147 Within-Family Dynamics Influencing Parent and Child Sleep Quality and Nighttime Activities

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A60-A61
Author(s):  
Brigid Hanley ◽  
Suzanne Gorovoy ◽  
Stihlyn Chamberlain ◽  
Bharat Bhushan ◽  
Sadia Ghani ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Family Dynamics ◽  
Sleep Habits ◽  
Television Watching ◽  
Child Sleep ◽  
Independent Variables ◽  
Logistic Regressions ◽  
Tv Watching ◽  
Fair Poor ◽  
Child Age

Abstract Introduction Increasing efforts have focused on child sleep due to its benefits to academics and physical/mental health. Less understood are the within-family dynamics that drive sleep-related behavior. Methods Data were obtained from the 2014 National Sleep Foundation Sleep in America Poll (N=1102 parent/child dyads). Variables including age, gender, sleep quality (Excellent/Good/Fair/Poor), evening activities including reading, TV-watching, and online browsing/gaming (Never/Rarely/Sometimes/Often) were reported for parent and child. Ordinal logistic regressions examined child nighttime activity as outcome and nighttime activities (entered simultaneously in the model, adjusted for each other) as independent variables, adjusted for parent and child age, sex, and sleep quality. Results Worse sleep quality in parents was associated with worse sleep quality in their children. Moreover, increased likelihood of child television-watching at night was not associated with parental sleep quality, but it was associated with child sleep quality, with “Fair” and “Poor” sleepers more likely to watch TV (Fair: oOR=1.7,p=0.018; Poor: oOR=8.0,p=0.001). Child television-watching was not associated with likelihood of parental reading, but it was associated with likelihood of parental online browsing/gaming (Rarely oOR=1.7,p=0.001; Sometimes oOR=2.3,p<0.0005; Often oOR=1.9,p=0.004) and parental TV-watching (Rarely oOR=2.6,p<0.0005; Sometimes oOR=5.4,p<0.0005; Often oOR=13.3,p<0.0005). Child online browsing/gaming was also not associated with parental sleep quality but it was associated with child sleep quality (Fair oOR=2.3,p=0.001; Poor oOR=4.8,p=0.009) and parental reading (Rarely oOR=1.5,p=0.04; Often oOR=1.6,p=0.03), TV-watching (Rarely oOR=2.3,p=0.004; Sometimes oOR=2.8,p<0.0005; Often oOR=4.6,p<0.0005) and online browsing/gaming (Rarely oOR=2.8,p<0.0005; Sometimes oOR=5.0,p<0.0005; Often oOR=7.8,p<0.0005). Child reading was not associated with parent or child sleep quality or parental online browsing/gaming, but it was related to parental TV-watching (Sometimes oOR=1.45,p=0.04; Often oOR=1.6,p=0.02) and reading (Rarely oOR=2.4,p<0.0005; Sometimes oOR=4.4,p<0.0005; Often oOR=6.9,p<0.0005). Conclusion Children who do not sleep well have parents who do not sleep well. Further, parents who read are more likely to have children who read, and parents on screens are more likely to have children on screens. Interventions targeted to parents may lead to better sleep habits in children. Support (if any):

scholarly journals Inflammation, Oxidative Stress, and Antioxidants Contribute to Selected Sleep Quality and Cardiometabolic Health Relationships: A Cross-Sectional Study

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Thirumagal Kanagasabai ◽  
Chris I. Ardern
Keyword(s):  
Oxidative Stress ◽  
Sleep Quality ◽  
Reference Range ◽  
Cross Sectional Study ◽  
Mediating Effect ◽  
Cardiometabolic Health ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Cross Sectional ◽  
Fair Poor

Sleep is vital for cardiometabolic health, but a societal shift toward poor sleep is a prominent feature of many modern cultures. Concurrently, factors such as diet and lifestyle have also changed and may mediate the relationship between sleep quality and cardiometabolic health. Objectives were to explore (1) the interrelationship and (2) mediating effect of inflammation, oxidative stress, and antioxidants on sleep quality and cardiometabolic health. Cross-sectional data from the US National Health and Nutritional Examination Survey 2005-06 (≥20 y;N=2,072) was used. Cardiometabolic health was defined as per the Joint Interim Statement; overall sleep quality was determined from six sleep habits and categorized as good, fair, poor, and very poor. Fair quality sleepers had optimal inflammation, oxidative stress, and antioxidant levels. Inflammation was above the current clinical reference range across all sleep quality categories, while oxidative stress was only within the clinical reference range for fair sleep quality. Selected sleep quality-cardiometabolic health relationships were mediated by inflammation, oxidative stress, and antioxidants and were moderated by sex. Our results provide initial evidence of a potential role for inflammation, oxidative stress, and antioxidants in the pathway between poor sleep quality-cardiometabolic decline. Further prospective research is needed to confirm our results.

