|
 
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| ORIGINAL ARTICLE |
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| Year : 2023 | Volume
: 6
| Issue : 3 | Page : 112-118 |
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Sleep and subjective well-being among chinese adolescents: Resilience as a mediator
Yuanyuan An1, Xiaopeng Ji2, Linli Zhou1, Jianghong Liu3
1 School of Psychology, Nanjing Normal University, Nanjing, China
2 School of Nursing, College of Health Sciences, University of Delaware, Newark, DE, USA
3 Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, PA, USA
| Date of Submission | 02-May-2023 |
| Date of Acceptance | 13-Aug-2023 |
| Date of Web Publication | 18-Sep-2023 |
Correspondence Address:
Jianghong Liu
418 Curie Blvd., Room 426, Claire M. Fagin Hall, Philadelphia, PA
USA
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/shb.shb_238_23
Introduction: The relationships among sleep, resilience, and subjective well-being (SWB) are less studied in adolescents. This study aimed to examine the associations between multiple sleep domains (sleep duration and quality, and chronotype) and SWB in Chinese adolescents, and whether resilience mediated these relationships. Methods: We enrolled 455 adolescents in Jintan and Nanjing cities (Jiangsu Province, China) in 2017–2018. Sleep variables included sleep duration (time in bed [TIB], interval between bedtime and waketime), sleep quality (global score of the Pittsburgh Sleep Quality Index [PSQI]), and chronotype (mid-sleep time on weekends corrected for sleep debt). We used the Chinese version of the Connor–Davidson Resilience Scale to measure resilience, and the satisfaction with Life Scale and Subjective Happiness Scale to measure SWB. Mediation analyses were performed using structural equation modeling with a bootstrap approach. Results: The associations between sleep duration/sleep quality and SWB were fully mediated by resilience. Specifically, longer TIB (B = 2.04, P = 0.03) and lower PSQI scores (B = −1.60, P < 0.001) were associated with greater resilience, which in turn, was associated with greater latent SWB constructed from happiness and life satisfaction (BTIB = 0.12, BPSQI = 0.11, P < 0.05). Later chronotype was associated with lower happiness (B = −0.52, P = 0.01) and life satisfaction (B = −0.76, P = 0.02) but not resilience and latent SWB. Conclusion: Sleep duration and sleep quality were positively associated with latent SWB, and resilience is a mediator. Later, chronotype was independently associated with lower levels of SWB indicators, including happiness and life satisfaction. The study findings highlight the importance of optimal sleep in promoting resilience and SWB during adolescence.
Keywords: Adolescents, chronotype, resilience, sleep, well-being
How to cite this article:
An Y, Ji X, Zhou L, Liu J. Sleep and subjective well-being among chinese adolescents: Resilience as a mediator. Asian J Soc Health Behav 2023;6:112-8 |
Yuanyuan An and Xiaopeng Ji are co-first authors
| Introduction | |  |
Unhealthy sleep is prevalent in adolescents, with up to 75% of adolescents reporting insufficient sleep (<8 h) and/or poor sleep (e.g., subjective and objective sleep difficulties and sleep fragmentation).[1],[2],[3],[4],[5] Adolescents are also known to progress toward an eveningness chronotype,[6] which is the behavioral manifestation (sleep and wake times) of the later circadian phase. Asian adolescents have a greater risk for unhealthy sleep (i.e., shorter and later sleep) than their counterparts in North America and Europe,[2] probably attributed to homework-related ethics and sociocultural expectations for academic success. Unhealthy sleep has been linked to multiple risk factors in adolescents, such as neurobehavioral dysfunction[7] and cardiometabolic risk factors.[8]
Coinciding with the decline in sleep health during adolescence,[5] there is a progressive decline in the levels of subjective well-being (SWB) throughout adolescence.[9] SWB, encompassing cognitive evaluation of their life as a whole (e.g., life satisfaction) and subjective process related to positive affect (e.g., happiness),[10] predicts mental and physical health, mortality, and longevity.[11] Despite the importance of SWB, evidence is limited regarding multiple sleep domains in relation to positive well-being indicators among adolescents.
