Kidney Res Clin Pract > Epub ahead of print
Han, Ko, Lee, Kim, Kim, Oh, Lim, and Lee: Weekend catch-up sleep and its association with chronic kidney disease and albuminuria in middle age and older adults from the National Health and Nutrition Examination Survey (2017–2020)

Abstract

Background

How weekend catch-up sleep (WCS) influences chronic kidney disease (CKD) risk is unknown. We investigated the association between WCS and CKD prevalence in adults.

Methods

In the National Health and Nutrition Examination Survey (NHANES, 2017–2020) participants (n = 4,961; age ≥ 40 years), we assessed the relationships of WCS (>1 hour increased sleep duration on weekends) with CKD and albuminuria prevalence via multivariate logistic regression analysis adjusted for potential confounders.

Results

WCS participants exhibited notably both lower CKD and albuminuria prevalence than non-WCS participants did, even after confounding variable adjustment (adjusted odds ratio [OR], 0.67; 95% confidence interval [CI], 0.46–0.96 and OR, 0.69; 95% CI, 0.49–0.97, respectively). Specifically, 1 to 2 hours of WCS were associated with decreased CKD (OR, 0.58; 95% CI, 0.38–0.89; p = 0.02). Furthermore, 1 to 2 hours of WCS were also significantly associated with lower albuminuria (OR, 0.11; 95% CI, 0.05–0.22; p < 0.001) among individuals sleeping <6 hours on weekdays.

Conclusion

WCS, particularly 1 to 2 hours, was significantly associated with a lower CKD prevalence in the middle-aged and older population, and albuminuria risk among those with restricted weekday sleep. These findings suggest that maintaining adequate sleep duration through WCS is linked to beneficial effects on kidney health. Longitudinal studies are needed to confirm these results.

Introduction

Chronic kidney disease (CKD) has emerged as a critical public health concern in the modern century, and its prevalence has increased in association with an increased incidence of risk factors such as hypertension and diabetes mellitus (DM) [13]. The global burden of CKD has markedly increased, affecting more than 10% of the general population worldwide and accounting for approximately 846 million individuals in 2017 [3]. As CKD is a well-known risk factor for cardiovascular morbidity and mortality, identifying and preventing the etiology of CKD is a crucial medical challenge in the field of healthcare [4,5].
Sleep, an essential component of human physiology, profoundly influences various health outcomes, including development, immune function, cognitive performance, and disease progression [6]. Epidemiologic evidence has consistently demonstrated that both deficient or excessive sleep durations are associated with adverse health problems, including hypertension, type 2 DM, cardiovascular disease (CVD), and increased mortality [79]. Furthermore, recent studies have reported an association between shorter sleep duration and decreased kidney function [10,11]. In a cross-sectional study of a healthy population, individuals who slept less than 5 hours or more than 9 to 10 hours per day were associated with a higher prevalence of CKD [11]. Given the importance of adequate sleep, the American Academy of Sleep Medicine and the Sleep Research Society advocate for a minimum of 7 hours of nightly sleep for adults [12]. However, contemporary societal demands often render sleep deprivation a common occurrence, especially among middle-aged and older adults, who are experiencing psychological stress, aging, and more prevalent sleep disorders [13]. In this context, weekend catch-up sleep (WCS), which compensates for sleep deficits during the week or workdays, has gained recognition as a potentially beneficial pattern for ameliorating sleep-related health issues. Previous studies have reported that WCS is associated with a lower risk of metabolic conditions, such as hypertension, metabolic syndrome, and type 2 DM [1416]. In addition, a WCS duration >2 hours was associated with a reduced CVD prevalence when the weekday sleep duration was less than 6 hours [17]. These metabolic derangements are known contributors to decreased kidney function, suggesting a potential link between WCS and improved kidney health. Nevertheless, despite the increasing evidence connecting inadequate sleep duration with CKD [10,18], research exploring the relationship between WCS and CKD remains scarce.
Thus, we sought to assess the association between WCS and CKD within a nationally representative cohort from the United States, suggesting that WCS may be inversely related to the risk of deteriorating kidney function, including the manifestation of albuminuria.

