The joint association between sleep quality, moderate-to-vigorous physical activity , cardiorespiratory fitness, and working memory in Chinese adolescents

The joint association between sleep quality, moderate-to-vigorous physical activity , cardiorespiratory fitness, and working memory in Chinese adolescents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The joint association between sleep quality, moderate-to-vigorous physical activity , cardiorespiratory fitness, and working memory in Chinese adolescents jun hong, Yuan Liu, Yaru Guo, YuQiang Li, Feng Zhang, Pengwei Sun, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5772463/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jul, 2025 Read the published version in BMC Public Health → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Poor sleep quality is a prevalent health concern among Chinese adolescents. Although significant focus has been given to the impact of sleep problems on cognitive function, research on the association between sleep quality and working memory in typically developing adolescents remains limited. The aim of this study is to examine this association in Chinese adolescents. Methods: The present study randomly recruited 2428 adolescents aged 12-18 years from four schools in Shanghai and Suzhou, eastern China in 2023 through two-stage cluster sampling. Information on sleep quality was collected using the questionnaire (Pittsburgh Sleep Quality Index). Adolescents’ working memory was evaluated using the N-back task. A general linear regression analysis was conducted to evaluate the association between sleep quality and working memory, adjusted for potential confounders. Interaction terms, representing the product of sleep quality and each modifier, were included to test for interaction effects. Results: In the adjusted model, adolescents with good sleep quality served as the reference group. Those with poor sleep quality had increased reaction times by 0.11 seconds (95% CI :0.09-0.13) during the 1-back task and by 0.10 seconds (95% CI :0.08-0.12) during the 2-back task. Moderate-to-vigorous physical activity (MVPA) time, cardiorespiratory fitness (CRF) and age significantly modified the associations between sleep quality and working memory ( P for interaction<0.05). Conclusions: Chinese Adolescents with poor sleep quality exhibited worse working memory, particularly among those who were younger, had insufficient MVPA time, and lower CRF. Good sleep quality is significant in improving cognition function among Chinese adolescents. Chinese adolescents cross-sectional studies effect modification sleep quality working memory Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Sleep quality is crucial for maintaining normal functioning of both cerebral and somatic systems, and is increasingly recognized as an important lifestyle contributor to physical and psychological health. However, an increasing number of people are now experiencing poor sleep quality due to stress or psychological issues. Studies indicated that approximately one-third of children [ 1 ] , 32.8% of adults [ 2 ] , and 60% of elderly individuals [ 3 ] suffer from poor sleep quality. Additionally, in 2019, it was estimated that sleep disorders affected 176 million Chinese individuals, positioning China as the nation with the greatest global burden of sleep-related issues [ 4 ] . Poor sleep quality might result in a multitude of medical conditions, such as cardiovascular disease [ 5 ] , obesity [ 6 ] , neurocognitive decline [ 7 , 8 ] . Working memory is thought to be a cognitive system for on-line storage and processing of information in the service of the current task [ 9 ] . Working memory emerges during the primary school stage and continues to develop throughout adolescence [ 10 ] . Sleep grants our brain an interval devoid of heavy informational input, enabling the classification, structuring, and stabilization of recently formed memories [ 11 ] . Sleep quality has been reported to affect specific brain structures that have a high correlation with working memory [ 12 , 13 ] . Therefore, it is plausible to speculate about the adverse effects of poor sleep quality on the performance of working memory. However, prior research focused primarily on exploring the association between sleep and working memory in atypical samples. For instance, Sciberras et al. reported a significant relationship between behavioral sleep issues and working memory performance among children with ADHD aged 5–13 [ 14 ] . Similarly, McCann et al. discovered associations between poor sleep quality and verbal working memory deficits in children with neurological conditions [ 15 ] . In another study among children aged 3–5 years, parents’ reports of elevated risk of sleep-disordered breathing were linked to impaired working memory [ 16 ] . Moreover, Lau et al. found that compared to healthy children, those with obstructive sleep apnea exhibited worse working memory performance [ 17 ] . Interestingly, prior studies on the association between sleep quality and working memory in typical samples yielded inconsistent conclusions. A study revealed that poor sleep quality was an independent predictor of reduced working memory capacity among college students [ 18 ] . However, a similar study conducted among adolescents found no significant association between sleep duration (assessed through actigraphy) and working memory [ 19 ] . The inconsistencies might stem from variations in sleep measurement methods and sample diversity across studies (e.g., age ranges from infants to adults, and populations spanning healthy to atypical groups). To our knowledge, the present study is the first large sample to investigate the association between sleep quality and working memory in typically developing Chinese adolescents. If poor sleep quality contributes to worse working memory among adolescents, improving sleep quality may serve as a viable intervention to enhance cognitive performance. Furthermore, our previous studies identified several factors linked to working memory. Specifically, we observed that increased consumption of sugar-sweetened beverage (SSB) is associated with worse working memory [ 20 ] . Adolescents with higher levels of cardiorespiratory fitness (CRF) demonstrated enhanced working memory capabilities [ 21 ] . Additionally, adolescent obesity correlated with poorer working memory performance [ 22 ] . A review suggested that insufficient physical activity might exacerbate the negative impact of poor sleep on cognitive function [ 23 ] . However, interactions among these factors, sleep quality, and working memory remain unclear. Therefore, the primary objective of this study is to investigate the association between sleep quality and working memory in Chinese adolescents. We explored whether age, gender, SSB consumption, MVPA time, CRF, and BMI moderate the association between sleep quality and working memory. 2. Methods 2.1 Participants and study design The sample recruitment process involved two stages of cluster sampling. Firstly, from September to November 2023, this study randomly selected two cities (Shanghai and Suzhou) from eastern China to conduct a cross-sectional study. Subsequently, random selection was conducted in each city, picking one junior high school and one high school, resulting in a total of four schools. Finally, this study invited all students from these four schools to participate. The inclusion criteria were as follows: (1) Chinese adolescents with an IQ score above 90, as assessed using the Wechsler Intelligence Scale; (2) free from neurological diseases or other severe injuries; (3) without experiencing negative psychological emotions. The present study invited a total of 2694 Chinese adolescents from the four selected schools, and 170 adolescents were excluded due to failure to meet inclusion criteria or incomplete informed consent. A total of 96 adolescents were excluded due to incomplete data on sleep quality or working memory. Finally, 2428 participants were included in the final sample size (Figure 1). This study was approved by the Human Experiment Ethics Committee of East China Normal University (HR761-2022) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all the participants and all parents of the participating children before their involvement in the study. 