The extant SWB studies have focused on sleep duration and sleep quality. Decreased subjective happiness co-occurs with an increased prevalence of unhealthy sleep (e.g., short sleep, insomnia, and poor sleep) among adolescents in Australia.[12] A longitudinal study on Netherlands Twins also suggests a temporal association between short sleep during early adolescence and worse SWB during late adolescence.[13] Compared with sleep duration and sleep quality, the role of circadian rhythm in both affective and cognitive aspects of SWB (i.e., life satisfaction and happiness) is less clear. The tendency to eveningness chronotype[6] conflicts with a restricted social schedule among adolescents, potentially leading to declined SWB during adolescence.[9] Thus, understanding the role of chronotype is important to health and well-being among adolescents.
Resilience, defined as the capacity to positively adapt to adverse events threatening their sense of well-being,[14] has been associated with both sleep and SWB across the life course. Young adults with greater resilience tend to have increased SWB indicators such as positive affect and life satisfaction.[15] The association between sleep and resilience may be reciprocal;[16] however, unhealthy sleep and daytime dysfunction have shown stronger predictive effects on resilience in a Chinese adolescent sample.[16] Given the associations between (1) sleep and resilience, and (2) resilience and SWB, the aforementioned sleep-SWB relationship may be mediated by resilience.
Overall, both sleep health[2],[17] and SWB[9] decline as children transition into adolescence. Adolescence is also accompanied by dramatic changes in sleep patterns[2],[17] and brain maturation that is related to the development of resilience.[16] Thus, a better understanding of the intertwined associations among sleep, resilience, and SWB has significant implications for health promotion in adolescence and beyond. This study aims to investigate whether multiple sleep metrics (sleep duration, sleep quality, and chronotype) are associated with SWB captured by happiness and life satisfaction, and test whether resilience mediates the association between sleep and SWB in Chinese adolescents.
| Methods | | |
Participants and procedure
We sampled participants from two cities of Nanjing and Jintan in Jiangsu Province, China. Nanjing is the capital city of the Jiangsu Province, whereas Jintan represents a small county-level city in Jiangsu. By leveraging two studies (Nanjing and Jintan), we had a representative sample to answer research questions. Nanjing Study: using the convenience sampling method, we enrolled 245 adolescents from junior middle and high schools in Nanjing between 2017 and 2018. Jintan Study: Jintan Child Cohort is a longitudinal preschool cohort designed to examine the influence of environmental exposure on neurobehavioral development.[18],[19] This cohort study utilized a multiple-stage sampling approach and enrolled Chinese preschoolers (n = 1656, 44.5% girls) from Jintan City in 2004. We collected follow-up data on sleep, resilience, and SWB among participants who were in high schools (n = 210) between 2017 and 2018 (Wave 3). Inclusion criteria for both sites are students who were not in clinical treatment for depression or insomnia. Participants received instructions from research coordinators and completed the questionnaires in their classrooms.
Of the 455 participants, 12 (2.44%) were excluded due to an incomplete survey (e.g., missing data on the total scale) and obvious response set (e.g., same answers to all questions), yielding 443 participants in data analyses.
Measures
Sleep
Sleep variables of interest included time in bed (TIB), sleep quality, and chronotype. Adolescents self-reported usual bedtime and waketime on weekdays and weekends separately.
Sleep duration
TIB was measured as a proxy of sleep duration to allow a comparison of results with the literature on children and adolescents.[4] TIB refers to the number of hours between habitual bedtime and risetime. We calculated average TIB using the formula: [(TIB on weekdays × 5) + (actual TIB on weekend × 2)]/7.
Chronotype
We estimated chronotype using mid-sleep time on non-school days (weekends), accounting for sleep debt (MSFsc) accumulated on school days. Mid-sleep time refers to the clock time halfway between bedtime. For adolescents who slept longer on weekends than weekdays, sleep debt was adjusted for as follows: MSFsc = MSF – (average sleep duration on non-school days-average weekly sleep duration)/2,[6] expressed as the number of hours past midnight.
Sleep quality
Sleep quality was measured using the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI). The CPSQI comprises seven domains (19 questions): sleep duration, sleep efficiency, sleep latency, sleep disturbances, subjective sleep quality, use of sleep medication, and daytime dysfunction.[20] We scored the domain of sleep duration using the adolescent cutoff (“0 ≥ 9 h, 1 = 8.5–9 h 1, 2 = 8–8.5 h, and 3 ≤ 8 h).[21] Scores of seven domain yield the global score, with scores greater than five categorized as poor sleepers.[20] The internal consistency of the PSQI was 0.87 (ranging from 0.46 to 0.85 for subdomains) in Chinese adolescents,[22] and 0.79 in our sample.