Methods

Study population

This was a cross-sectional study that utilized data from the National Health and Nutrition Examination Survey (NHANES) cycles spanning from 2017 to March 2020. The NHANES is designed to estimate the prevalence of common diseases and associated risk factors from nationally representative samples of the noninstitutionalized United States population [19]. The survey protocol and participant consent for the NHANES were approved by the Institutional Review Board of the National Center for Health Statistics and are available on the survey website (https://www.cdc.gov/nchs/nhanes). The original dataset included 15,560 participants; for this study, we included study participants aged 40 years or older (n = 6,433). A total of 1,472 participants were excluded due to missing values, including information related to sleep, serum creatinine levels, and urine albumin levels. Consequently, the final analysis was conducted on a total of 4,961 participants in this study (Fig. 1).

Weekend catch-up sleep and outcomes

Based on the participants’ responses to the sleep-related questionnaires, WCS data were obtained by calculating the average sleep durations on weekdays (or workdays) and weekends (or non-workdays). The catch-up sleep duration was determined by subtracting weekday sleep duration from weekend sleep duration [16]. Catch-up sleep of 1 hour or less was considered within the normal range of sleep difference, as indicated by a previous study [17]. Thus, we defined WCS as a weekend sleep duration that exceeded the weekday sleep duration by more than 1 hour. The participants were subsequently divided into WCS and non-WCS (i.e., WCS ≤1 hour) groups.
The primary outcome was the prevalence of CKD, and the secondary outcome was the prevalence of albuminuria. A person with an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or a urinary albumin-creatinine ratio (UACR) ≥30 mg/g was defined as having CKD [20]. The eGFR was calculated using the 2009 CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation [20]. Albuminuria was defined as a UACR ≥30 mg/g, independent of the eGFR.

Assessment of other variables

The covariates were carefully defined and selected based on clinical experience and relevant literature, including sociodemographic factors (age, sex, race, education, job status [21], and living with a partner [17]), lifestyle factors (smoking status, alcohol consumption [22], and physical activity), and clinical factors (body mass index [BMI], hypertension, and DM). The following factors were categorized for comparison analysis: job status (employed vs. unemployed); living with a partner (yes or no); current smoking status (never, former, or current); and BMI (<25 kg/m2, ≥25 and <30 kg/m2, or ≥30 kg/m2). Alcohol consumption was categorized as ‘no’ for individuals who had not consumed alcohol in the past year and ‘yes’ for all others. Physical activity was classified as ‘moderate’ or ‘less,’ with individuals reporting engagement in moderate-intensity activities, such as brisk walking or carrying light loads for at least 10 minutes continuously, categorized as ‘moderate.’ Hypertension was defined as systolic blood pressure >140 mmHg or diastolic blood pressure >90 mmHg, current use of antihypertensive medication, or a self-reported history of hypertension. DM was defined as the use of insulin or oral hypoglycemic agents, a glycated hemoglobin level ≥6.5%, or a self-reported history based on the following question, ‘Have you ever been told by a doctor that you have DM?’

Statistical analysis

We analyzed the NHANES data from 2017 to March 2020 using sampling weights, stratification, and clustering to account for the complex survey design [23]. The analyses included the sampling unit variable (SDMVPSU) as the stratification variable (SDMVSTRA) and the Mobile Examination Center (MEC) exam variable (WTMECPRP) as the weight variable. We used the Wilcoxon rank-sum test for continuous variables and the Pearson chi-square test for categorical variables. Univariate analyses were conducted to assess the associations of WCS with CKD and albuminuria. Multivariate logistic analysis was further performed after adjusting for potential confounders. Age, sex, race, BMI, job status, alcohol consumption, smoking, education, partner status, physical activity, hypertension, and DM were included as categorical variables, whereas average sleep duration was treated as a continuous variable. Furthermore, we carried out an adjusted multivariate analysis to evaluate the associations of WCS duration, categorized as no WCS, 1–2 hours, and >2 hours, with CKD and albuminuria. Subgroup analyses were also conducted to explore potential effect modifications by key variables. A two-tailed p-value of <0.05 was considered to indicate statistical significance in all analyses. All the statistical analyses were performed using R version 4.3.1 (R Foundation for Statistical Computing).