scholarly journals 0925 Associations Between Co-sleeping And Sleep Quality Of Urban Preschool Children

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A351-A352
Author(s):  
M Stein ◽  
N DiSanti ◽  
S Weaver-Rogers ◽  
W Garcia ◽  
G Bonilla-Santiago ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Ethnic Minority ◽  
Intervention Development ◽  
Sleep Hygiene ◽  
Median Income ◽  
Significant Independent Predictor ◽  
Child Sleep ◽  
Urban Preschool ◽  
The Relationship ◽  
Child Age

Abstract Introduction Perspectives on co-sleeping vary by family cultural background and socio-demographic characteristics; furthermore, families may choose to co-sleep based on family values or out of necessity. To better understand the role of co-sleeping in young children from ethnic minority backgrounds, the current study sought to test the relationship between co-sleeping and sleep outcomes in an urban early childhood setting. Methods 141 Parent-child dyads with children aged 1-5 years old (N=141,50.4% female, M=4.01 [SD=1.05]; 41% African American; 41% Latinx; median income $20-30,000) were recruited through an urban preschool. Parents completed demographic information and the Brief Child Sleep Questionnaire, which yielded insomnia and sleep hygiene indices. Step-wise regressions were used to examine the relationship between sleeping location and sleep outcomes (insomnia, sleep health, and child sleep quality), controlling for child age. Results Approximately half of the sample (n=71) reported that their child sleeps in a space shared by caregivers or siblings. Co-sleeping did not differ by race/ethnicity [χ 2(3)=1.45, p=.694], child age [F(1, 140)=2.15, p=.145], or income [χ 2(5)=7.05, p=.217]. Controlling for age, insomnia was higher in co-sleeping children [F(2,140)=4.10, p=.019], although sleep location was not a significant independent predictor. Sleep hygiene [F(2,140)=2.39, p=.095] and sleep quality [F(2,139)=0.94, p=.394] did not differ by sleeping location, when controlling for age. Conclusion Co-sleeping was common but was not related to sociodemographic factors as described in prior research. Controlling for age, co-sleeping predicted higher insomnia scores suggesting that co-sleeping may be related to symptoms of behavioral insomnia. Sleep hygiene practices and sleep quality did not differ by sleeping location, suggesting that in children without behavioral insomnia symptoms, co-sleeping may not affect sleep. Future studies that seek to better understand caregiver preference and intentions regarding co-sleeping may be important to intervention development seeking to improve behavioral insomnia in ethnic/minority samples. Support  

scholarly journals 0990 Evaluating Components Of Sleep Quality And The Sleep-Quality Of Life Relationship For Children With Acute Lymphoblastic Leukemia

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A376-A376
Author(s):  
Y Gross ◽  
L Barakat ◽  
L C Daniel
Keyword(s):  
Quality Of Life ◽  
Acute Lymphoblastic Leukemia ◽  
Sleep Quality ◽  
Lymphoblastic Leukemia ◽  
Demographic Characteristics ◽  
Normative Values ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Child Sleep

