Nocturia, Sleep Quality, and Mortality: A Systematic Review and Meta-Analysis

Abstract

Purpose

Nocturia is increasingly recognized as a significant factor influencing sleep quality and potentially linked to increased mortality risk. This meta-analysis aimed to systematically review and synthesize existing research investigating the relationship between nocturia, sleep quality, and mortality, in a single framework.

Materials and Methods

A comprehensive systematic search across PubMed, Embase, and the Cochrane Library was conducted from the inception of each database until April 2, 2024, yielding studies investigating the methodological qualities and the relationship between nocturia and its impact on mortality and sleep quality. Risk of Bias was assessed using ROBINSE tool and RevMan 5.4 was used to analyze the results.

Results

Of the 1,450 studies subjected to screening, 33 were selected for analysis. Fourteen studies examined the association between nocturia and mortality, and 19 studies investigated impact of nocturia on sleep quality. Significant associations were found between nocturia and both mortality (pooled risk ratio: 1.78, 95% confidence interval [CI]: 1.50–2.10) and poor sleep quality (pooled odds ratio: 3.05, 95% CI: 1.89–4.93). Patients with nocturia demonstrated significantly poorer sleep quality scores compared with controls (pooled standardized mean difference: 1.01, 95% CI: 0.55–1.47).

Conclusions

This meta-analysis underscores the significance of addressing nocturia as a public health concern owing to its association with poor sleep quality and increased mortality risk. It advocates for comprehensive patient care strategies for addressing nocturia, sleep quality, and mortality.

INTRODUCTION

Nocturia, described by the International Continence Society as the need to urinate one or more times during the nighttime hours [1], is a prevalent condition affecting individuals of all ages, but predominantly impacts older adults [2]. Although often regarded as a benign inconvenience, emerging evidence suggests that nocturia may significantly increase the risk of mortality [3]. Prior studies have extensively investigated these associations independently, demonstrating that nocturia disrupts sleep and is linked to increased mortality risk. However, comprehensive analyses that integrate these dual aspects remain scarce. This meta-analysis aims to comprehensively review and synthesize existing research to explore the association between nocturia, sleep quality, and mortality, in a single framework.

Nocturia has multifactorial causes, including its association with obstructive sleep apnea (OSA). OSA contributes to nocturia through increased release of atrial natriuretic peptide during apneic episodes [4]. While OSA is a recognized risk factor for nocturia, our study focuses on the downstream effects of nocturia on sleep quality, emphasizing the importance of managing nocturia irrespective of its underlying etiology. As individuals age, the prevalence of nocturia increases, with studies reporting the occurrence of one or more episodes per night in up to 80% of individuals aged ≥80 years [2]. The implications of nocturia extend beyond mere sleep interruption. Sleep quality refers to an individual's overall satisfaction with their sleep experience, encompassing factors such as the ability to fall asleep, stay asleep, total sleep duration, and feeling refreshed upon waking [5]. Poor sleep quality has been independently linked to several adverse health conditions, including hypertension, cardiovascular disease, diabetes, and depression [6,7,8,9], all of which are associated with increased mortality risk.

While earlier research has investigated these associations separately, comprehensive analyses integrating these factors are limited. Moreover, the role of nocturia as an independent risk factor for mortality has not been extensively studied. This meta-analysis aims to address this gap by evaluating both the direct and indirect effects of nocturia on health, particularly focusing on sleep quality and mortality rates. By integrating findings from diverse cohorts, this study aimed to provide a more definitive understanding of the impact of nocturia on public health and guide the development of clinical strategies for mitigating its effects.

The main object of this study is to explore the association between nocturia and mortality, and sleep quality through the synthesis of available evidence. Specifically, we analyzed the mortality risk in individuals with nocturia compared to those without, assessed differences in sleep quality between these groups, and examined the prevalence of poor sleep quality among patients with and without nocturia. To increase the validity of our findings, we included a larger pool of studies compared to prior meta-analyses, aiming to provide a more comprehensive and definitive overview. In this systematic review and meta-analysis, we sought to answer the following question: Dose nocturia, compared to its absence, increase mortality risk and negatively affect sleep quality in adults of all ages?