2.2 Assessment of sleep quality The sleep quality of participants was assessed using the Pittsburgh Sleep Quality Index (PSQI), which evaluated participants’ sleep quality over the past month. Each item was scored on a 0-3 scale, and the total PSQI score was obtained by summing up the scores of all items. A higher PSQI score indicated poorer sleep quality, and the PSQI score of 5 or below was considered to indicate good sleep quality, while a score above 5 is considered to indicate poor sleep quality [24] . In this study, the Cronbach's alpha coefficient for the PSQI score was 0.762, indicated high reliability. Additionally, the confirmatory factor analysis yielded satisfactory results, demonstrating high validity. 2.3 Assessment of working memory The working memory of participants was evaluated using the N-back task via the E-prime 1.1 software system. The assessment required participants to complete the task in a quiet environment. The results of the N-back task indicated the reaction time and accuracy during the assessment, with a longer reaction time indicating worse performance in the participants’ working memory. The details of the assessment process of N-back task were described in our previous study [21] . 2.4 Confounders A self-administered questionnaire collected information on the following potential variables: participants’ age (years), participants’ gender (boys, girls), sugar-sweetened beverage consumption (SSB consumption, <1 times/week, 1-4 times/week, ≥5 times/week) by the question “How many times did you consume sugar-sweetened beverages during the past week?”, moderate-to-vigorous physical activity time (MVPA time, <70 min/day, ≥70 min/day) [25] . Additionally, the study measured participants’ BMI and classified it into obesity and normal groups based on the WHO standard [26] . The participants' cardiorespiratory fitness (CRF) was evaluated by the 20-meter shuttle run (20m SRT) and divided into high, moderate and low groups categories. The details of the assessment process of 20m SRT and CRF were described in our previous study [21] . We drew a directed acyclic graph (DAG) with the aim of determining the most parsimonious set of confounding variables [27] (Figure 2). Finally, we adjusted the following confounding variables in the primary model: age, gender, SSB consumption, MVPA time, and CRF. 2.5 Statistical analysis For continuous data, the present study used the independent samples t test, and the results were expressed using means and standard deviations (Mean ± SD). For categorical data, the present study used the Chi-square test to compare sleep quality in different categories, and the results were expressed by percentage. The present study took good sleep quality as the reference and conducted general linear regression to assess the association between sleep quality and working memory among Chinese adolescents. We used two models: the crude model (without adjustment) and the adjusted model (after adjusting for confounders such as age, gender, SSB consumption, MVPA time, BMI, and CRF). For adolescents with poor sleep quality, the present study assessed the associations between the PSQI score (as a continuous variable) and working memory. Due to the right-skewed distribution of the PSQI scores, we applied a natural logarithm (LN) transformation to the PSQI scores of adolescents with poor sleep quality. The present study further calculated for multiple comparisons to correct the false discovery rate (FDR), and when FDR was less than 0.05, we considered the result significant [28] . Additionally, the present study investigated the effect modification of various factors, including gender (boys vs girls), age (12-15years vs 16-18 years), SSB consumption (0 time/week vs ≥1 times/week), MVPA time (<70 min/day vs ≥70 min/day), BMI (normal vs obesity), CRF (moderate-high vs low). We tested for interaction by incorporating an interaction term in the adjusted model, which was the product of sleep quality and a modifier. When P for interaction less than 0.05, the covariate was considered to exhibit effect modification. Furthermore, we calculated the subgroup-specific estimates of the effect by conducting stratified analyses within each subgroup. Data was analyzed using SPSS software (version 24.0; IBM Corp) and R (version 4.4.1; R Development Core Team) for data analysis. All statistical P -values less than 0.05 (two-sided) were considered as statistically significant. 3. Result 3.1 Description of study participants Table 1 showed the study population characteristics. Among 2428 Chinese adolescents, 1264 (52.1%) were boys with an average age of 14.6 years old. A total 37.8% adolescents exhibited poor sleep quality, while 62.2% adolescents exhibited good sleep quality. Compared to adolescents with good sleep quality, those with poor sleep quality were more likely to be older and girls, and had less MVPA time, higher SSB consumption, and lower CRF (all p -values <0.05). Table 1. Study population characteristics according to sleep quality Characteristic Total sample Sleep quality P -values Good Poor N(%) 2428 1510(62.2) 918(37.8) Age, years (mean ± SD) 14.6 ± 1.8 14.4 ± 1.8 14.8 ± 1.7 <0.0001 BMI, kg/m 2 (mean ± SD) 21.2 ± 4.3 21.4 ± 4.0 0.456 RT for working memory 1-back, seconds (mean ± SD) 0.80 ± 0.22 0.76 ± 0.19 0.88 ± 0.23 <0.0001 2-back, seconds (mean ± SD) 1.11 ± 0.22 1.02 ± 0.22 1.13 ± 0.20 <0.0001 Gender, n (%) <0.0001 Boys 1264 (52.1) 830 (55.0) 434 (47.3) Girls 1164 (47.9) 680 (45.0) 484 (52.7) SSB consumption, n (%) 0.001 0 times/week 1376 (56.7) 891 (59.0) 485 (52.8) 1-4 times/week 679 (28.0) 415 (27.5) 264 (28.8) ≥5 times/week 373 (15.4) 204 (13.5) 169 (18.4) MVPA time, n (%) 0.026 <70min/day 1685 (69.4) 1029 (68.1) 656 (71.5) ≥70min/day 743 (30.6) 481 (31.9) 262 (28.5) CRF, n (%) high 582 (24.0) 391 (25.9) 191 (20.8) 0.007 moderate 1242 (51.2) 766 (50.7) 476 (51.9) low 604 (24.9) 353 (23.4) 251 (27.3) Abbreviations: RT, reaction time; SSB, sugar-sweetened beverage; MVPA, moderate-to-vigorous physical activity; BMI, body mass index; CRF, cardiorespiratory fitness 3.2 Association between sleep quality and working memory Table 2 presented the association between sleep quality and working memory. The sleep quality was significantly associated with working memory among Chinese adolescents. Specifically, in the adjusted model, adolescents with poor sleep quality demonstrated significantly longer reaction time for both the 1-back and 2-back tasks compared to adolescents with good sleep quality (all p -values <0.05). Table 3 showed the association between PSQI score and working memory. When analyzing only adolescents with poor sleep quality, the analysis revealed that an increase in the logarithmic PSQI score was associated with increased in reaction time for the 1-back and 2-back tasks (all p -values < 0.05). Table 2. The linear regression of sleep quality and working memory (n=2824) Working memory Crude model Adjusted model a Estimates 95% CI p ­values FDR Estimates 95% CI p -values FDR 1-back task Good sleep quality Reference Reference Poor sleep quality 0.12 0.10, 0.13 <0.0001 <0.0001 0.11 0.09, 0.13 <0.0001 <0.0001 2-back task Good sleep quality Reference Reference Poor sleep quality 0.11 0.10, 0.13 <0.0001 <0.0001 0.10 0.08, 0.12 <0.0001 <0.0001 a Adjusted for age, gender, sugar-sweetened beverage consumption, moderate-to-vigorous physical activity time, BMI, and cardiorespiratory fitness Table 3. The linear regression of PSQI score and working memory for adolescents with poor sleep (n = 918) Working memory Crude model Adjusted model a Estimates 95% CI p ­values FDR Estimates 95% CI p -values FDR 1-back task 0.08 0.06, 0.09 <0.0001 <0.0001 0.07 0.05, 0.08 <0.0001 <0.0001 2-back task 0.07 0.06, 0.09 <0.0001 <0.0001 0.06 0.05, 0.08 <0.0001 <0.0001 a Adjusted for age, gender, sugar-sweetened beverage consumption, moderate-to-vigorous physical activity time, body mass index, and cardiorespiratory fitness 3.3 Effect modification