Daytime Nap and Depression Risk: a meta-analysis of observational studies

doi:10.21203/rs.3.rs-1738555/v1

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Daytime Nap and Depression Risk: a meta-analysis of observational studies

https://doi.org/10.21203/rs.3.rs-1738555/v1

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Background: Relationship between daytime napping and the risk of depression remains debatable. Thus, a meta-analysis in this study was conducted to evaluate the relationship between daytime napping and the depression risk.

Methods: PubMed, Embase, Web of Science and China National Knowledge Infrastructure databases were searched through up to February 2022, and the reference lists of the included studies were also retrieved. A random-effects model was used to estimate the combined effect size.

Results: Nine studies with 649,111 participants were included in the final analysis. The pooled odd ratio (OR) was 1.15 (95% confidence interval: 1.01-1.31) with a significant heterogeneity (I²=91.3%, P for heterogeneity < 0.001), and the results demonstrated an increasing risk of depression were observed among daytime nappers. Visual inspection of funnel plot, Egger’s and Begg’s tests identified no obvious evidence of publication bias.

Conclusion: This meta-analysis indicates that daytime nap plays a predictor for depressive symptom. These findings might obtain important implications for depression prevention.

Daytime nap

Depression

Meta-analysis

Depression is a common and disabling psychiatric condition world-wide [1, 2], and it is a syndrome consisting of a variety of symptoms (such as depressed mood and loss of interest) [3]. The etiology of depression is complex resulting from interactions between biological vulnerabilities and environmental factors [4]. According to data from the Global Burden of Disease Study 2019, depressive disorders were the leading causes of burden worldwide with a higher prevalence than other diseases [5]. The World Health Organization (WHO) has estimated that depression will become the top cause of global disease burden in 2030 [6]. As one of the most widespread diseases affecting mental, physical and social well-being, depression is receiving increasing attention.

Daytime nap is a short sleep during daylight hours [7], and it is a habitual behavior in many regions around the world, such as Asia, Central America and the Mediterranean region [8]. In some countries, especially those with a nap culture, daytime napping is often considered as a healthy lifestyle [9, 10]. Some studies have shown that short naps are beneficial to increase alertness [11–13], motor skills [14, 15], and cognitive performance [16–18]. Conversely, other researchers have noted that daytime napping is associated with an increased risk of obesity [19], chronic diseases [20, 21] and all-cause mortality [22]. Some studies suggested that the effect of daytime napping was related to age and the duration of the nap. Yamada et al. indicated that long daytime napping could cause sleep inertia and it was associated with a higher risk of cardiovascular disease and all-cause mortality compared with not napping [7]. Leng et al. found that daytime napping significantly increased C reactive protein levels among participants over 70 years old [23].

Sleep is fundamental to a person’s emotional and physical health [2, 24]. Many studies suggested that a series of sleep problems, including obstructive sleep apnea, circadian disorder, insomnia, excessive daytime sleepiness, were associated with the risk of depression [25–27]. Biological mechanisms between daytime napping and the risk of depression are confused; we are not sure whether napping is a beneficial, detrimental, or neutral to our health [28]. Choi et al. [29] found that daytime napping was appeared to increase the risk of depressive symptoms. On the contrary, the study by Bao et al. [30] suggested that daytime napping was a protective factor for depression. To date, meta-analysis assessing the association of daytime napping and the risk of depression is unavailable. Thus, we conducted a meta-analysis to investigate the effects of daytime napping on depression.

Literature search strategy

This meta-analysis was conducted following the checklist of the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines [31]. We systematically searched the PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases from their inception to February 2022 for studies describing an association between daytime napping and the risk of depression. We used the following keywords “snooze” or “siesta” or “daytime napping” or “noontime nap” or “midday nap” or “noontime snooze” or “noontime nap” in combination with “depression” or “depressive symptom” as search terms. In addition, all reference articles listed were reviewed. The search was applied without language restriction.

Inclusion and exclusion criteria

Studies were included if they fulfilled the following criteria: (1) the exposure of interest was daytime napping; (2) the outcome of interest was depression; (3) the study provided the risk estimates such as relative risks (RR) or odds ratios (OR) with corresponding 95% confidence intervals (CIs) or sufficient data to calculate them; (4) observational studies were included, i.e. cohort studies, cross-sectional studies, and case-control studies.

Studies were excluded if: (1) publications which were not full reports; (2) duplicate studies; (3) studies on excessive daytime sleepiness rather than daytime napping; (4) inadequate information to calculate risk estimates. Two reviewers (Q.Z and D.Y) independently reviewed all studies by title or abstract or full text. Disagreements were resolved through consultation with the third reviewer (C.M.W).