MATERIALS AND METHODS

1. Search strategy

We conducted a systematic search across multiple databases, including PubMed, Embase, and the Cochrane Library, to identify relevant studies published in English from database inception to April 2, 2024. The search string used was: (nocturia OR “nocturnal polyuria” OR “nocturnal frequency” OR “night* frequency”) AND ((“sleep quality” OR “quality of sleep”) OR (mortality OR survival)).

Medical Subject Headings (MeSH) and equivalent indexing terms were applied where available to enhance the search’s sensitivity and specificity. Database-specific modifications of the search strategy, including filters for language (English) and study design, were implemented to ensure comprehensive retrieval. A detailed list of the exact search terms and strategies employed in each database has been provided as supplementary material for transparency and reproducibility (Supplement Materials 1).

Additionally, a backward citation search was performed by reviewing the references of all included studies. The protocol was registered on the PROSPERO website (CRD42024563323).

2. Inclusion and exclusion criteria

Observational studies conducted among adults, without restrictions on age, sex, or sociodemographic profile; studies that examined the associations between nocturia and two primary outcomes: mortality and sleep quality. Studies that reported sleep quality scores measured using any scale, poor sleep quality identified using any questionnaire, or mortality rates; and original research articles published in English were included in the meta-analysis. Conversely, case reports, pilot studies, reviews, letters, and editorials; studies that did not report on sleep quality scores, the prevalence of poor sleep quality, or mortality; studies that involved patients with severe comorbidities; and studies conducted among patients who were hospitalized were excluded.

3. Measurement instruments

Nocturia was measured using both validated and non-validated questionnaires, while mortality outcomes were derived from registries. To evaluate sleep quality, a variety of tools were employed, including the Pittsburgh Sleep Quality Index (PSQI), Medical Outcomes Study-Sleep Scale, Nocturia Impact Diary, Epworth Sleepiness Scale, The Assessment of Nocturnal Voiding Frequency and Daytime Consequences Diary (TANGOD), and the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance and Sleep-Related Impairment Measures. Although these instruments use Likert-type items, total scores are generally treated as continuous variables in analysis. Higher scores on these scales typically indicate poorer sleep quality.

4. Data collection and analysis

The Rayyan systematic review application [10] was used for screening and organization of studies, while RevMan 5.4 software [11] was utilized for data extraction and assessment of risk of bias. Two independent reviewers conducted the study screening, date extraction, and assessment of the risk of bias, with discrepancies resolved through consensus. The risk of bias was assessed using the Risk Of Bias In Non-randomized Studies of Exposures (ROBINS-E) tool [12]. Funnel plot analysis was employed to identify the risk of publication bias. A pooled risk ratio (RR) was used to compare the risk of mortality between patients with and without nocturia, because studies included in this outcome were cohort designs. In contrast, a pooled odds ratio (OR) was used to compare the prevalence of poor sleep quality between these groups, as the studies included were cross-sectional designs. To compare sleep quality scores, we used the pooled standardized mean difference (SMD) and a random-effects model, given the expected heterogeneity in the study settings and population characteristics. A random-effects model was employed for the forest plots to account for heterogeneity among the included studies. This model assumes that the true effect size may vary across studies due to differences in study populations, methodologies, and measurement tools. By incorporating between-study variability, the random-effects model provides more generalized pooled estimates despite study-level differences. The point estimate of the RR, OR and SMD were deemed significant if the p-value was <0.05. RevMan 5.4 [11] was used to perform all statistical analyses. The heterogeneity among studies was measured using I². Additionally, subgroup analyses were performed to explore potential sources of heterogeneity within the included studies.

RESULTS

Out of 1,450 studies screened, 82 articles with full text were retrieved for possible inclusion. Thirty-three studies were included, 14 of which provided data on nocturia and mortality [13,14,15,16,17,18,19,20,21,22,23,24,25,26], while 19 provided data on nocturia and sleep quality (Fig. 1) [27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45].

Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart of the study selection process.

The studies with data on nocturia and mortality are shown in Table 1, while the studies with data on nocturia and sleep quality are shown in Table 2. The assessment of nocturia varied from each study. The definition of nocturia also differed among the studies (i.e., 1 or more, 2 or more, 3 or more, or 4 or more episodes per night).

Table 1. Characteristics of studies with data on Nocturia and Mortality included in the meta-analysis.

Author (year)	Country or region	Study design	Final sample size (n)	Age (y)	Male (%)	Nocturia assessment (nocturia case definition)	Follow-up (y)
Åkerla et al (2022) [13]	Finland	Prospective	1,167	58±5	100	Danish Prostatic Symptom Score (3+)	24.0
Asplund (1999) [14]	Sweden	Prospective	6,143	72.8±6.4	39.5	Questionnaire (3+)	4.5
Bliwise et al (2019) [15]	United States	Prospective	7,343	63±6.7	100	International Prostate Symptom Score (3+)	4.0
Bursztyn et al (2006) [16]	Israel	Prospective	456	70	54.8	Questionnaire (2+)	12.0
Chen et al (2023) [17]	China	Prospective	13,862	45±5.8	46.6	Questionnaire (3+)	26.7
Chung et al (2014) [18]	Taiwan	Prospective	1,301	62.6±10.7	64.3	Questionnaire (3+)	2.5
Endeshaw et al (2016) [19]	United States	Prospective	1,478	73.±2.9	100	International Prostate Symptom Score (3+)	9.9
Funada et al (2020) [20]	Japan	Prospective	9,762	56.8±18.1	32.8	International Prostate Symptom Score (3+)	8.8
Galizia et al (2012) [21]	Italy	Prospective	1,288	74.2±6.3	43.0	Questionnaire (2+)	12.0
Kupelian et al (2011) [22]	United States	Prospective	15,988	49±17.5	46.6	International Prostate Symptom Score (2+)	8.8
Lightner et al (2012) [23]	United States	Prospective	2,447	51.9±13.3	100	American Urological Association Symptom Index (2+)	17.1
Moon et al (2022) [24]	Korea	Prospective	9,892	54.3±16.8	48.1	Questionnaire (2+)	10.0
Nakagawa et al (2010) [25]	Japan	Prospective	784	76±4.6	45.5	Questionnaire (2+)	5.0
Van Doorn et al (2012) [26]	Netherlands	Prospective	1,114	60.8±7.6	100	International Prostate Symptom Score (2+)	13.4

Values are presented as mean±standard deviation.

Table 2. Characteristics of studies with data on nocturia and sleep quality included in the meta-analysis.