Results

Baseline characteristics of the participants

Among the 4,961 participants analyzed, 1,147 individuals were categorized into the WCS group. The demographic and clinical characteristics of the study participants are summarized in Table 1. The WCS group exhibited a shorter weekday sleep duration than the non-WCS group, but they compensated with a longer sleep duration over the weekend. Notably, the prevalence of hypertension, CKD, and albuminuria were significantly greater in the non-WCS group than in the WCS group. The mean age of the participants in the WCS group was lower than that of the participants in the non-WCS group (53.04 ± 9.02 years vs. 60.47 ± 11.60 years). Additionally, factors such as race, employment status, and alcohol consumption were significantly associated with WCS.

Associations between weekend catch-up sleep and chronic kidney disease

Univariate and multivariate logistic regression analyses were performed to evaluate the associations between WCS and CKD (Table 2). According to the unadjusted model, WCS was associated with a significantly lower prevalence of CKD (odds ratio [OR], 0.47; 95% confidence interval [CI], 0.37–0.60). After full adjustment for potential confounders, the association remained significant, indicating a reduced prevalence of CKD among the WCS group (OR, 0.66; 95% CI, 0.45–0.98; p = 0.04). In addition, subgroup analysis was performed to investigate the association of WCS with varying weekday sleep durations (shorter [<6 hours] or longer [>9 hours]), but no significant differences were observed (Supplementary Table 1, available online).

Associations between weekend catch-up sleep and Albuminuria

A separate multivariate logistic regression analysis was performed to examine the potential association between WCS and albuminuria as a secondary outcome. Participants with WCS durations of more than 1 hour demonstrated a significantly decreased risk of albuminuria in the unadjusted model (OR, 0.65; 95% CI, 0.50–0.84). Furthermore, this association was persistent in the fully adjusted model (OR, 0.68; 95% CI, 0.47–0.99) (Table 3). However, subgroup analyses stratified by weekday sleep duration did not reveal any significant associations (Supplementary Table 2, available online).

Associations between weekend catch-up sleep duration and chronic kidney disease outcomes

Further analysis was conducted to identify the optimal duration of WCS for health benefits. The participants were divided into subgroups based on WCS duration: 1–2 hours (n = 579) and >2 hours (n = 568). Multivariate logistic regression analysis revealed that there was a stronger association with a reduced incidence of CKD in the group with a WCS duration of 1–2 hours than in the non-WCS group (OR, 0.58; 95% CI, 0.36–0.95) (Table 4). However, a WCS duration >2 hours was not significantly different from the non-WCS group regarding the risk of CKD (OR, 0.76; 95% CI, 0.39–1.48).
Regarding albuminuria prevalence, WCS duration of neither 1–2 hours nor >2 hours was significantly associated with the risk of albuminuria (OR, 0.63; 95% CI, 0.34–1.18 and OR, 0.73; 95% CI, 0.44–1.23, respectively) (Table 5). Intriguingly, among participants who slept less than 6 hours on weekdays, those with a WCS of 1–2 hours had a significantly reduced risk of albuminuria in both adjusted models (OR, 0.09; 95% CI, 0.04–0.21 and OR, 0.11; 95% CI, 0.05–0.25, respectively). However, there were no significant differences observed between the groups with adequate or excessive sleep duration.

Subgroup analyses between weekend catch-up sleep and chronic kidney disease outcomes

Subgroup analyses revealed that although the WCS effects did not significantly differ between groups (all p for interaction, >0.05), the beneficial associations of WCS with CKD and albuminuria were more prominent in certain subgroups (Supplementary Tables 3, 4; available online). For CKD, WCS was associated with lower odds in subgroups such as males, individuals with a BMI ≥30 kg/m2, and those with hypertension or without DM. Similarly, for albuminuria, the protective effects of WCS were notable among males, individuals with a BMI ≥30 kg/m2, those who consumed alcohol, and those with no DM. In addition, participants with more structured lifestyles, such as higher education (college or above), living with a partner, employment, or engagement in moderate physical activity, demonstrated stronger associations between WCS and reduced odds of CKD and albuminuria.