Data extraction

The follow information for each included study was extracted: first author’s name, publication year, country, study design, follow-up year (only for cohort studies), age range or mean age of the participants (at baseline for cohort studies), gender, sample size, daytime napping definition and measurement, depression definition and measurement, adjusted covariates, and effect estimates with their corresponding 95% CI. Data extraction was conducted independently by two authors (K.J.Z and Q.Z).Interobserver agreement was assessed using Cohen kappa (κ) and any disagreements were resolved by discussion with the third author (Z.X.L.).

Quality assessment

The included studies’ methodological quality independently assessed by two reviewers ( L.Q.L and G.H.Z ) with appropriate tools. We used the Newcastle-Ottawa Scale (NOS) [32] for assessing the quality of cohort studies and case-control studies. The NOS includes eight items grouped into selection, comparability and outcome, each study would be assigned a score of 0-9. A NOS score more than 6 is relatively high quality, 5-6 is medium quality and less than 5 is low quality. The Agency for Healthcare Research and Quality (AHRQ) methodology checklist was applied to evaluate cross-sectional studies. The AHRQ checklist includes 11 items. We assigned scores as follows: 0-3 = low quality, 4-7 = moderate quality and 8-11 = high quality.

Statistical analysis

The OR was considered as the common measure of the association between daytime nap and depression. The multivariable adjusted ORs were preferentially pooled when such estimates were reported. If adjusted analysis was unavailable, the unadjusted estimate would be pooled. The fixed-effect model was applied when heterogeneity was not detected, otherwise the random-effects model was used to summary ORs for the association between daytime napping and depression. For further confirmation and assessment of the association between daytime napping and the risk of depression, subgroup analysis was carried out to explore the sources of potential heterogeneity and examine the robustness of the primary results. The differences among subgroups were tested by meta-regression analysis (using STATA ‘metareg’ command). Statistical heterogeneity among studies was evaluated with the I² statistics, where values of 25%, 50%, and 75% represented cut-off point for low, moderate, and high degrees of heterogeneity, respectively. Potential publication bias was evaluated with a funnel plot, the Begg’s test and the Egger’s test.

Literature search

The process of study screening on the PubMed, Embase, Web of science and China National Knowledge Infrastructure databases and the reference lists of the included studies retrieved total 5,337 studies. After the eliminating of duplicated publications and the screening of titles and abstracts, 71 articles were considered. At the full text review stage, 9 studies were eventually included in the meta-analysis. All steps and the reasons for exclusion are shown in Figure 1.

Study characteristics

The characteristics of included 9 studies [29,30,33-39] are shown in Table 1. Our studies included 649,111 individuals, and the sample size of these studies ranged from 1,497 [37] to 512,891 [39]. Most of the included studies [29,30,33-35,37-39] were published since 2014, only one study [36] was published before 2014 (in 2007). Four [29,34,37,38] were cohort studies, and 5 [30,33,35,36,39] were cross-sectional studies. Of these included cohort studies, the lengths of follow-up years ranged from 1 year [37,38] to 17 years [34], and the sample sizes ranged from 3,075 [38] to 118,373 [29]. Four studies [30,37-39] were conducted in China, 2 studies [33, 36] in North America, and 3 studies [29,34,35] in Europe. All included studies [29,30,33-39] provided self-reported daytime napping only, and only two of the included studies [30,39] reported results for males and females separately. The results of the quality assessment are shown in Table 2 and Table 3. All studies were moderate or high quality according to the NOS or AHRQ scores.

Quantitative synthesis

Figure 2 shows the pooled results from the random-effect model and ORs of the included studies. Among these included studies, five studies reported a positive relationship between daytime nap and the risk of depression [35-39]. The pooled OR was 1.15 (95% CI: 1.01-1.31). The result showed a positive association of daytime nap and the risk of depression with a high level of heterogeneity (I²= 91.3%, P<0.001).

Subgroup analysis

Subgroup analyses were conducted by study design, daytime nap category, depression measurement, sample size, study quality, study location and drinking status and sleep duration controlled or absent in the models (Table 4). As a lack of the insufficient information, napping could not be divided by the duration. Instead, nap was categorized by the timing as afternoon napping or napping without definite timing. Afternoon napping was at afternoon or after lunch, while napping without definite timing was without definite time. The results of subgroup analyses indicated that the diverse definitions of daytime nap might be a source of heterogeneity. Napping in the daylight was significantly associated with an increased risk of depression while afternoon nap showed no significant association.

Sensitivity analysis

Sensitivity analysis was adopted to identify the potential sources of the heterogeneity in the association between daytime nap and depression risk. This helped examine the influence of various exclusions on the combined OR and test the stability of the quantitative synthesis results. The pooled OR ranged from 1.07 (95% CI, 0.91-1.27) to 1.15(95% CI, 1.00-1.34) when one study was omitted in turn. The leave-one-out analysis indicated that none of the individual studies significantly influenced the overall result.