Author (year)	Country or region	Study design	Final sample size (n)	Age (y)	Male (%)	Nocturia assessment (nocturia case definition)	Sleep quality assessment
Bliwise et al (2009) [27]	USA	Cross-sectional	1,424	55–84	42.2	Questionnaire (1+)	Questionnaire
Chang et al (2017) [28]	Taiwan	Cross-sectional	275	57.9±8.1	0	Questionnaire (2+)	Pittsburgh Sleep Quality Index
Chiang et al (2018) [29]	Singapore	Cross-sectional	199	72.8±5.5	55.8	Questionnaire (1+)	Pittsburgh Sleep Quality Index
Choi et al (2019) [30]	Hong Kong	Cross-sectional	500	57.5±9.8	42.6	Questionnaire (2+)	Pittsburgh Sleep Quality Index
Clemens et al (2020) [31]	USA	Cross-sectional	502	60.4±13.2	56.8	Bladder diary (2+)	Patient-Reported Outcomes Measurement Information System (PROMIS)
Doo et al (2012) [32]	Korea	Cross-sectional	75	63.1 ±1.7	100	International Prostate Symptom Score (2+)	Pittsburgh Sleep Quality Index
Endeshaw et al (2009) [33]	USA	Cross-sectional	244	75.8±6.4	41.7	Questionnaire (2+)	Pittsburgh Sleep Quality Index
Fung et al (2017) [34]	USA	Cross-sectional	1,520	87.6±2.9	0	Questionnaire (3+)	Questionnaire
Haddad et al (2022) [35]	Belgium	Cross-sectional	80	89 ±1.75	23.0	International Consultation on Incontinence Modular Questionnaire on Male/Female Lower Urinary Tract Symptoms Module (2+)	Targeting the individual’s Aetiology of Nocturia to Guide Outcomes Questionnaire (TANGO-D)
Hernández et al (2010) [36]	Spain	Cross-sectional	249	67±6.2	100	International Prostate Symptoms Score (2+)	Medical Outcomes Study-Sleep Scale
Huang et al (2012) [37]	Taiwan	Cross-sectional	1,011	61.5±12	46.7	International Prostate Symptom Score (2+)	Questionnaire
Martin et al (2016) [38]	Australia	Cross-sectional	729	60.7±11.65	100	American Urological Association Symptom Index (2+)	Pittsburgh Sleep Quality Index
Mittal et al (2024) [39]	India	Cross-sectional	123	31±11.1	100	International Prostate Symptom Score (4+)	Pittsburgh Sleep Quality Index
Obayashi et al (2015) [40]	Japan	Cross-sectional	1,086	71.8±7.1	47.1	Urination diary (2+)	Pittsburgh Sleep Quality Index
Rose et al (2020) [41]	Australia	Cross-sectional	202	Not reported	26.0	Questionnaire (2+)	Nocturia impact diary
Şenel et al (2022) [42]	Turkey	Cross-sectional	100	63±7.9	100	International Prostate Symptom Score (1+)	Pittsburgh Sleep Quality Index
Yang et al (2012) [43]	Taiwan	Cross-sectional	160	72.6±7.4	56.9	Questionnaire (1+)	Pittsburgh Sleep Quality Index
Yoo et al (2010) [44]	Korea	Cross-sectional	102	56.9±14.6	43.1	International Prostate Symptom Score (2+)	Epworth Sleepiness Scale
Yuen et al (2022) [45]	Hong Kong	Cross-sectional	1,239	56.9±14.6	100	International Prostate Symptom Score (1+)	Pittsburgh Sleep Quality Index

Values are presented as range or mean±standard deviation.

Fig. 2 displays the funnel plot analysis, which showed the absence of asymmetry, indicating the low likelihood of publication bias. ROBINS-E [12,46] was used to assess for the risk of bias in all included studies. The risk of bias assessments for the studies on nocturia and mortality are shown in Fig. 3, and for nocturia and sleep quality in Fig. 4. For nocturia and mortality studies, 12 of 14 assessed nocturia adequately with validated tools, and all assessed mortality through registries. All studies had some concerns for risk of bias due to post-exposure interventions, as treatments and lifestyle changes may not be uniformly applied. Twelve studies had some concerns for overall risk of bias, while two had an overall high risk. For nocturia and sleep quality studies, 13 of 19 controlled for confounding adequately, 13 of 19 assessed nocturia with validated tools, and 13 of 19 evaluated sleep quality with validated methods. Eleven of 19 studies had a low risk of bias in participant selection. Overall, three studies had a low risk of bias, eight had some concerns, and eight had a high risk of bias.

Fig. 2. (A) Funnel plot of studies with data on nocturia and mortality. (B) Funnel plot of studies with data on nocturia and sleep quality. SE: standard error, RR: risk ratio, OR: odds ratio.

Fig. 3. Risk of Bias assessment for studies on nocturia and mortality using ROBINSE (Risk Of Bias In Non-randomized Studies of Exposures) tool.

Fig. 4. Risk of Bias assessment for studies on nocturia and sleep quality using ROBINS-E (Risk Of Bias In Non-randomized Studies of Exposures) tool.