Abstract Introduction Poor sleep quality is associated with reduced health-related quality of life (HRQL) for children with Acute Lymphoblastic Leukemia (ALL). Research has yet to evaluate how components of child sleep quality uniquely contribute to HRQL beyond demographic characteristics. This study evaluates features of sleep and the relationship between sleep and HRQL for children in the maintenance phase of ALL treatment. Methods 89 caregivers (ages 20-52, M=35.95, SD=7.10) of children with ALL (ages 3-12, M=5.73, SD=2.21; 13.76 months from diagnosis) completed demographic questionnaires and reports of child sleep quality (Child Sleep Habits Questionnaire; CSHQ), and 64 caregivers reported on child HRQL (Pediatric Quality of Life Inventory). Descriptive statistics were calculated. T-tests compared CSHQ subscales to ratings of healthy normative values. Pearson correlations evaluated associations between sleep and overall HRQL. Hierarchical regression assessed whether CSHQ subscales uniquely predicted HRQL beyond demographic characteristics. Results This sample reported greater bedtime resistance [t(88)=6.413, p<.001], sleep onset delay [t(88)=3.180, p=.002], sleep anxiety [t(88)=4.271, p<.001], night awakenings [t(88)=6.031, p<.001], parasomnias [t(88)=3.900, p<.001], and daytime sleepiness [t(87)=1.781, p=.078] than normative values, although sleep duration [t(88)=1.781, p=.078] and sleep disordered breathing (SDB) [t(88)=-.061, p=.951] did not differ. HRQL was related to SDB (r=-.289, p=.021), bedtime resistance (r=-.263, p=.036), and total sleep score (r=-.34, p=.006). The regression model with SDB and bedtime resistance explained 24.2% of variance but was not significant [F(6,31)=1.651, p=.167]. Conclusion Caregiver ratings showed greater sleep impairments for children in this sample than of norms. Sleep subscales were associated with HRQL, but did not predict HRQL beyond demographic factors. Caregiver reports of child sleep and HRQL may vary depending on when during the monthly chemotherapy cycle questionnaires were completed. SDB did not differ from normative values but was related to HRQL, suggesting the need to screen for SDB symptoms to potentially improve child outcomes. Support This study was supported by funding from the American Cancer Society PF-13-238-01-PCSM (PI: Daniel).

scholarly journals The Parent’s Chronotype and Child’s Sleeping Quality in Association with Relationship Satisfaction

2020 ◽  
Vol 2 (3) ◽  
pp. 375-389
Author(s):  
Cristian Ricci ◽  
Zaida Parra-Robledo ◽  
Dietrich Rothenbacher ◽  
Juan Francisco Díaz-Morales ◽  
Jon Genuneit
Keyword(s):  
Sleep Quality ◽  
Relationship Satisfaction ◽  
Sleep Duration ◽  
Sleep Onset ◽  
Sleep Time ◽  
Stress Index ◽  
German Version ◽  
Sleep Habits ◽  
Partner Relationship ◽  
Child Sleep

The prospective Ulm-SPATZ study was investigated to assess the role of child sleeping quality between 4 to 6 years of age in affecting a partner’s sleeping and relationship satisfaction within a couple. The study was conducted using a triadic approach in which the child was included in the Actor-Partner-Interdependence Model (APIM). Sleeping quality of the child was determined by using the German version of the children’s sleep habits questionnaire, sleeping features of the parents were assessed by using the Munich chronotype questionnaire, and the partner relationship assessment was performed by employing the German version of the parenting stress index questionnaire. In 211 German triads, we observed that sleeping characteristics and partner relationship scores at different child ages are consistent for both men and women. Higher and statistically significant sleep duration, time spent in bed, the midpoint of sleep, time getting out of bed, and sleep onset in women compared to men during the working days were observed. The APIM analyses showed a significant direct effect of child sleep quality on the partner relationship satisfaction. In women, a mediated effect of child sleep quality acted through sleep duration and time spent in bed on the partner relationship satisfaction score during both free and working days. In men, low child sleep quality was found to be associated with increased sleep onset during both free and working days. Child sleep quality influences relationship satisfaction mostly in mothers, likely because of their higher involvement in childcare during working days. Distress in the couple could be counteracted by a major involvement of the fathers in child management.

scholarly journals 192 Self-reported sleep features in the Italian population across the first and second wave of the COVID-19 pandemic

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A77-A78
Author(s):  
Oreste De Rosa ◽  
Nicola Cellini ◽  
Francesca Conte ◽  
Serena Malloggi ◽  
Fiorenza Giganti ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Linear Mixed Model ◽  
Negative Impact ◽  
Italian Population ◽  
Sleep Habits ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Time Points ◽  
Time In Bed ◽  
Second Wave