Connor–Davidson Resilience Scale
The Chinese version of Connor-Davidson Resilience Scale (CD-RISC) was used to measure adolescents' resilience.[14],[23] The CD-RISC includes 25 self-report items grouped into three domains: tenacity, optimism, and strength. The tenacity factor (13 items) describes individuals' equanimity, perseverance, promptness, and sense of control when individuals face challenges and hardship. The optimism-related questions (4 items) focus on the tendency of trusting one's personal and social resources and looking on the positive side of things, and the strength domain (8 items) reflects the capacity of recovering and becoming strong after setbacks. Questions were rated on a five-point Likert scale from 0 (not at all) to 4 (extremely), with higher scores reflecting greater resilience. The CD-RISC has good internal consistency reliability in our sample (Cronbach's alpha = 0.93).
Subjective well-being
We used the satisfaction with life scale (SWLS) and subjective happiness scale (SHS) to measure SWB. While life satisfaction is considered the most stable cognitive component of SWB, happiness reflects the affective component of SWB.[10]
Satisfaction with life
Adolescents were asked about their agreement with 5 statements (e.g., “In most ways my life is close to my ideal”) on a 7-point Likert scale.[24] The total score ranged from 5 to 35 and higher scores suggest greater satisfaction with life. The SWLS has adequate internal consistency (Cronbach's alpha = 0.85) among adolescents in our study.
Subjective happiness scale
The Chinese version of SHS comprises 4 items using a 7-point Likert scale.[25] One example question is “In general, I consider myself: from 1 (not a very happy person) to 7 (a very happy person). The last item was reverse-coded for the total score calculation. Higher composite scores represent greater perceived happiness. The reliability and validity of the SHS have been established in Chinese samples.[25]
Statistical analysis
We used Stata 16 to conduct all analyses. Pearson correlations were calculated to test the interrelations among continuous variables of interest, including total scores of well-being indicators (happiness and life satisfaction), resilience, and sleep variables (PSQI global score, TIB, and MSFsc). A series of multivariate linear regression models tested the relationship among sleep, resilience, and SWB indicators: (1) sleep variables were each regressed onto the SHS and SWLS scores, controlling for gender, grade, region (Nanjing or Jintan city); and (2) resilience was then additionally adjusted for in the models. Multivariate regression is chosen because there are two correlated dependent variables. Age was excluded from the final models due to its multicollinearity with grade.
Next, we estimated the direct and indirect effect of sleep variables on SWB using the structural equation model (SEM) with bootstrap method and resilience was a mediator. Given the moderate correlation between SHS and SWLS, a latent SWB variable from SHS and SWLS was constructed in the pathways using SEM. A direct path from sleep to latent SWB and indirect pathway through resilience were included in the final model. The 95% bias-corrected (BC) confidence intervals (CIs) for direct and indirect effects were estimated using a bootstrap approach (5000 random samples). The goodness of fit was measured according to the following criteria: Chi-square test (P > 0.05), comparative fit index (CFI) >0.95, Tucker–Lewis index (TLI) >0.95, and root mean square error of approximation (RMSEA) ≤0.06.[26] We handled missing data using Full Information Maximum Likelihood. All tests were two-tailed at a significance level of 0.05.
Ethical consideration
Approval from Institutional Review Boards was obtained from the University of Pennsylvania and the ethical committee for research at Jintan Hospital in China (IRB 811114). All adolescents provided assent and their parents signed the informed consent form before participation, according to the Institutional Review Board-approved guidelines.