Fourteen studies were included in the analysis, all of which reported the association between nocturia on mortality. The pooled RR indicated a significant association, showing that nocturia linked to and increased risk of mortality (RR=1.78, 95% confidence interval [95% CI]: 1.50–2.10, p<0.00001). The studies showed considerable heterogeneity (I²=91%) (Fig. 5). To explore potential sources of heterogeneity, we conducted subgroup analysis based on definition of nocturia. Six studies defined nocturia as 2 or more voids per night, and the pooled RR was 1.78 (95% CI: 1.48–2.13, I²=77%). Eight studies defined nocturia as 3 or more voids per night, and the pooled RR was 1.79 (95% CI: 1.37–2.33, I²=94%).

Fig. 5. Association between nocturia and mortality. M-H: Mantel-Haenszel, CI: confidence interval.

Eight studies compared the sleep quality scores between those with nocturia and controls. The pooled SMD showed a large effect size (SMD=1.01, 95% CI: 0.55–1.47, p<0.0001), meaning their sleep quality scores are, on average, more than one standard deviation worse, indicating significantly poorer sleep quality in patients with nocturia. The studies showed considerable heterogeneity (I²=96%) (Fig. 6). Subgroup analysis based on the definition of nocturia was also conducted; however heterogeneity remained considerable.

Fig. 6. Effect of nocturia on sleep quality score. SD: standard deviation, CI: confidence interval.

Eleven studies were included, which reported the impact of nocturia on sleep quality. The pooled OR showed a significant association between nocturia and poor sleep quality (OR=3.05, 95% CI: 1.89–4.93, p<0.00001). The studies showed considerable heterogeneity (I²=90%) (Fig. 7). Similarly, subgroup analysis based on nocturia definition was also conducted, but heterogeneity remained considerable.

Fig. 7. Association between nocturia and poor sleep quality. M-H: Mantel-Haenszel, CI: confidence interval.

Sensitivity analysis showed that the results were reliable, and the observed findings on the association between nocturia and mortality, as well as nocturia and sleep quality, remained consistent (Supplement Table 1, 2, 3).

DISCUSSION

Our research highlights the importance of recognizing nocturia as a significant public health concern due to its association with diminished sleep quality and increased risk of mortality. Although several systematic reviews and meta-analyses have examined these association separately, our study is the first to investigate these associations concurrently.

Nocturia contributes to overall mortality risk, particularly through pathways related to cardiovascular diseases [17]. The nocturnal dip in blood pressure, which typically shows a 10% to 20% reduction in mean systolic blood pressure at night compared to daytime levels, is essential for maintaining cardiovascular health. A dipping of less than 10% is a risk factor for adverse cardiovascular events [47]. Disrupted sleep caused by nocturia can interfere with this critical rest period for the heart, triggering the sympathetic nervous system and imposing additional stress on the heart [40]. Furthermore, nocturia heightens the risk of falls due to frequent nighttime toileting and daytime fatigue, thereby increasing the mortality rates [21].

A meta-analysis conducted by Pesonen et al [3] and colleagues revealed that nocturia increases the risk of death by 1.3 times. Their subgroup analysis indicated that this association between nocturia and mortality is more pronounced in younger populations, with no notable increase in mortality observed for those aged ≤40 years. The risk was particularly higher in those in their 50s or 60s compared with those aged ≥70 years [3]. Age has been identified as a factor influencing the prevalence and impact of nocturia, as well as its associations with mortality and sleep quality. This trend is hypothesized to stem from the compounding effects of comorbidities and other age-related risk factors that may overshadow the independent impact of nocturia in older populations.

While our meta-analysis included studies encompassing diverse age groups, we did not perform a subgroup analysis stratified by age due to limitations in the availability of detailed age-specific data in the included studies. This represents a significant limitation and future research should include these age-specific dynamics to better inform age-appropriate management strategies for nocturia.

In contrast to Pesonen et al’s study [3], our meta-analysis incorporated additional studies and assessed the impact of nocturia on sleep quality. Meanwhile, Pesonen et al [3] focused exclusively on mortality, our analysis found that nocturia linked to a 1.78-fold increase in mortality risk and a 3.05-fold increase in the risk of poor sleep quality.