Publication bias

Visual inspection of the funnel plot did not reveal any significant asymmetry (Figure 3). The Egger’s and the Begg’s tests indicated no obvious publication bias among the studies (Egger’s test t = -0.41, P = 0.693; Begg’s test z =- 0.42, P = 0.677).

This study is the first meta-analysis on the association between daytime nap and depression risk. Such researches, only one of nine studies included were published before 2017, suggesting the growing attention to the effects of daytime nap in recent years. The pooled results (OR = 1.15; 95% CI: 1.01–1.31) indicated that nappers were more likely to develop depression than non-nappers.

Although a high heterogeneity was observed in the meta-analysis, meta-regression analysis showed that the definition of daytime nap explained most potential heterogeneity. Based on the previous studies [10, 40], people choose to take naps for a variety of reasons such as appetitive napping for enjoyment, naps in response to sleep loss and napping in preparation for sleep loss. Milner et al. noted that individuals’ levels of experience with napping lead to different impact [41]. This was consistent with the results of our subgroup analysis studies which based on study location. As napping was not customary in areas such as the USA and Canada, daytime napping was significantly associated with an increased risk of depression in South American. Due to insufficient information in the original studies, we grouped the naps in one way only, i.e. afternoon naps or naps without definite timing. Subgroup analysis showed that naps without definite timing were significantly associated with an increased risk of depression. An afternoon nap trended to increase risk of depression, but the association was not statistically significant. In a cross-sectional study [30], a nap after lunch was a protective factor against depression. Research by Liu et al. showed that a nap during the day increased the risk of depression [39]. These results suggested that different timing of naps could have different effects on depression. However, information is not enough to categorize naps in details, and as well to explore the different effects of various types of naps upon depression and their mechanisms.

It was observed that the daytime nap effects on health might differ in age and duration. A cohort study on people under the average age of 40 found that daytime nap did not increase the risk of depression, although the association was not statistically significant [34]. Simoes Maria et al. had shown that daytime napping was significantly associated with an increased risk of depression in people over 60 years old [35]. Some studies indicated that long daytime napping might increase the risk of cardiovascular diseases, chronic diseases and mortality in older people [40, 42, 43], and long daytime nap could cause sleep inertia which had a detrimental effect to people [7, 23]. However, we did not carry out a subgroup analysis by age or the duration of naps, because only some of the included literature reported the duration of naps, and there were different groups regarding nap duration and the most participants were older adults. It is common for epidemiological studies as there is no standard way of assessing napping in current studies, and self-reported sleep questions are usually used. Some research [30, 44] had shown that self-reported naps did not increase the risk of depression. Due to memory biases, self-reports of daytime naps are unreliable and nap details are unlikely to be reported. Therefore, more studies using objective measures to detect naps are needed so that objective naps could be determined with definite and detailed information, such as duration, frequency and timing.

The underlying biological mechanisms between daytime nap and risk of depression are still unknown. Previous studies indicated that the association between daytime nap and depression was attributed to disturbed sleep, such as insomnia, excessive daytime sleepiness and sleep apnea [45, 46]. In other words, studies suggested that these previously mentioned sleep disorders increased the risk of depression. And the side effect of antidepressant therapy such as insomnia and hypnosia might cause daytime napping [47]. However, it is still unclear whether daytime nap is a consequence of sleep disorders. In addition, depression has been suggested as a cause of daytime napping, with one might be explanation that daytime nap is a common symptom among depressive patients.

Strengths and limitations

Such meta-analysis in this study highlights synthesized effects of daytime napping on the risk of depression in an international public publication for the first time. First, it included a total of 648,711 participants from 6 countries in Europe, Asia and North America. A large sample size and wide areas significantly increased the statistical power and generalization of the associations between daytime napping and the risk of depression. Second, four cohort studies were included, which could provide longitudinal evidence for the demonstration of temporal relationships between daytime nap and the risk of depression. Third, all included studies were moderate or high quality with more convincing results.

Some potential limitations in this study should also be discussed. First, five of the nine original studies included were cross-sectional studies. Only longitudinal studies can demonstrate the effect of a risk factor (i.e. daytime nap) on health conditions (i.e. depression). Second, the original study information was insufficient to make a distinction between the definition and types of napping. Different types of nap could have different relation to or effects on health status according to available studies. Thus, the summary could not independently made about the relationship between various types of naps and depression risk. Third, the recall bias and measurement error are unavoidable the application of self-reported questionnaires rather than actigraphies to observe the association between daytime nap and depression. But self-reported naps were usually accepted without feasibility to measure naps using actigraphies in large epidemiological studies. Fourth, although each included study had various adjusted confounding factors, some important confounding factors were not fully adjusted, which might influence the association of daytime nap and depressive risk. Therefore, the results in this study were extracted with the full adjusted covariates.