We found that age, MVPA time and CRF modified the association between sleep quality and the 1-back and 2-back tasks ( P for interaction <0.05, respectively). Figure 3 demonstrated the difference in reaction time for the 1-back task between adolescents with good sleep quality (reference group) and those with poor sleep quality across subgroups. Specifically, among adolescents with sufficient MVPA time, the estimated difference in reaction time was 0.17 seconds (95% CI : 0.14-0.20), while for those with insufficient MVPA time, the estimated difference was 0.09 seconds (95% CI : 0.07-0.11). Similarly, adolescents with moderate-high CRF showed a difference of 0.13 seconds (95% CI : 0.11-0.14), whereas those with low CRF had a difference of 0.08 seconds (95% CI : 0.05-0.12). Figure 4 demonstrated the difference in reaction time for the 2-back task between adolescents with good sleep quality (reference group) and those with poor sleep quality across subgroups. Specifically, among adolescents with sufficient MVPA time, the difference was 0.17 seconds (95% CI : 0.14-0.21), while for those with insufficient MVPA time, the difference was 0.08 seconds (95% CI : 0.06-0.10). Similarly, younger adolescents showed a difference of 0.12 seconds (95% CI : 0.10-0.15), whereas older adolescents had a difference of 0.07 seconds (95% CI: 0.04–0.10). Interestingly, among adolescents with poor sleep quality, those who were younger, had insufficient MVPA time, and exhibited lower CRF levels performed worse on working memory. No significant effect modifications were detected for gender, SSB, or BMI. 4. Discussion This study examined the association between sleep quality and working memory performance in a large sample of typically developing adolescents. We found that poor sleep quality was significantly associated with longer reaction time in both the 1-back and 2-back tasks, indicating worse working memory performance among adolescents with poor sleep quality. Moreover, MVPA time, age and CRF as significant effect modifiers of these associations. These findings offered a fresh perspective to investigate the association between sleep quality and working memory. Few studies examined the relationship between sleep quality and working memory in typically developing adolescents. We summarized three studies on the working memory effects of sleep quality in typically developing adolescents [18,] [29,] [30] . Specifically, Data from 110 college students from the USA showed that working memory capacity was negatively correlated with PSQI scores [18] . Similarly, Li et al. found that college students with poor sleep quality exhibited lower working memory performance, which they attributed to their lack of ability to sustain attention [29] . Another cross-sectional study, conducted in 204 typically developing children aged 7-9, suggested that sleep self-reported scores were significantly related to working memory [30] . Combining previous studies, our findings supported the association between the poor sleep quality and worse working memory performance in adolescents. Interestingly, previous studies reported inconsistent associations between specific dimensions of sleep quality and working memory performance [19] , [31] , [32] . For example, Anderson et al. conducted a cross-sectional study with 236 healthy adolescents and found a significant association between sleep scores based on a questionnaire and working memory performance, but no association between actigraphy-measured sleep duration and working memory [19] . Similarly, data from 135 healthy school children demonstrated a significant association between sleep quality and working memory, but no significant association was found between sleep duration (or sleep efficiency) and working memory [31] . And a meta-analysis revealed that insufficient sleep had a greater impact on basic cognitive functions than on short-term memory [32] . We speculated that the difference in sleep issues studied might account for the discrepancy. The findings from the present study and those mentioned previously both supported the view that sleep quality is significantly related to working memory performance in adolescents. However, it is worth noting that this does not exclude the possibility that a single sleep issue might impact the working memory performance of adolescents. The potential biological mechanisms linking sleep quality to working memory remain incompletely explored. Among the proposed mechanisms, alterations in brain structure appeared to be the most plausible explanation. Specifically, a study from the Life brain consortium showed that low sleep quality was related to greater hippocampal volume loss [12] . Furthermore, a longitudinal study found that an increased rate of atrophy in the frontal lobe was associated with poor sleep quality [13] . Previous studies indicated that both the hippocampus and the prefrontal cortex were brain structures highly correlated with working memory [33] , [34] . These findings provided indirect evidence suggesting that poor sleep quality could affect working memory by altering specific brain structures. This study showed that adolescents with poor sleep quality but sufficient MVPA exhibited better working memory performance compared to those with both poor sleep quality and insufficient MVPA time. This finding suggested that there may be an interaction between sleep quality and MVPA time, with similar results also reported in previous studies [23,] [35] . A prospective cohort study conducted in Europe observed that moderate physical activity decreased the likelihood of developing rheumatoid arthritis among adults with poor sleep patterns [35] . A review analyzed the interaction between physical activity (PA) and sleep, indicating that insufficient PA might exacerbate the negative impact of poor sleep on cognitive function [23] . However, the seven studies included in this review all focus on adult populations, excluding adolescents. Considering the well-documented links between cognitive performance and dementia risk [36] , identifying modifiable risk factors for impaired cognitive function among adolescents is of paramount importance. Interestingly, one of this study findings also provided evidence for this. Specifically, among adolescents with poor sleep quality, younger (12-15 years) adolescents exhibited significantly lower levels of working memory compared to older adolescents (16-18 years). The relatively low level of brain development in younger adolescents may explain why poor sleep quality has a more detrimental effect on working memory. Additionally, according to our awareness, the study is the first to offer epidemiological evidence regarding the interplay between sleep quality and CRF on working memory. Adolescents with poor sleep quality and low CRF exhibited worse working memory performance compared to those with poor sleep quality but high CRF. Our previous research confirmed that CRF was a significant and independent predictor of working memory [21] . CRF promotes angiogenesis in the motor cortex and increases blood flow, thereby improving cerebral vascularization [37] . These findings suggested that there might be some interactive mechanisms between CRF and sleep quality, which provided a physiological basis for the observed association in adolescents. The present study had some limitations that should be noted. Firstly, the data used in this study were from a cross-sectional study, so caution should be exercised when inferring causal associations between sleep quality and working memory. Secondly, because the sleep quality of participants was assessed using a self-reported questionnaire, the results may be subject to bias. Thirdly, due to the inability to adjust for all potential covariates of working memory, the study results may be influenced by residual confounding. 