| Results | | |
Sample characteristics
The final sample comprised 443 adolescents (16.24 ± 1.87 years old), most were of Han ethnicity (98.50%) and 47% (n = 206) were females. Adolescents averagely slept 7.24 ± 0.93 h/night, with 82% having insufficient sleep (<8 h). Midsleep times shifted 1 h later on weekends (3:49 AM) compared with weekdays (2:42 AM), with an average mid-sleep time (corrected for sleep debt) of 3:05 AM. 60% of participants reported poor sleep (PSQI>5). [Table 1] shows sample characteristics over PSQI groups. Poor sleepers were slightly younger than normal sleepers (t = 3.28, P = 0.001). The 10th graders (χ2 = 76.27, P < 0.001) and participants living in the metropolitan Nanjing (χ2 = 44.63, P < 0.001) reported higher proportions of poor sleepers. There was no gender difference in the proportion of poor sleepers (P > 0.05). | Table 1: Sample characteristics by Pittsburgh sleep quality index groups (n=421)*
Click here to view |
[Table 2] shows the results of Pearson's correlations. While TIB was positively correlated with perceived resilience (r = 0.10, P = 0.04), life satisfaction (r = 0.20, P < 0.001), and happiness (r = 0.17, P = 0.001), increasing PSQI global scores (worse sleep quality) were correlated with decreasing scores of resilience, life satisfaction and happiness (P's <0.05). Later sleep times were correlated with lower levels of happiness (r = −0.13, P = 0.01) but not life satisfaction and resilience (P > 0.05). | Table 2: Pearson correlations among life satisfaction, subjective well-being, resilience, and sleep quality
Click here to view |
Results from regression models
These bivariate correlations remained significant after controlling for gender, grade and region. The relationship between later sleep times and lower levels of happiness (B = −0.52, P = 0.01) and satisfaction with life became significant (B = −0.76, P = 0.02) in adjusted models. The magnitude of these associations decreased after resilience was additionally added to the model, suggesting the potential mediating effect of resilience. As shown in [Table 3], adolescents in higher grades at school and those who live in Nanjing (versus Jintan) were consistently associated with lower scores on the SWLS in different models [Table 3].
Mediation analyses
We constructed a latent SWB variable from SHS and SWLS and estimated whether resilience-mediated associations between sleep and SWB. As shown in [Figure 1], the link between TIB and SWB was fully mediated by resilience. There was no direct effect of TIB on SWB estimated from 1000 random bootstrap samples; however, the indirect effect through resilience was statistically significant with BC 95% CI of (0.04, 0.47). Specifically, each hour increase in TIB was associated with a two-point increase in resilience scores (B = 2.04, P = 0.03), which in turn, predicted better SWB (B = 0.12, P < 0.001). The model showed a good fit with data (LR test: χ2 = 3.74, P = 0.15, RMSEA = 0.04, CFI = 0.99, TLI = 0.97). Similarly, adolescents with greater PSQI global scores (worse sleep quality) tended to report lower levels of SWB (B = −0.18, P < 0.001), which was fully mediated by resilience [Figure 2]. The indirect effect of PSQI on SWB through resilience was −0.18 and the BC 95% CI was (−0.26, −0.11) estimated by bootstrap method. The fit indices supported the model (LR test: χ2 = 3.72, P = 0.16, RMSEA = 0.04, CFI = 0.99, TLI = 0.97). Later sleep times were not associated with latent SWB (P > 0.05). | Figure 1: The direct and indirect pathways of sleep duration (time in bed) on SWB [B (se)]a. Note: aBiased corrected 95% confidence interval from 1000 bootstrap samples. Models controlled for gender, grade and region. SWB: Subjective well-being, SHS: Subjective Happiness Scale, SWLS: Satisfaction with Life Scale, PSQI: Pittsburgh Sleep Quality index. P <0.05. ***P < 0.001
Click here to view |
 | Figure 2: The direct and indirect pathways of PSQI global score on SWB[B (se)]. Note: aBiased corrected 95% confidence interval from 1000 bootstrap samples. Models controlled for gender, grade, and region. SWB: Subjective Well-being, SHS: Subjective Happiness Scale, SWLS: Satisfaction with Life Scale, PSQI: Pittsburgh Sleep Quality Index. ***P < 0.001
Click here to view |
| Discussion | | |
This study represents one of the first to explore the relationship among multiple sleep domains, SWB, and resilience in Chinese adolescents. Insufficient sleep, poor sleep quality and sleep inconsistency between weekdays and weekends were prevalent in adolescents. Adolescents in higher grades or living in metropolitan areas (Nanjing) tended to report worse sleep and lower levels of SWB. Both TIB and sleep quality were positively associated with latent SWB constructed from happiness and life satisfaction, and resilience fully mediated these associations. Later, chronotype was associated with lower happiness and life satisfaction but not latent SWB.
Eighty percent of adolescents did not meet the 8-h recommendation, which is similar to the 17 years old in another Chinese study.[1] However, the average sleep duration (TIB) was shorter than the same age group in Australia[3] and the United States.[4] The cultural value of academic success contributes to sleep deficiencies in China, especially on school days. Sleep duration was associated with happiness, satisfaction with life, and latent SWB constructed from them, which were congruent with previous studies across countries.[12],[27] In contrast, an actigraph sleep study reported that high night-to-night variability in sleep duration, but not average sleep duration, was associated with SWB among African American adults.[28] More research using objective sleep assessment is necessary to understand the dynamic role of sleep duration in SWB.