Discussion

In the present study, we found that WCS was significantly associated with a reduced risk of both CKD and albuminuria in middle-aged and older individuals in the general population. Notably, a WCS of 1–2 hours was associated with a lower prevalence of CKD. Additionally, WCS was linked to a reduced prevalence of albuminuria in individuals with a weekday sleep duration of less than 6 hours. To our knowledge, this is the first study to examine the association between WCS and CKD.
Numerous prior studies have established a connection between adequate sleep duration and kidney function. A prospective study involving 4,000 women reported that a shorter sleep duration was significantly associated with a rapid decrease in the eGFR [10]. Park et al. [24] reported that a shorter (<6 hours) or longer (> 9 hours) duration was associated with a greater incidence of CKD in a Mendelian randomization study. Furthermore, albuminuria, an important marker of kidney damage, has a U-shaped association with sleep duration in the general population [25].
WCS, a compensatory behavior for sleep deficits that involves extending sleep on weekends, has demonstrated beneficial impacts on various health issues [1417]. Son et al. [16] reported that WCS of 1–2 hours was associated with a reduced risk of metabolic syndrome among Korean adults experiencing sleep deprivation (<6 hours) compared with WCS <0 hours. Similarly, moderate WCS (0–2 hours) was linked to reduced odds of depressive symptoms [26]. In contrast, prolonged weekend sleep duration (>9 hours) has been linked to eGFR decline, even in individuals with shorter weekday sleep duration (<6 hours) [27]. This may reflect a nonlinear relationship between sleep duration and CKD, with both shorter and longer sleep durations relative to 7–8 hours linked to a greater risk of incident CKD [28]. In our study, 1–2 hours of WCS was strongly associated with a reduced risk of CKD, whereas a duration of WCS >2 hours showed no such benefit, which aligns with previous findings on the adverse effects of prolonged sleep. Prolonged sleep (>9 hours) was also linked to an increased CKD progression, potentially due to circadian rhythm disturbances that lead to nondipper hypertension and subsequent kidney function decline [29]. Furthermore, prolonged sleep may also reduce physical activity, contributing to obesity, hypertension, and DM—major risk factors for CKD progression [30]. Our findings also support the need for balanced sleep duration, highlighting that even when compensating for insufficient sleep, adequate WCS had more beneficial effects than excessive WCS. However, further research is warranted to ascertain the optimal duration of WCS.
In addition, subgroup analyses indicated that the effects of WCS on CKD and albuminuria were consistent across groups, without significant interaction effects. However, the benefits of WCS appeared more pronounced in individuals with a structured lifestyle, such as being employed, living with a partner, or engaging in regular physical activity. These findings suggest that appropriate sleep supplementation combined with a structured lifestyle may further enhance kidney health.
One possible explanation for these findings is that insufficient sleep can lead to metabolic disturbances such as insulin resistance or hypertension, which are acknowledged risk factors for CKD. A systemic review reported that short sleep duration was significantly associated with insulin resistance [31], and the authors suggested that glucagon-like peptide-1 and inflammatory markers such as C-reactive protein (CRP) may play crucial roles in the pathogenesis of this relationship. Another potential mechanism is that WCS may help ameliorate inflammatory changes, given the significant role of chronic inflammation in CKD progression [32]. Han et al. [33] reported that individuals engaging in WCS exhibited significantly lower CRP levels than did individuals in the non-WCS group. Another recent study demonstrated that a duration of 1–2 hours of WCS was associated with a significantly lower risk of high-sensitivity CRP elevation among Korean workers [34].
Our study also demonstrated that WCS was linked to a lower risk of albuminuria, which was a secondary outcome. Similar to the findings for CKD, 1–2 hours of WCS was associated with a reduced albuminuria prevalence in participants with sleep durations less than 6 hours. Previous research has consistently indicated an increased prevalence of albuminuria among individuals with sleep deprivation [35,36]. A longitudinal Japanese study among young to middle-aged adults who slept less than 5 hours a night revealed a 28% increase in the incidence of proteinuria over a median period of 2.5 years, despite the absence of initial kidney dysfunction [18]. Considering the role of albuminuria in mediating CKD progression and kidney dysfunction [37], adequate sleep supplementation may help mitigate the onset and progression of kidney disease in those with insufficient sleep. Our present findings corroborate those previous findings, indicating the beneficial effects of WCS on reducing the prevalence of albuminuria in the general population with short sleep durations.
Despite these novel findings, the present study has several limitations. First, its cross-sectional design precludes establishing causality between WCS and CKD. In addition, because the dataset provided only a single measurement of laboratory tests, this may have led to potential misclassification of CKD status. However, NHANES data are representative of US populations, and their stability and reliability for epidemiological evaluations are well-acknowledged, which mitigates these limitations. Second, the reliance on self-reported sleep duration data may introduce bias, including recall bias. Third, although we performed a multivariate regression analysis considering numerous confounders, other hidden covariates could have affected the results. Fourth, our study population was limited to middle-aged and older individuals, and the applicability of our findings to younger individuals is uncertain. However, age subgroup analyses showed no significant differences, suggesting consistent potential benefits of WCS across age groups. In addition, as middle-aged and older adults are more prone to CKD and the negative impacts of sleep disturbances, our results support the importance of WCS for the general populations vulnerable to sleep issues.
In conclusion, we demonstrated that WCS, particularly less than 2 hours, is associated with a lower prevalence of CKD in the middle-aged and older populations. In addition, 1–2 hours of WCS significantly reduces the risk of albuminuria in individuals with short sleep durations. Further investigations are necessary to elucidate the causal relationships between WCS and CKD progression.