5. Conclusion The study found that Chinese adolescents with poor sleep quality exhibited worse working memory performance, particularly among those who were younger, had insufficient MVPA time, and lower CRF. Considering the widespread prevalence of poor sleep quality among adolescents, the findings of the present study have significant implications for improving Chinese adolescents’ cognitive function. Declarations Ethics approval and consent to participate This study was approved by the Human Experiment Ethics Committee of East China Normal University (HR761-2022) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all the participants and all parents of the participating children before their involvement in the study. Consent for publication Not applicable Availability of data and materials The datasets used during the current study cannot be made publicly available as per ethics approval at East China Normal University. Readers can obtain them from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The study was funded by National Natural Science Foundation of China (granted number: 82373595) Authors' contributions HJ conceptualized, analysed and wrote the original draft of the manuscript. LY conducted the behavioural testing. GYR and LYQ assisted in the data analyses. ZF and SPW conceptualized the study. LH and HYY conducted the behavioural testing. YXJ conceptualized, supervised and provided funding for the study. All authors read, reviewed, edited and approved the final manuscript. Acknowledgments We express our gratitude to all the participants and their parents for their invaluable cooperation in our study. 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MVPA, moderate-to-vigorous physical activity; BMI, body mass index; CRF, cardiorespiratory fitness\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5772463/v1/b7c6ceeb709a0926f5bf83d5.png"},{"id":79164753,"identity":"de43a2d7-9d4b-4c83-a3ca-30db0297e433","added_by":"auto","created_at":"2025-03-25 08:12:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":113474,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between sleep quality and reaction time for 1-back in various subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: The linear regression model adjusted for gender, age, SSB, MVPA, BMI, and CRF\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5772463/v1/a30b213ca798f3c6feaa0f45.png"},{"id":79163843,"identity":"28c2e1cb-b255-49a4-bf99-6b0b70fb09e7","added_by":"auto","created_at":"2025-03-25 08:04:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98610,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between sleep quality and reaction time for 2-back in various subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: The linear regression model adjusted for gender, age, SSB, MVPA, BMI, and CRF\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5772463/v1/c8439c8646b2d9581990667f.png"},{"id":87219348,"identity":"d5993aa7-d7f1-4268-8c3a-eaa690fa06b0","added_by":"auto","created_at":"2025-07-21 16:04:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1244957,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5772463/v1/0dacbaf1-ef24-4b1d-b144-c352dfa09f36.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The joint association between sleep quality, moderate-to-vigorous physical activity , cardiorespiratory fitness, and working memory in Chinese adolescents","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSleep quality is crucial for maintaining normal functioning of both cerebral and somatic systems, and is increasingly recognized as an important lifestyle contributor to physical and psychological health. However, an increasing number of people are now experiencing poor sleep quality due to stress or psychological issues. Studies indicated that approximately one-third of children\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, 32.8% of adults\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, and 60% of elderly individuals\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e suffer from poor sleep quality. Additionally, in 2019, it was estimated that sleep disorders affected 176\u0026nbsp;million Chinese individuals, positioning China as the nation with the greatest global burden of sleep-related issues\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Poor sleep quality might result in a multitude of medical conditions, such as cardiovascular disease\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, obesity\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, neurocognitive decline\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWorking memory is thought to be a cognitive system for on-line storage and processing of information in the service of the current task\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Working memory emerges during the primary school stage and continues to develop throughout adolescence\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Sleep grants our brain an interval devoid of heavy informational input, enabling the classification, structuring, and stabilization of recently formed memories\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Sleep quality has been reported to affect specific brain structures that have a high correlation with working memory\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Therefore, it is plausible to speculate about the adverse effects of poor sleep quality on the performance of working memory.\u003c/p\u003e \u003cp\u003eHowever, prior research focused primarily on exploring the association between sleep and working memory in atypical samples. For instance, Sciberras et al. reported a significant relationship between behavioral sleep issues and working memory performance among children with ADHD aged 5\u0026ndash;13\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Similarly, McCann et al. discovered associations between poor sleep quality and verbal working memory deficits in children with neurological conditions\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. In another study among children aged 3\u0026ndash;5 years, parents\u0026rsquo; reports of elevated risk of sleep-disordered breathing were linked to impaired working memory\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Moreover, Lau et al. found that compared to healthy children, those with obstructive sleep apnea exhibited worse working memory performance\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInterestingly, prior studies on the association between sleep quality and working memory in typical samples yielded inconsistent conclusions. A study revealed that poor sleep quality was an independent predictor of reduced working memory capacity among college students\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. However, a similar study conducted among adolescents found no significant association between sleep duration (assessed through actigraphy) and working memory\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The inconsistencies might stem from variations in sleep measurement methods and sample diversity across studies (e.g., age ranges from infants to adults, and populations spanning healthy to atypical groups). To our knowledge, the present study is the first large sample to investigate the association between sleep quality and working memory in typically developing Chinese adolescents. If poor sleep quality contributes to worse working memory among adolescents, improving sleep quality may serve as a viable intervention to enhance cognitive performance.\u003c/p\u003e \u003cp\u003eFurthermore, our previous studies identified several factors linked to working memory. Specifically, we observed that increased consumption of sugar-sweetened beverage (SSB) is associated with worse working memory\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Adolescents with higher levels of cardiorespiratory fitness (CRF) demonstrated enhanced working memory capabilities\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Additionally, adolescent obesity correlated with poorer working memory performance\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. A review suggested that insufficient physical activity might exacerbate the negative impact of poor sleep on cognitive function\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. However, interactions among these factors, sleep quality, and working memory remain unclear.