Abstract Introduction Several studies have shown the negative impact of COVID-19-related confinement measures (spring 2020) on sleep features and quality. Here we aim to follow-up on these data by assessing self-reported sleep characteristics during the second wave of the pandemic (autumn 2020) in Italy, where the government responded with a second, partial, lockdown. Methods Using a longitudinal approach, 214 participants (Mage=36.78±14.2y; 159F) who had participated in a previous survey (April 2020 – Total Lockdown, TL) completed the same online survey from November 10th to December 1st (Partial Lockdown, PL). In each survey, participants had to respond to a set of questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), referring to their current situation and, retrospectively, to their situation before the lockdown, resulting in four time-points (pre-TL, TL, pre-PL, PL). Results Linear mixed-model analysis showed that bedtime was delayed from pre-TL (23:46) to TL (24:42) and then linearly advanced in pre-PL (24:02) and PL (23:56). The same pattern emerged for rise time (pre-TL: 07:48, TL: 9:05, pre-PL: 8:28, PL: 7:58) and time in bed, which increased from pre-TL (8h4min) to TL (8h24min) and then linearly decreased (pre-PL: 8h15m, PL: 8h2m). Subjective sleep quality decreased in the two lockdowns compared to the period with no restrictions. The proportion of poor sleepers (PSQI>5) increased from 39.7% (pre-TL) to 48.6% in TL and again from 36.9% (pre-PL) to 47.7% in PL. Conclusion Sleep habits and quality showed different profiles across four time-points of the COVID-19 pandemic and related restrictive measures. Sleep timing alterations appeared during the first lockdown, recovered after the confinement period, and almost returned to baseline during the second lockdown (likely due to a normalization of working schedules). Instead, subjective sleep quality markedly worsened during both lockdowns relative to the preceding respective months. These data suggest that subjective sleep quality is particularly sensitive to changes in life habits and psychological factors, independently of sleep habits. Considering that the pandemic situation may continue for several months, there is a need for interventions targeting sleep quality. Support (if any) N/A

Getting Enough Sleep: On the Importance of Collecting Longitudinal Data from Wearables to Assess Sleep Quality and Seasonal Effects on Variability in Daily Activity (Preprint)

2021 ◽  
Author(s):  
María Óskarsdóttir ◽  
Anna Sigridur Islind ◽  
Elias August ◽  
Erna Sif Arnardóttir ◽  
Francois Patou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Data Collection ◽  
Sleep Quality ◽  
Daily Activity ◽  
Hospital Environment ◽  
Sensor Data ◽  
Seasonal Patterns ◽  
Sleep Patterns ◽  
Sleep Habits

BACKGROUND The method considered the gold standard for recording sleep is a polysomnography, where the measurement is performed in a hospital environment for 1-3 nights. This requires subjects to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. For longer studies with actigraphy, 3-14 days of data collection is typically used for both clinical and research studies. OBJECTIVE The primary goal of this paper is to investigate if the aforementioned timespan is sufficient for data collection, when performing sleep measurements at home using wearable and non-wearable sensors. Specifically, whether 3-14 days of data collection sufficient to capture an individual’s sleep habits and fluctuations in sleep patterns in a reliable way for research purposes. Our secondary goals are to investigate whether there is a relationship between sleep quality, physical activity, and heart rate, and whether individuals who exhibit similar activity and sleep patterns in general and in relation to seasonality can be clustered together. METHODS Data on sleep, physical activity, and heart rate was collected over a period of 6 months from 54 individuals in Denmark aged 52-86 years. The Withings Aura sleep tracker (non-wearable) and Withings Steel HR smartwatch (wearable) were used. At the individual level, we investigated the consistency of various physical activities and sleep metrics over different time spans to illustrate how sensor data from self-trackers can be used to illuminate trends. RESULTS Significant variability in standard metrics of sleep quality was found between different periods throughout the study. We show specifically that in order to get more robust individual assessment of sleep and physical activity patterns through wearable and non-wearable devices, a longer evaluation period than 3-14 days is necessary. Additionally, we found seasonal patterns in sleep data related to changing of the clock for Daylight Saving Time (DST). CONCLUSIONS We demonstrate that over two months worth of self-tracking data is needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3-14 days for sleep quality assessment and call for rethinking standards when collecting data for research purposes. Seasonal patterns and DST clock change are also important aspects that need to be taken into consideration, and designed for, when choosing a period for collecting data. Furthermore, we suggest using consumer-grade self-trackers (wearable and non-wearable ones) to support longer term evaluations of sleep and physical activity for research purposes and, possibly, clinical ones in the future.

Sleep disturbance in adolescents: Sleep quality, sleep habits, beliefs about sleep, and daytime functioning

1984 ◽  
Vol 13 (5) ◽  
pp. 375-384 ◽  
Author(s):  
Kathleen Kirmil-Gray ◽  
Jean R. Eagleston ◽  
Elizabeth Gibson ◽  
Carl E. Thoresen
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Habits ◽  
Daytime Functioning ◽  
Quality Sleep

scholarly journals 0962 Sleep and Daytime Functioning in Gifted and Twice Exceptional Children