Poor sleep quality (PSQI >5) is widespread in our sample, with greater proportions in higher grades and those living in the big city. It could be related to sleep curtailment resulting from increased academic demands and commuting. Our findings support previous research that has linked better sleep quality and fewer sleep disturbances to greater subjective happiness[12] and life satisfaction[27] in adolescents. The public health epidemic of poor sleep calls for more research on Chinese adolescents.
This study indicates that the level of resilience mediates the associations between sleep duration/quality and SWB. Short sleep and poor sleep quality are related to neuronal networks and function in certain brain regions (i.e., prefrontal cortex and amygdala) that are also responsible for emotional regulation, stress coping, and psychological resilience.[29] Consistent with our findings, Wang et al. reported predictive effects of sleep disturbances on lower resilience in Chinese adolescents.[16] Resilience reflects individuals' capacity to successfully adapt to adverse events and recover from environmental stressors. A systematic review suggests the protective effect of resilience on psychological distress and behavioral problems in children and adolescents.[30] Our findings have further linked sleep-related lower resilience to compromised SWB and its indicators including perceived happiness and life satisfaction. Adolescence is accompanied by developmental changes in sleep function and brain maturation, thus may be particularly susceptible to the “chain reaction”. Interventions targeting unhealthy sleep may improve resilience and subsequent SWB during adolescence and beyond.
Our study extended previous work to the relationship among chronotype, resilience and well-being in adolescents. Midsleep times in our sample were similar to other Chinese adolescent samples[31] but earlier than their peers in the United States,[32] with most of them fall in the intermediate chronotype between 3 AM and 5 AM. Mid-point sleep times on free days are behavioral manifestations of the underlying circadian phase and are associated with endogenous circadian pacemakers (i.e., dim light melatonin onset times).[6] Later chronotypes, reflected by later midsleep times on non-school days adjusting for sleep dept, were associated with lower happiness and life satisfaction in our sample. Our findings, to some extent, support previous findings of improved positive affect in morning-type adolescents.[33] However, chronotype was operationalized as behavioral references or times preferred for peak cognitive and physical performance in these studies, which may not reflect the circadian phase. Nevertheless, those with later chronotype tend to have misalignment between biological and social clocks (e.g., early school start time), thus at a higher risk for sleep and circadian disruptions and subsequent negative emotions. Regarding resilience, we did not find an association between chronotype and resilience. A recent study in the context of the COVID-19 pandemic reported a positive correlation between morningness and resilience score in Italian adults and sleep quality may mediator the association.[34] The inconsistency warrants a need for future investigation of the associations among sleep metrics, resilience, and SWB.
Limitation
There are several limitations that need to be addressed in this study. First, the nature of the cross-sectional design limits causal conclusions. There may be bi-directional relationships among sleep, resilience, and SWB. Whereas increased resilience scores can predict increased sleep quality and decreased sleep latency, sleep disturbance, and daytime dysfunction may be associated with later resilience.[16] Second, self-reported sleep measures are subjected to recall bias, thus calling for objective sleep measurements in the field. Third, given that afternoon naps are prevalent in China, future studies adjusting for naps are needed to replicate our findings. Finally, social determinants such as family socioeconomic status and parental education may confound the relationship among sleep, resilience, and SWB. We did not control for these variables due to data availability.
| Conclusion | | |
More than half of Chinese adolescents have short sleep and poor sleep quality. Adolescents with longer sleep duration and better sleep quality are associated with greater resilience, which in turn, is associated with better SWB reflected by happiness and life satisfaction. Later chronotype (later midsleep times) is associated with lower happiness and life satisfaction but not resilience or latent SWB. These findings indicate the importance of healthy sleep to youth resilience and well-being, and may inform prevention and intervention programs to improve adolescent health. Further longitudinal research with objective measurements of nighttime sleep and daytime naps is needed to identify optimal sleep practices to promote adolescent resilience and well-being.
Financial support and sponsorship
The data from Jintan China Child Cohort were supported by the National Institute of Environment Health Sciences grants (R01-ES018858, K01-ES015877, and K02-ES019878) to JL. The data from Nanjing Cohort was supported by the National Science Foundation of the Jiangsu Higher Education Institutions of China (18KJB190004), the Philosophy and Social Science Foundation of Jiangsu (18SHC004), and the Philosophy and Social Sciences of Jiangsu Higher Education Institutions (2018SJZDI206) to YA.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
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