\u003c/p\u003e \u003cp\u003eTherefore, the primary objective of this study is to investigate the association between sleep quality and working memory in Chinese adolescents. We explored whether age, gender, SSB consumption, MVPA time, CRF, and BMI moderate the association between sleep quality and working memory.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Participants and study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample recruitment process involved two stages of cluster sampling. Firstly, from September to November 2023, this study randomly selected two cities (Shanghai and Suzhou) from eastern China to conduct a cross-sectional study. Subsequently, random selection was conducted in each city, picking one junior high school and one high school, resulting in a total of four schools. Finally, this study invited all students from these four schools to participate. The inclusion criteria were as follows: (1) Chinese adolescents with an IQ score above 90, as assessed using the Wechsler Intelligence Scale; (2) free from neurological diseases or other severe injuries; (3) without experiencing negative psychological emotions.\u003c/p\u003e\n\u003cp\u003eThe present study invited a total of 2694 Chinese adolescents from the four selected schools, and 170 adolescents were excluded due to failure to meet inclusion criteria or incomplete informed consent. A total of 96 adolescents were excluded due to incomplete data on sleep quality or working memory. Finally, 2428 participants were included in the final sample size (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Human Experiment Ethics Committee of East China Normal University (HR761-2022) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all the participants and all parents of the participating children before their involvement in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Assessment of sleep quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sleep quality of participants was assessed using the Pittsburgh Sleep Quality Index (PSQI), which evaluated participants\u0026rsquo; sleep quality over the past month. Each item was scored on a 0-3 scale, and the total PSQI score was obtained by summing up the scores of all items. A higher PSQI score indicated poorer sleep quality, and the PSQI score of 5 or below was considered to indicate good sleep quality, while a score above 5 is considered to indicate poor sleep quality\u003csup\u003e[24]\u003c/sup\u003e. In this study, the Cronbach\u0026apos;s alpha coefficient for the PSQI score was 0.762, indicated high reliability. Additionally, the confirmatory factor analysis yielded satisfactory results, demonstrating high validity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Assessment of working memory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe working memory of participants was evaluated using the N-back task via the E-prime 1.1 software system. The assessment required participants to complete the task in a quiet environment. The results of the N-back task indicated the reaction time and accuracy during the assessment, with a longer reaction time indicating worse performance in the participants\u0026rsquo; working memory. The details of the assessment process of N-back task were described in our previous study\u003csup\u003e[21]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Confounders\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA self-administered questionnaire collected information on the following potential variables: participants\u0026rsquo; age (years), participants\u0026rsquo; gender (boys, girls), sugar-sweetened beverage consumption (SSB consumption, \u0026lt;1 times/week, 1-4 times/week, \u0026ge;5 times/week) by the question \u0026ldquo;How many times did you consume sugar-sweetened beverages during the past week?\u0026rdquo;, moderate-to-vigorous physical activity time (MVPA time, \u0026lt;70 min/day, \u0026ge;70 min/day)\u003csup\u003e[25]\u003c/sup\u003e. Additionally, the study measured participants\u0026rsquo; BMI and classified it into obesity and normal groups based on the WHO standard\u003csup\u003e[26]\u003c/sup\u003e. The participants\u0026apos; cardiorespiratory fitness (CRF) was evaluated by the 20-meter shuttle run (20m SRT) and divided into high, moderate and low groups categories. The details of the assessment process of 20m SRT and CRF were described in our previous study\u003csup\u003e[21]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe drew a directed acyclic graph (DAG) with the aim of determining the most parsimonious set of confounding variables\u003csup\u003e[27]\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(Figure 2). Finally, we adjusted the following confounding variables in the primary model: age, gender, SSB consumption, MVPA time, and CRF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor continuous data, the present study used the independent samples \u003cem\u003et\u003c/em\u003e test, and the results were expressed using means and standard deviations (Mean \u0026plusmn; SD). For categorical data, the present study used the Chi-square test to compare sleep quality in different categories, and the results were expressed by percentage.\u003c/p\u003e\n\u003cp\u003eThe present study took good sleep quality as the reference and conducted general linear regression to assess the association between sleep quality and working memory among Chinese adolescents. We used two models: the crude model (without adjustment) and the adjusted model (after adjusting for confounders such as age, gender, SSB consumption, MVPA time, BMI, and CRF). For adolescents with poor sleep quality, the present study assessed the associations between the PSQI score (as a continuous variable) and working memory. Due to the right-skewed distribution of the PSQI scores, we applied a natural logarithm (LN) transformation to the PSQI scores of adolescents with poor sleep quality. The present study further calculated for multiple comparisons to correct the false discovery rate (FDR), and when FDR was less than 0.05, we considered the result significant\u003csup\u003e[28]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAdditionally, the present study investigated the effect modification of various factors, including gender (boys vs girls), age (12-15years vs 16-18 years), SSB consumption (0 time/week vs \u0026ge;1 times/week), MVPA time (\u0026lt;70 min/day vs \u0026ge;70 min/day), BMI (normal vs obesity), CRF (moderate-high vs low). We tested for interaction by incorporating an interaction term in the adjusted model, which was the product of sleep quality and a modifier. When \u003cem\u003eP\u003c/em\u003e for interaction less than 0.05, the covariate was considered to exhibit effect modification. Furthermore, we calculated the subgroup-specific estimates of the effect by conducting stratified analyses within each subgroup.\u003c/p\u003e\n\u003cp\u003eData was analyzed using SPSS software (version 24.0; IBM Corp) and R (version 4.4.1; R Development Core Team) for data analysis. All statistical \u003cem\u003eP\u003c/em\u003e-values less than 0.05 (two-sided) were considered as statistically significant.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003e3.1 Description of study participants\u003c/p\u003e\n\u003cp\u003eTable 1 showed the study population characteristics. Among 2428 Chinese adolescents, 1264 (52.1%) were boys with an average age of 14.6 years old. A total 37.8% adolescents exhibited poor sleep quality, while 62.2% adolescents exhibited good sleep quality. Compared to adolescents with good sleep quality, those with poor sleep quality were more likely to be older and girls, and had less MVPA time, higher SSB consumption, and lower CRF (all \u003cem\u003ep\u003c/em\u003e-values \u0026lt;0.05).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 524px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Study population characteristics according to sleep quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 158px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eTotal sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 183px;\"\u003e\n \u003cp\u003eSleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eN(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e2428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e1510(62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e918(37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eAge, years (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e14.