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A365-A366
Author(s):  
R Théoret ◽  
L Bastien ◽  
R Godbout
Keyword(s):  
Sleep Quality ◽  
Internalizing Problems ◽  
Intellectual Development ◽  
Child Behavior Checklist ◽  
Typically Developing ◽  
Sleep Habits ◽  
Daytime Functioning ◽  
Twice Exceptional ◽  
Social And Emotional ◽  
Children’S Sleep

Abstract Introduction Gifted (G) children display an asynchrony between intellectual development and social and emotional development. Twice exceptional (2e) children are G children with a neuropsychological disability. We compared the sleep and daytime behavior of G, 2e and typically developing (TD) children and we sought for group-specific relationships between sleep and daytime behavior. Methods 23 children were recruited: seven G (8.7 years old, SD = 1.7), six 2e (9.8 years old, SD = 1.8) and 10 TD children (10.0 years old, SD = 2.2). Giftedness was diagnosed with neuropsychological tools. The Children’s Sleep Habits Questionnaire (CSHQ) assessed sleep quality, the Child Behavior Checklist (CBCL) assessed daytime functioning. Sleep quality and its impact on daytime functioning was measured with a MANCOVA, with the CBCL’s three main factors as dependent variables (internalizing problems, IP; externalizing problems, EP and total problems, TP), children group as the independent variable and the CSHQ total score as the covariate. Results G, 2e and TD groups scored 39.86, 39.17 and 39.70 on the CSHQ, respectively (n.s.). The three groups were not different on the CBCL, with respective mean T scores of 57.86, 50.33 and 48.60 for IP, 56.43, 55.67 and 47.80 for EP and 55.29, 53.83 and 46.40 for TP. Pillai’s trace statistics disclosed a significant relationship between CSHQ and CBCL scores regardless of groups (p = 0.04) but the influence of sleep quality did not differ among the groups for any of the three factors. The CSHQ total score was positively and significantly related to IP (p = 0.03, r = 0.47); relationships were not significant for EP (p = 0.96, r = -0.01) and TP (p = 0.17, r = 0.31). Conclusion Sleep quality influences internalizing problems in children, without group-specific relationships, but this association does not seem to differ between gifted, twice exceptional and TD children. Support N/A

scholarly journals Prevalence and Determinants of Bad Sleep Perception among Italian Children and Adolescents

2020 ◽  
Vol 17 (24) ◽  
pp. 9363
Author(s):  
Serena Malloggi ◽  
Francesca Conte ◽  
Giorgio Gronchi ◽  
Gianluca Ficca ◽  
Fiorenza Giganti
Keyword(s):  
Sleep Quality ◽  
Depressed Mood ◽  
Behavioral Problems ◽  
Sleep Disturbances ◽  
Sleep Problems ◽  
Sleep Latency ◽  
Sleep Habits ◽  
Subjective Sleep Quality ◽  
Quality Perception ◽  
Subjective Sleep

Although sleep problems at young ages are well investigated, the prevalence of bad sleepers and the determinants of sleep quality perception remain unexplored in these populations. For this purpose, we addressed these issues in a sample of children (n = 307), preadolescents (n = 717), and adolescents (n = 406) who completed the School Sleep Habits Survey, addressing sleep quality perception, sleep habits, sleep features, daytime behavior and sleep disturbances, circadian preference, and dreaming. The sample was split in “good sleepers” and “bad sleepers”, based on the answer to the question item assessing overall subjective sleep quality. Being a bad sleeper was reported by 11.7% of the sample, with significant between-groups differences (children: 8.3%; preadolescents: 11.3%; adolescents: 15.3%; p = 0.01). At all ages, relative to good sleepers, bad sleepers showed higher eveningness, sleepiness, and depression, longer sleep latency, more frequent insufficient sleep, nocturnal awakenings, sleep–wake behavioral problems, and unpleasant dreams (all p’s ≤ 0.01). Sleep quality perception was predicted: in children, by depressed mood, eveningness, and unpleasant dreams (all p’s ≤ 0.01); in preadolescents, by sleep latency, awakening frequency, depressed mood, sufficiency of sleep, and unpleasant dreams (all p’s < 0.01); in adolescents, by awakening frequency, depressed mood, and sufficiency of sleep (all p’s < 0.001). In children, bad subjective sleep quality appears to be mainly determined by daytime psychological features, for example, depressed mood, whereas at later ages, sleep characteristics, such as frequent awakenings, add to the former determinants. This could depend on (a) the appearance, with increasing age, of objective sleep modifications and (b) a greater attention paid by adolescents to their sleep characteristics.

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