous animal studies also have shown that intermittent hypoxia and resultant oxygen desaturation may be associated with subsequent activation of in ammatory pathways and cause elevated SUA level [37]. Further studies are needed to clarify the mechanism.
The strengths of this study are as follows. Firstly, the current study thoroughly discussed the independent association between snoring frequency, daytime napping, night sleep duration and HUA based on a large rural cohort, which help us ll this knowledge gap about the relationship in rural Chinese population.
Secondly, to our knowledge, this is the rst study to found the joint effect of snoring and napping on HUA, which both were prevalent in Chinese rural area and should be given more attention. However, several limitations need to be noted: rst, because of the cross-sectional nature, we could not establish the causal relationship of snoring or napping or night sleep duration with HUA. Thus, further prospective studies are demanded to con rm the results from this study. Second, data on snoring frequency and napping were obtained from a self-reported questionnaire rather than an accurate evaluation using polysomnography. Nevertheless, similar assessment of these variables has been widely used [35,38]. Third, because our participants hardly reported the use of sleep medications, we also did not include this variable in the current study.

Conclusions
In conclusion, snoring frequency or daytime napping might be important predictors of high SUA level and HUA prevalence among rural Chinese adults. Moreover, habitual snoring combined with longer daytime napping (≥ 61 min) may be associated with a higher prevalence of HUA. Intervention of snoring and measures to control longer daytime napping could contribute to reducing prevalence of HUA and SUA level, which further control the development of gout.  Figure 1 Snoring (vs never snoring) and prevalence of hyperuricemia, strati ed by age, gender, and chronic disease conditions. Adjusted for age, gender, education level, marital status, average monthly income, smoking status, drinking status, physical activity, dietary pattern, daytime napping, night sleep duration, family history of gout, obesity, T2DM, hypertension and dyslipidemia conditions. Each group adjusted for the other covariates except itself. OR= Odds Ratio, CI= con dence interval, T2DM= type 2 diabetes mellitus.

Figure 2
Napping (each 30min increment) and prevalence of hyperuricemia, strati ed by age, gender, and chronic disease conditions. Adjusted for age, gender, education level, marital status, average monthly income, smoking status, drinking status, physical activity, dietary pattern, snoring, night sleep duration, family history of gout, obesity, T2DM, hypertension and dyslipidemia conditions. Each group adjusted for the other covariates except itself. OR= Odds Ratio, CI= con dence interval, T2DM = type 2 diabetes mellitus.