Based on meta-analysis results, this study found there were few longitudinal studies on nap and depression and future studies should focus more on the causal and temporal relationships between nap and depression. In addition, researchers should pay special attention to the duration, timing and frequency of naps and explore their effects on depression with probably distinct biological mechanisms.

In summary, the meta-analysis demonstrates that daytime napping is likely to increase the risk of depression. Considering the increasing prevalence of depression in modern society, findings have important implications in depression prevention.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

No fund.

Authors' contributions

CMW and LQL conceived the study. GHZ, HWH, JZG, XRK, SLY, DY and ZSC were responsible for collection and cleaning of the data, and assisted the writing of the manuscript. LQL and QZ wrote the manuscript. LYZ, YG and ZXL contributed to review and revision of the study. CMW is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Acknowledgements

Not applicable.

Authors' information

Not applicable.

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Table 1 is available in the Supplementary Files section

Table 2 Quality assessment of included cohort studies
Original studies	Selection					Comparability	Outcome				Total score
Original studies	1) Representativeness of the exposed cohort	2) Selection of the non exposed cohort	3) Ascertainment of exposure		4) Demonstration that outcome of interest was not present at start of study	1) Comparability of cohorts on the basis of the design or analysis	1) Assessment of outcome	2) Was follow-up long enough for outcomes to occur		3) Adequacy of follow up of cohorts	Total score
Ruiz-Estigarribia et al., 2019	1	1		0	1	1	1	1	1		7
Choi et al., 2020	1	1		0	1	1	1	1	0		6
Jing et al., 2020	1	1		0	0	1	1	0	1		5
Liu et al. 2021	1	1		1	1	1	1	0	1		7

Table 3 Quality assessment of included cross-sectional studies
Original studies	1)	2)	3)	4)	5)	6)	7)	8)	9)	10)	11)	Total score
Foley et al. 2007	1	1	1	0	0	1	1	1	0	1	0	7
Leblanc et al. 2015	1	1	1	0	0	1	1	1	0	0	0	6
Liu et al. 2018	1	1	1	1	0	1	0	1	0	0	0	6
Simoes Maria et al. 2019	1	1	1	1	0	1	1	0	0	1	0	7
Xie et al. 2020	1	1	1	1	0	1	1	1	0	0	0	7

1) Define the source of information (survey, record review).

2) List inclusion and exclusion criteria for exposed and unexposed subjects (cases and controls) or refer to previous publications.

3) Indicate time period used for identifying patients.

4) Indicate whether or not subjects were consecutive if not population-based.

5) Indicate if evaluators of subjective components of study were masked to other aspects of the status of the participants.

6) Describe any assessments undertaken for quality assurance purposes (e.g., test/retest of primary outcome measurements).

7) Explain any patient exclusions from analysis.

8) Describe how confounding was assessed and/or controlled.

9) If applicable, explain how missing data were handled in the analysis.

10) Summarize patient response rates and completeness of data collection.

11) Clarify what follow-up, if any, was expected and the percentage of patients for which incomplete data or follow-up was obtained.

Table 4 Subgroup analysis of odd ratios for the association between daytime napping and depression
		No of studies	OR (95% CI)	I² (%)	P value for heterogeneity	P value between groups
study location
	Asia	4	1.01(0.80,1.27)	94.4	<0.001	0.334
	North America	2	1.57(0.84,2.94)	85.1	0.010
	Europe	3	1.20(0.99,1.45)	86.5	0.001
daytime napping definition
	afternoon nap	4	0.95(0.76,1.19)	94.6	<0.001	0.036
	nap without definite timing	5	1.36(1.19,1.55)	58.2	0.048
type of depression measure
	self-reported scales	6	1.08(0.92,1.25)	92.8	<0.001	0.458
	physician diagnosis	3	1.38(0.94,2.04)	91.0	<0.001
sample size
	<10000	6	1.15(0.93,1.42)	93.0	<0.001	0.688
	>10000	3	1.17(0.96,1.42)	85.5	0.001
study design
	cross-sectional	5	1.28(0.96,1.71)	90.9	<0.001	0.483
	cohort	4	1.08(0.93,1.24)	90.8	<0.002
source of participants
	general period	8	1.20(1.06,1.37)	90.7	<0.001	0.067
	special period	1	0.75(0.60,0.93)	-	-
controlling drinking
	adjusted	3	1.10(0.86,1.41)	95.1	<0.001	0.923
	unadjusted	6	1.19(0.97,1.46)	89.0	<0.001
controlling sleep duration
	adjusted	3	1.94(0.73,1.21)	84.9	0.001	0.08
	unadjusted	6	1.25(1.12,1.40)	80.6	<0.001

No competing interests reported.

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Daytime Nap and Depression Risk: a meta-analysis of observational studies

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