Endeshaw et al [19] demonstrated that nocturia is associated with increased mortality hazard ratio of 1.21, even after adjusting for insomnia and sleep quality. They also observed a higher risk among patients with cardiovascular diseases and diabetes. Similarly, Bliwise et al [15] reported a 1.72-fold higher mortality risk in individuals with nocturia, which decreased to 1.43-fold after adjusting for sleep quality. This result suggests that sleep quality has a higher impact on the association between nocturia and mortality than expected. Another study indicated that a shorter sleep duration increases the mortality risk among patients with cardiovascular or cerebrovascular risk factors or diseases, but not among those without such risk factors or diseases [48]. This underscores the importance of addressing poor sleep quality, particularly in patients with cardiovascular or cerebrovascular diseases or related risk factors.

A recent investigation showed that lower urinary tract symptoms (LUTS), including nocturia and particularly urgency, were significantly linked to an increased risk of mortality even after controlling for age, comorbidities, and other confounding variables [13]. This finding indicates that although comorbidities largely account for the association between LUTS and mortality, the persistence of this association even after adjusting for age and comorbidity suggests that other, currently unidentified factors contributing to the risk of death are also at play.

This meta-analysis has several limitations that need to be acknowledged. The substantial heterogeneity across the studies highlights notable variations in study populations, methodologies, and measurement tools, limiting the generalizability of our results. Such variability is a common challenge in observational studies, given the differences among populations, settings, and methodologies. The lack of randomized controlled trials among the included studies means that our conclusions are based on observational data, which carry a susceptible to bias and confounding factors. Nevertheless, observational data offer benefits over randomized trials in terms of the volume of data that can be synthesized and their applicability to the general population. Certain clinical outcomes, such as those in the current study, are only feasible to investigate through observational designs. Another limitation is the use of diverse instruments to measure sleep quality and varying definitions of nocturia across the included studies. The inclusion of studies utilizing nonvalidated questionnaires may introduce measurement bias. However, sensitivity analyses demonstrated that excluding these studies did not significantly alter the pooled estimates.

The cross-sectional nature of the included studies limits our ability to determine whether sleep disturbances are a cause or consequence of nocturia. Frequent awakenings due to nocturia likely fragment sleep, but pre-existing sleep disorders such as insomnia may also exacerbate nocturia. Additionally, insomnia may act as a confounder, independently contributing to mortality, or as a mediator, amplifying nocturia’s effects on health outcomes. Future longitudinal studies are needed to clarify these relationships and disentangle the roles of insomnia as a confounder or mediator.

These limitations suggest a need for cautious interpretation of the results and emphasize the importance of future research to address these issues by prioritizing the use of validated instruments to enhance reliability. Given these constraints, our aim is to summarize the presence and direction of associations between variables rather than provide an exact effect estimate.

Considering these insights, we must recognize the multidimensional nature of nocturia and advocate for a comprehensive management approach. Future research should prioritize the interactions; mediating factors; and interplay between nocturia, sleep quality, and mortality. Consideration should be given to confounding variables such as cardiovascular risk factors, cardiovascular disease, diabetes, lifestyle and socioeconomic status, and medication use. Investigations should delve into these interconnections and assess the potential benefits of targeted therapeutic interventions.

CONCLUSIONS

Our meta-analysis underscores the significant impact of nocturia on sleep quality and mortality. This emphasizes the importance of implementing integrated patient care strategies and serves as an impetus for further research efforts in this crucial area of healthcare.

Supplementary Materials

Supplementary materials can be found via https://doi.org/10.5534/wjmh.240237.

Supplement Materials 1

Search strategy

Supplement Table 1

Sensitivity analysis on the association between nocturia and mortality

Supplement Table 2

Sensitivity analysis on the effect of nocturia on sleep quality score

Supplement Table 3

Sensitivity analysis on the association between nocturia and poor sleep quality