Notes

Conflicts of interest

Jeonghwan Lee is a deputy editor of Kidney Research and Clinical Practice and was not involved in the review process of this article. All authors have no other conflicts of interest to declare.

Funding

This work was supported by a multidisciplinary research grant from the Seoul Metropolitan Government, SMG-SNU Boramae Medical Center (No. 04-2023-0034).

Data sharing statement

The data that support the findings of this study are openly available on the National Health and Nutrition Examination Survey (NHANES) website at https://www.cdc.gov/nchs/nhanes.

Authors’ contributions

Conceptualization, Methodology: SHH, JPL

Formal analysis: SHH

Data curation: SHH, AK

Investigation: SHH, AK, JL, DKK, YSK, YKO, CSY

Supervision: JPL

Writing–original draft: SHH

Writing–review & editing: All authors

All the authors read and approved the final manuscript.

Figure 1.

Flow chart of study participants in the National Health and Nutrition Examination Survey (NHANES) 2017–2020.

j-krcp-24-285f1.jpg
Table 1.
Baseline characteristics of the study participants
Characteristic No WCS (n = 3,814) WCS (n = 1,147) p-value
Age (yr) 60.47 ± 11.60 53.04 ± 9.02 <0.001
 40–59 1,599 (47.2) 803 (78.3) <0.001
 60–79 1,806 (45.1) 326 (20.4)
 ≥80 409 (7.7) 18 (1.2)
Female sex 1,853 (51.9) 621 (52.1)
Race <0.001
 Hispanic 707 (10.9) 327 (20.3)
 White 1,619 (71.8) 295 (58.7)
 Black 913 (8.9) 340 (11.9)
 Others 575 (8.5) 175 (9.0)
Body mass index (kg/m2) 0.05
 <25 843 (21.4) 227 (21.7)
 25–30 1,318 (36.6) 365 (29.4)
 ≥30 1,653 (42.0) 555 (49.0)
Smoking 0.07
 Never 1,977 (52.2) 730 (60.4)
 Former 1,178 (32.4) 254 (27.4)
 Current 659 (15.3) 163 (12.3)
 Education 0.71
  College or above 2,181 (62.1) 639 (60.4)
  High school 920 (26.6) 283 (28.3)
  Less than high school 713 (11.2) 225 (11.3)
Job status <0.001
 Unemployed 2,159 (49.6) 291 (18.5)
 Employed 1,655 (50.4) 856 (81.5)
Partner 0.06
 Living with a partner 2,300 (67.2) 756 (70.7)
 Living without a partner 1,514 (32.8) 391 (29.3)
Alcohol consumption <0.001
 None 1,346 (29.4) 344 (20.6)
 Yes 2,468 (70.6) 803 (79.4)
Physical activity 0.07
 Less 2,261 (54.4) 659 (50.0)
 Moderate 1,553 (45.6) 488 (50.0)
Hypertension 2,314 (53.5) 426 (46.8) 0.04
Diabetes mellitus 1,002 (20.7) 279 (18.8) 0.44
eGFR (mL/min/1.73 m2) 82.95 ± 19.22 91.65 ± 16.93 <0.001
Albumin-creatinine ratio (mg/g) 45.39 ± 288.91 34.74 ± 318.17 0.002
Chronic kidney disease 975 (22.0) 198 (11.7) <0.001
Albuminuria 654 (13.4) 154 (9.1) 0.003
Weekday sleep duration (hr) 7.73 ± 1.45 6.77 ± 1.29 <0.001
Weekend sleep duration (hr) 7.73 ± 1.49 9.32 ± 1.42 <0.001

Data are expressed as mean ± standard deviation or number (weighted %).

eGFR, estimated glomerular filtration rate; WCS, weekend catch-up sleep.