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e14.4 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e14.8 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e21.2 \u0026plusmn; 4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e21.4 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eRT for working memory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e1-back, seconds (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.80 \u0026plusmn; 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.76 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.88 \u0026plusmn; 0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e2-back, seconds (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.11 \u0026plusmn; 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e1.02 \u0026plusmn; 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.13 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1264 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e830 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e434 (47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1164 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e680 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e484 (52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eSSB consumption, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e0 times/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1376 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e891 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e485 (52.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e1-4 times/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e679 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e415 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e264 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u0026ge;5 times/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e373 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e204 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e169 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eMVPA time, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u0026lt;70min/day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1685 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e1029 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e656 (71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u0026ge;70min/day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e743 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e481 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e262 (28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003eCRF, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e582 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e391 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e191 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1242 (51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e766 (50.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e476 (51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e604 (24.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e353 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e251 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 524px;\"\u003e\n \u003cp\u003eAbbreviations: RT, reaction time; SSB, sugar-sweetened beverage; MVPA, moderate-to-vigorous physical activity; BMI, body mass index; CRF, cardiorespiratory fitness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.2 Association between sleep quality and working memory\u003c/p\u003e\n\u003cp\u003eTable 2 presented the association between sleep quality and working memory. The sleep quality was significantly associated with working memory among Chinese adolescents. Specifically, in the adjusted model, adolescents with poor sleep quality demonstrated significantly longer reaction time for both the 1-back and 2-back tasks compared to adolescents with good sleep quality (all \u003cem\u003ep\u003c/em\u003e-values \u0026lt;0.05). Table 3 showed the association between PSQI score and working memory. When analyzing only adolescents with poor sleep quality, the analysis revealed that an increase in the logarithmic PSQI score was associated with increased in reaction time for the 1-back and 2-back tasks (all \u003cem\u003ep\u003c/em\u003e-values \u0026lt; 0.05).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"653\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 653px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. The linear regression of sleep quality and working memory (n=2824)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 114px;\"\u003e\n \u003cp\u003eWorking memory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 254px;\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 253px;\"\u003e\n \u003cp\u003eAdjusted model \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eEstimates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026shy;values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eEstimates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e1-back task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eGood sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003ePoor sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.10, 0.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.09, 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2-back task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eGood sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003ePoor sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.10, 0.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.08, 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 653px;\"\u003e\n \u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eAdjusted for age, gender, sugar-sweetened beverage consumption, moderate-to-vigorous physical activity time, BMI, and cardiorespiratory fitness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"657\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. The linear regression of PSQI score and working memory for adolescents with poor sleep (n = 918)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 103px;\"\u003e\n \u003cp\u003eWorking memory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 251px;\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 272px;\"\u003e\n \u003cp\u003eAdjusted model \u003csup\u003ea\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eEstimates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026shy;values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eEstimates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1-back task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.06, 0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.05, 0.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e2-back task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.06, 0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.05, 0.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eAdjusted for age, gender, sugar-sweetened beverage consumption, moderate-to-vigorous physical activity time, body mass index, and cardiorespiratory fitness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.3 Effect modification\u003c/p\u003e\n\u003cp\u003eWe found that age, MVPA time and CRF modified the association between sleep quality and the 1-back and 2-back tasks (\u003cem\u003eP\u003c/em\u003e for interaction \u0026lt;0.05, respectively). Figure 3 demonstrated the difference in reaction time for the 1-back task between adolescents with good sleep quality (reference group) and those with poor sleep quality across subgroups. Specifically, among adolescents with sufficient MVPA time, the estimated difference in reaction time was 0.17 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.14-0.20), while for those with insufficient MVPA time, the estimated difference was 0.09 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.07-0.11). Similarly, adolescents with moderate-high CRF showed a difference of 0.13 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.11-0.14), whereas those with low CRF had a difference of 0.08 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.05-0.12).