Table 2.
Associations between WCS and chronic kidney disease
WCS (>1 hr) Crude
Model 1
Model 2
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
No (n = 3,814) Reference Reference Reference
Yes (n = 1,147) 0.47 (0.37–0.60) <0.001 0.72 (0.52–0.99) 0.045 0.66 (0.45–0.98) 0.04

Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, race, body mass index, education, job status, alcohol consumption, smoking status, physical activity, partner status, hypertension, diabetes mellitus, and average sleep duration.

CI, confidence interval; OR, odds ratio; WCS, weekend catch-up sleep.

Table 3.
Associations between WCS and albuminuria
WCS (>1 hr) Crude
Model 1
Model 2
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
No (n = 3,814) Reference Reference Reference
Yes (n = 1,147) 0.65 (0.50–0.84) 0.003 0.80 (0.59–1.07) 0.13 0.68 (0.47–0.99) 0.047

Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, race, body mass index, education, job status, alcohol consumption, smoking status, physical activity, partner status, hypertension, diabetes mellitus, and average sleep duration.

CI, confidence interval; OR, odds ratio; WCS, weekend catch-up sleep.

Table 4.
Adjusted multivariate logistic regression analysis between the duration of WCS and chronic kidney disease prevalence
Sleep duration (hr) Model 1
Model 2
OR (95% CI) p-value OR (95% CI) p-value
Total
 No WCS (n = 3,814) Reference Reference
 WCS >1 and ≤2 (n = 579) 0.61 (0.42–0.87) 0.009 0.58 (0.36–0.95) 0.04
 WCS >2 (n = 568) 0.88 (0.54–1.44) 0.60 0.76 (0.39–1.48) 0.32
Weekday sleep duration <6
 No WCS (n = 310) Reference Reference
 WCS >1 and ≤2 (n = 70) 0.21 (0.09–0.47) <0.001 0.34 (0.09–1.28) 0.09
 WCS >2 (n = 163) 0.59 (0.28–1.26) 0.16 0.80 (0.18–3.56) 0.71
Weekday sleep duration ≥6 and <9
 No WCS (n = 2,514) Reference Reference
 WCS >1 and ≤2 (n = 459) 0.72 (0.47–1.09) 0.12 0.64 (0.37–1.12) 0.09
 WCS >2 (n = 374) 0.98 (0.55–1.74) 0.93 0.72 (0.32–1.63) 0.33
Weekday sleep duration ≥9
 No WCS (n = 990) Reference Reference
 WCS >1 and ≤2 (n = 50) 0.58 (0.23–1.45) 0.23 0.44 (0.09–2.22) 0.23
 WCS >2 (n = 31) 0.77 (0.26–2.26) 0.62 0.65 (0.12–3.66) 0.53

Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, race, body mass index, education, job status, alcohol consumption, smoking status, physical activity, partner status, hypertension, diabetes mellitus, and average sleep duration.

CI, confidence interval; OR, odds ratio; WCS, weekend catch-up sleep.

Table 5.
Adjusted multivariate logistic regression analysis between the duration of WCS and albuminuria
Sleep duration (hr) Model 1
Model 2
OR (95% CI) p-value OR (95% CI) p-value
Total
 No WCS (n = 3,814) Reference Reference
 WCS >1 and ≤2 (n = 579) 0.69 (0.44–1.07) 0.09 0.63 (0.34–1.18) 0.11
 WCS >2 (n = 568) 0.94 (0.65–1.34) 0.71 0.73 (0.44–1.23) 0.17
Weekday sleep duration <6
 No WCS (n = 310) Reference Reference
 WCS >1 and ≤2 (n = 70) 0.09 (0.04–0.21) <0.001 0.11 (0.05–0.25) 0.002
 WCS >2 (n = 163) 0.64 (0.27–1.50) 0.28 0.80 (0.27–2.31) 0.59
Weekday sleep duration ≥6 and <9
 No WCS (n = 2,514) Reference Reference
 WCS >1 and ≤2 (n = 459) 0.82 (0.52–1.30) 0.38 0.73 (0.39–1.39) 0.25
 WCS >2 (n = 374) 1.06 (0.63–1.78) 0.83 0.74 (0.36–1.53) 0.31
Weekday sleep duration ≥9
 No WCS (n = 990) Reference Reference
 WCS >1 and ≤2 (n = 50) 0.70 (0.26–1.89) 0.46 0.55 (0.10–3.01) 0.38
 WCS >2 (n = 31) 0.74 (0.19–2.80) 0.64 0.56 (0.08–4.19) 0.47

Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, race, body mass index, education, job status, alcohol consumption, smoking status, physical activity, partner status, hypertension, diabetes mellitus, and average sleep duration.

CI, confidence interval; OR, odds ratio; WCS, weekend catch-up sleep.

References

1. Webster AC, Nagler EV, Morton RL, Masson P. Chronic kidney disease. Lancet 2017;389:1238–1252.
crossref pmid
2. Merchant RA, Vathsala A. Healthy aging and chronic kidney disease. Kidney Res Clin Pract 2022;41:644–656.
crossref pmid pmc pdf
3. Jager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C. A single number for advocacy and communication-worldwide more than 850 million individuals have kidney diseases. Kidney Int 2019;96:1048–1050.
crossref pmid
4. Kim KM, Oh HJ, Choi HY, Lee H, Ryu DR. Impact of chronic kidney disease on mortality: a nationwide cohort study. Kidney Res Clin Pract 2019;38:382–390.
crossref pmid pmc
5. GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2020;395:709–733.
crossref pmid pmc
6. Zielinski MR, McKenna JT, McCarley RW. Functions and mechanisms of sleep. AIMS Neurosci 2016;3:67–104.
crossref pmid
7. Grandner M, Mullington JM, Hashmi SD, Redeker NS, Watson NF, Morgenthaler TI. Sleep duration and hypertension: analysis of > 700,000 adults by age and sex. J Clin Sleep Med 2018;14:1031–1039.
crossref pmid pmc
8. Shan Z, Ma H, Xie M, et al. Sleep duration and risk of type 2 diabetes: a meta-analysis of prospective studies. Diabetes Care 2015;38:529–537.
crossref pmid pdf
9. Yin J, Jin X, Shan Z, et al. Relationship of sleep duration with all-cause mortality and cardiovascular events: a systematic review and dose-response meta-analysis of prospective cohort studies. J Am Heart Assoc 2017;6:e005947.
crossref pmid pmc
10. McMullan CJ, Curhan GC, Forman JP. Association of short sleep duration and rapid decline in renal function. Kidney Int 2016;89:1324–1330.
crossref pmid pmc
11. Jiang L, Xu H. U-shaped relationship between sleep duration and CKD in US adults: data from National Health and Nutrition Examination Survey (NHANES) 2005-2014. Am J Nephrol 2023;54:275–280.
crossref pmid pdf
12. Watson NF, Badr MS, Belenky G, et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep 2015;38:843–844.
crossref pmid pmc
13. Gulia KK, Kumar VM. Sleep disorders in the elderly: a growing challenge. Psychogeriatrics 2018;18:155–165.
crossref pmid pdf
14. Hwangbo Y, Kim WJ, Chu MK, Yun CH, Yang KI. Association between weekend catch-up sleep duration and hypertension in Korean adults. Sleep Med 2013;14:549–554.
crossref pmid
15. Kim JJ, Hwang IC. Weekend catch-up sleep is associated with reduced metabolic derangements in Korean adults. Neurol Sci 2021;42:735–737.
crossref pmid pdf
16. Son SM, Park EJ, Cho YH, et al. Association between weekend catch-up sleep and metabolic syndrome with sleep restriction in Korean adults: a cross-sectional study using KNHANES. Diabetes Metab Syndr Obes 2020;13:1465–1471.
crossref pmid pmc
17. Zhu H, Qin S, Wu M. Association between weekend catch-up sleep and cardiovascular disease: evidence from the National Health and Nutrition Examination Surveys 2017-2018. Sleep Health 2024;10:98–103.
crossref pmid
18. Yamamoto R, Shinzawa M, Isaka Y, et al. Sleep quality and sleep duration with CKD are associated with progression to ESKD. Clin J Am Soc Nephrol 2018;13:1825–1832.
crossref pmid pmc
19. Stierman B, Afful J, Carroll MD, et al. National Health and Nutrition Examination Survey 2017-March 2020 prepandemic data files-development of files and prevalence estimates for selected health outcomes. Natl Health Stat Report 2021 (158):10.15620/cdc:106273.
20. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–612.
crossref pmid pmc pdf
21. Kim KM, Han SM, Min IK, Heo K, Kim WJ, Chu MK. Weekend catch-up sleep and depression: results from a nationally representative sample in Korea. Sleep Med 2021;87:62–68.
crossref pmid
22. Son SM, Park EJ, Kwon RJ, et al. Association between weekend catch-up sleep and hyperuricemia with insufficient sleep in postmenopausal Korean women: a nationwide cross-sectional study. Menopause 2023;30:607–612.
crossref pmid pmc
23. Akinbami LJ, Chen TC, Davy O, et al. National Health and Nutrition Examination Survey, 2017-March 2020 prepandemic file: sample design, estimation, and analytic guidelines. Vital Health Stat 2022;(190):1–36.
24. Park S, Lee S, Kim Y, et al. Short or long sleep duration and CKD: a Mendelian Randomization Study. J Am Soc Nephrol 2020;31:2937–2947.
crossref pmid pmc
25. Yu JH, Han K, Kim NH, et al. U-shaped association between sleep duration and urinary albumin excretion in Korean adults: 2011-2014 Korea National Health and Nutrition Examination Survey. PLoS One 2018;13:e0192980.
crossref pmid pmc
26. Luo Z, Wang T, Wu W, Yan S, Chen L. Association between weekend catch-up sleep and depressive symptoms in American adults: Finding from NHANES 2017-2020. J Affect Disord 2024;354:36–43.
crossref pmid
27. Wu CC, Yang PL, Kao LT, et al. Sleep duration and kidney function: does weekend sleep matter? Nat Sci Sleep 2024;16:85–97.
crossref pmid pmc pdf
28. Koh JH, Yeo BS, Tan TW, et al. The association of sleep duration with the risk of chronic kidney disease: a systematic review and meta-analysis. Clin Kidney J 2024;17:sfae177.
crossref pmid pmc pdf
29. Hirano K, Komatsu Y, Shimbo T, Nakata H, Kobayashi D. Longitudinal relationship between long sleep duration and future kidney function decline. Clin Kidney J 2022;15:1763–1769.
crossref pmid pmc pdf
30. Humphreys BR, McLeod L, Ruseski JE. Physical activity and health outcomes: evidence from Canada. Health Econ 2014;23:33–54.
crossref pmid
31. Singh T, Ahmed TH, Mohamed N, et al. Does insufficient sleep increase the risk of developing insulin resistance: a systematic review. Cureus 2022;14:e23501.
crossref pmid pmc
32. Rapa SF, Di Iorio BR, Campiglia P, Heidland A, Marzocco S. Inflammation and oxidative stress in chronic kidney disease-potential therapeutic role of minerals, vitamins and plant-derived metabolites. Int J Mol Sci 2019;21:263.
crossref pmid pmc
33. Han KM, Lee HJ, Kim L, Yoon HK. Association between weekend catch-up sleep and high-sensitivity C-reactive protein levels in adults: a population-based study. Sleep 2020;43:zsaa010.
crossref pmid pdf
34. Jung SW, Lee KJ, Lee JH. Does weekend catch-up sleep affect high-sensitivity C-reactive protein levels among Korean workers?: a cross-sectional study using KNHANES. J Occup Environ Med 2019;61:e367–e373.
crossref pmid
35. Petrov ME, Buman MP, Unruh ML, et al. Association of sleep duration with kidney function and albuminuria: NHANES 2009-2012. Sleep Health 2016;2:75–81.
crossref pmid pmc
36. Afsar B. The relationship between self-reported nocturnal sleep duration, daytime sleepiness and 24-h urinary albumin and protein excretion in patients with newly diagnosed type 2 diabetes. Prim Care Diabetes 2013;7:39–44.
crossref pmid
37. Pasternak M, Liu P, Quinn R, et al. Association of albuminuria and regression of chronic kidney disease in adults with newly diagnosed moderate to severe chronic kidney disease. JAMA Netw Open 2022;5:e2225821.
crossref pmid pmc


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