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 4 demonstrated the difference in reaction time for the 2-back task between adolescents with good sleep quality (reference group) and those with poor sleep quality across subgroups. Specifically, among adolescents with sufficient MVPA time, the difference was 0.17 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.14-0.21), while for those with insufficient MVPA time, the difference was 0.08 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.06-0.10). Similarly, younger adolescents showed a difference of 0.12 seconds (95%\u003cem\u003eCI\u003c/em\u003e: 0.10-0.15), whereas older adolescents had a difference of 0.07 seconds (95% CI: 0.04\u0026ndash;0.10).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, among adolescents with poor sleep quality, those who were younger, had insufficient MVPA time, and exhibited lower CRF levels performed worse on working memory. No significant effect modifications were detected for gender, SSB, or BMI.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study examined the association between sleep quality and working memory performance in a large sample of typically developing adolescents. We found that poor sleep quality was significantly associated with longer reaction time in both the 1-back and 2-back tasks, indicating worse working memory performance among adolescents with poor sleep quality. Moreover, MVPA time, age and CRF as significant effect modifiers of these associations. These findings offered a fresh perspective to investigate the association between sleep quality and working memory.\u003c/p\u003e\n\u003cp\u003eFew studies examined the relationship between sleep quality and working memory in typically developing adolescents. We summarized three studies on the working memory effects of sleep quality in typically developing adolescents\u003csup\u003e[18,]\u003c/sup\u003e\u003csup\u003e[29,]\u003c/sup\u003e\u003csup\u003e[30]\u003c/sup\u003e. Specifically, Data from 110 college students from the USA showed that working memory capacity was negatively correlated with PSQI scores\u003csup\u003e[18]\u003c/sup\u003e. Similarly, Li et al. found that college students with poor sleep quality exhibited lower working memory performance, which they attributed to their lack of ability to sustain attention\u003csup\u003e[29]\u003c/sup\u003e. Another cross-sectional study, conducted in 204 typically developing children aged 7-9, suggested that sleep self-reported scores were significantly related to working memory\u003csup\u003e[30]\u003c/sup\u003e. Combining previous studies, our findings supported the association between the poor sleep quality and worse working memory performance in adolescents.\u003c/p\u003e\n\u003cp\u003eInterestingly, previous studies reported inconsistent associations between specific dimensions of sleep quality and working memory performance\u003csup\u003e[19]\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e[31]\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e[32]\u003c/sup\u003e. For example, Anderson et al. conducted a cross-sectional study with 236 healthy adolescents and found a significant association between sleep scores based on a questionnaire and working memory performance, but no association between actigraphy-measured sleep duration and working memory\u003csup\u003e[19]\u003c/sup\u003e. Similarly, data from 135 healthy school children demonstrated a significant association between sleep quality and working memory, but no significant association was found between sleep duration (or sleep efficiency) and working memory\u003csup\u003e[31]\u003c/sup\u003e. And a meta-analysis revealed that insufficient sleep had a greater impact on basic cognitive functions than on short-term memory\u003csup\u003e[32]\u003c/sup\u003e. We speculated that the difference in sleep issues studied might account for the discrepancy. The findings from the present study and those mentioned previously both supported the view that sleep quality is significantly related to working memory performance in adolescents. However, it is worth noting that this does not exclude the possibility that a single sleep issue might impact the working memory performance of adolescents.\u003c/p\u003e\n\u003cp\u003eThe potential biological mechanisms linking sleep quality to working memory remain incompletely explored. Among the proposed mechanisms, alterations in brain structure appeared to be the most plausible explanation. Specifically, a study from the Life brain consortium showed that low sleep quality was related to greater hippocampal volume loss\u003csup\u003e[12]\u003c/sup\u003e. Furthermore, a longitudinal study found that an increased rate of atrophy in the frontal lobe was associated with poor sleep quality\u003csup\u003e[13]\u003c/sup\u003e. Previous studies indicated that both the hippocampus and the prefrontal cortex were brain structures highly correlated with working memory\u003csup\u003e[33]\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e[34]\u003c/sup\u003e. These findings provided indirect evidence suggesting that poor sleep quality could affect working memory by altering specific brain structures.\u003c/p\u003e\n\u003cp\u003eThis study showed that adolescents with poor sleep quality but sufficient MVPA exhibited better working memory performance compared to those with both poor sleep quality and insufficient MVPA time. This finding suggested that there may be an interaction between sleep quality and MVPA time, with similar results also reported in previous studies\u003csup\u003e[23,]\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003e[35]\u003c/sup\u003e. A prospective cohort study conducted in Europe observed that moderate physical activity decreased the likelihood of developing rheumatoid arthritis among adults with poor sleep patterns\u003csup\u003e[35]\u003c/sup\u003e. A review analyzed the interaction between physical activity (PA) and sleep, indicating that insufficient PA might exacerbate the negative impact of poor sleep on cognitive function\u003csup\u003e[23]\u003c/sup\u003e. However, the seven studies included in this review all focus on adult populations, excluding adolescents. Considering the well-documented links between cognitive performance and dementia risk\u003csup\u003e[36]\u003c/sup\u003e, identifying modifiable risk factors for impaired cognitive function among adolescents is of paramount importance. Interestingly, one of this study findings also provided evidence for this. Specifically, among adolescents with poor sleep quality, younger (12-15 years) adolescents exhibited significantly lower levels of working memory compared to older adolescents (16-18 years). The relatively low level of brain development in younger adolescents may explain why poor sleep quality has a more detrimental effect on working memory. Additionally, according to our awareness, the study is the first to offer epidemiological evidence regarding the interplay between sleep quality and CRF on working memory. Adolescents with poor sleep quality and low CRF exhibited worse working memory performance compared to those with poor sleep quality but high CRF. Our previous research confirmed that CRF was a significant and independent predictor of working memory\u003csup\u003e[21]\u003c/sup\u003e. CRF promotes angiogenesis in the motor cortex and increases blood flow, thereby improving cerebral vascularization\u003csup\u003e[37]\u003c/sup\u003e. These findings suggested that there might be some interactive mechanisms between CRF and sleep quality, which provided a physiological basis for the observed association in adolescents.\u003c/p\u003e\n\u003cp\u003eThe present study had some limitations that should be noted. Firstly, the data used in this study were from a cross-sectional study, so caution should be exercised when inferring causal associations between sleep quality and working memory. Secondly, because the sleep quality of participants was assessed using a self-reported questionnaire, the results may be subject to bias. Thirdly, due to the inability to adjust for all potential covariates of working memory, the study results may be influenced by residual confounding.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe study found that Chinese adolescents with poor sleep quality exhibited worse working memory performance, particularly among those who were younger, had insufficient MVPA time, and lower CRF. Considering the widespread prevalence of poor sleep quality among adolescents, the findings of the present study have significant implications for improving Chinese adolescents\u0026rsquo; cognitive function.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Human Experiment Ethics Committee of East China Normal University (HR761-2022) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all the participants and all parents of the participating children before their involvement in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study cannot be made publicly available as per ethics approval at East China Normal University. Readers can obtain them from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was funded by National Natural Science Foundation of China (granted number: 82373595)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHJ conceptualized, analysed and wrote the original draft of the manuscript. LY conducted the behavioural testing. GYR and LYQ assisted in the data analyses. ZF and SPW conceptualized the study. LH and HYY conducted the behavioural testing. YXJ conceptualized, supervised and provided funding for the study. All authors read, reviewed, edited and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to all the participants and their parents for their invaluable cooperation in our study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLiu C, Chen R, Sera F, et al. Ambient Particulate Air Pollution and Daily Mortality in 652 Cities. N Engl J Med. 2019;381(8):705-715. doi:10.1056/NEJMoa1817364\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention. AdultDemographics. Published [November 2, 2022], https://www.cdc.gov/sleep/data-and-statistics/Adults.html. [Accessed 9 May 2024]\u003c/li\u003e\n\u003cli\u003eGulia KK, Kumar VM. Sleep disorders in the elderly: a growing challenge. Psychogeriatrics. 2018;18(3):155-165. doi:10.1111/psyg.12319\u003c/li\u003e\n\u003cli\u003eBenjafield AV, Ayas NT, Eastwood PR, et al. 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Neurosci Biobehav Rev. 2021;130:369-378. doi:10.1016/j.neubiorev.2021.09.003\u003c/li\u003e\n\u003cli\u003eChen G, Xiang H, Mao Z, et al. Is long-term exposure to air pollution associated with poor sleep quality in rural China?. Environ Int. 2019;133(Pt B):105205. doi:10.1016/j.envint.2019.105205\u003c/li\u003e\n\u003cli\u003eNational Bureau of Disease Control and Prevention.Evaluation of physical activity levels of children and adolescents aged 7 to 18 years:WS/T 10008-2023 [S].Beijing:China Standard Press,2023.(in Chinese)\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Child Growth Standards. Geneva: World Health Organization; 2007. Available from: https://www.who.int/publications/i/9789241563991. Accessed on 2025-03-10.\u003c/li\u003e\n\u003cli\u003eTextor J, van der Zander B, Gilthorpe MS, Liskiewicz M, Ellison GT. Robust causal inference using directed acyclic graphs: the R package \u0026apos;dagitty\u0026apos;. 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Combining Cognitive Markers to Identify Individuals at Increased Dementia Risk: Influence of Modifying Factors and Time to Diagnosis. J Int Neuropsychol Soc. 2020;26(8):785-797. doi:10.1017/S1355617720000272\u003c/li\u003e\n\u003cli\u003eHillman CH, Erickson KI, Kramer AF. Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci. 2008;9(1):58-65. doi:10.1038/nrn2298\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chinese adolescents, cross-sectional studies, effect modification, sleep quality, working memory","lastPublishedDoi":"10.21203/rs.3.rs-5772463/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5772463/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Poor sleep quality is a prevalent health concern among Chinese adolescents. Although significant focus has been given to the impact of sleep problems on cognitive function, research on the association between sleep quality and working memory in typically developing adolescents remains limited. The aim of this study is to examine this association in Chinese adolescents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe present study randomly recruited 2428 adolescents aged 12-18 years from four schools in Shanghai and Suzhou, eastern China in 2023 through two-stage cluster sampling. Information on sleep quality was collected using the questionnaire (Pittsburgh Sleep Quality Index). Adolescents’ working memory was evaluated using the N-back task. A general linear regression analysis was conducted to evaluate the association between sleep quality and working memory, adjusted for potential confounders. Interaction terms, representing the product of sleep quality and each modifier, were included to test for interaction effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIn the adjusted model, adolescents with good sleep quality served as the reference group. Those with poor sleep quality had increased reaction times by 0.11 seconds (95%\u003cem\u003eCI\u003c/em\u003e:0.09-0.13) during the 1-back task and by 0.10 seconds (95%\u003cem\u003eCI\u003c/em\u003e:0.08-0.12) during the 2-back task. Moderate-to-vigorous physical activity (MVPA) time, cardiorespiratory fitness (CRF) and age significantly modified the associations between sleep quality and working memory (\u003cem\u003eP\u003c/em\u003efor interaction\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003eChinese Adolescents with poor sleep quality exhibited worse working memory, particularly among those who were younger, had insufficient MVPA time, and lower CRF. Good sleep quality is significant in improving cognition function among Chinese adolescents.\u003c/p\u003e","manuscriptTitle":"The joint association between sleep quality, moderate-to-vigorous physical activity , cardiorespiratory fitness, and working memory in Chinese adolescents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 08:04:41","doi":"10.21203/rs.3.rs-5772463/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-14T11:45:29+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"313349051543019816597129618645368403982","date":"2025-05-06T16:30:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T09:48:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204194536452193928321296344525946900671","date":"2025-05-06T07:12:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187903760161409870934383646270499359696","date":"2025-03-27T07:24:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-24T17:28:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303881208029907772310798131301258763250","date":"2025-03-24T07:32:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-24T01:20:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-21T06:29:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-03-18T13:25:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ab4b545-8b52-4704-886d-db4f204647a9","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T16:01:19+00:00","versionOfRecord":{"articleIdentity":"rs-5772463","link":"https://doi.org/10.1186/s12889-025-23567-6","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-07-14 15:57:31","publishedOnDateReadable":"July 14th, 2025"},"versionCreatedAt":"2025-03-25 08:04:41","video":"","vorDoi":"10.1186/s12889-025-23567-6","vorDoiUrl":"https://doi.org/10.1186/s12889-025-23567-6","workflowStages":[]},"version":"v1","identity":"rs-5772463","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5772463","identity":"rs-5772463","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}