Family asthma management in urban children and its association with sleep outcomes

2021 ◽  
pp. 136749352110147
Author(s):  
Maria T Coutinho ◽  
Clara G Sears ◽  
Rebecca Noga ◽  
Elizabeth L McQuaid ◽  
Sheryl J Kopel ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Management Practices ◽  
Environmental Control ◽  
Asthma Management ◽  
Persistent Asthma ◽  
Structured Interview ◽  
Urban Children ◽  
Quality Data ◽  
Management Interventions

Asthma symptoms impact children’s sleep quality. However, it is unclear how families’ daily management of their child’s asthma is associated with sleep quality. We examine associations between family asthma management components and sleep duration and quality for urban children (ages 7–9 years). Additionally, we examine these associations by racial/ethnic group. Data were collected as part of a longitudinal study that examined the co-occurrence of asthma, allergic rhinitis, sleep quality, and academic functioning for urban children diagnosed with persistent asthma ( N = 196). A semi-structured interview assessed family asthma management practices. Sleep quality data were collected via actigraphy. Our visual depiction of sleep outcomes show that those with higher family asthma management ratings present with longer sleep duration and better sleep quality. Among specific family asthma management components, we found a significant association between children’s adherence to asthma medications and number of nighttime awakenings. For non-Latino Black (NLB) children, we found a significant association between environmental control and sleep duration. For urban children with asthma, clinical strategies to enhance overall family asthma management have the potential to support improved sleep quality. Additionally, for NLB children, asthma management interventions that provide environmental control practices may increase sleep duration.

scholarly journals 0120 Association Between Sleep Duration and Daytime Memory and Cognition Depends on Sleep Quality: Data from the 2017 Israel Social Survey

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A47-A48
Author(s):  
C C Wills ◽  
E A Rosenberg ◽  
M L Perlis ◽  
S Parthasarathy ◽  
S Chakravorty ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Duration ◽  
Quality Data ◽  
Poor Sleep ◽  
Israeli Population ◽  
Long Sleep ◽  
Cognitive Problems ◽  
The Impact ◽  
Sleep Difficulties

Abstract Introduction This study examines the relationship between sleep duration, sleep disturbance, and cognitive problems in a representative sample of the Israeli population. Methods 7,230 Israelis responded to an Israeli Bureau of Statistics population-based survey of households from the year 2017. All variables were self-reported. Outcome of interest was difficulty with memory/concentration (none, mild, or severe). Predictors included previous month sleep duration (<=5hrs, 6hrs, 7hrs [reference], 8hrs, or >=9hrs) and sleep disturbance (none [reference], mild [1/week], moderate [2–3/week], or severe [>3/week]). Covariates included age, sex, ethnic group, and financial status. Multinomial logistic regressions evaluated the relationships between variables, and post-hoc testing identified relationships within specific subgroups. Results 72.9% denied cognitive problems, 22.2% reported mild problems, and 4.9% severe problems. In adjusted analyses, Sleep <=5hrs and >=9hrs were associated with mild (RRR=1.39, p<0.0005), (RRR=1.46, p=0.004) and severe (RRR=2.75, p<0.0005), (RRR=3.24, p<0.0005) cognitive problems, respectively. Mild, moderate, and severe sleep difficulties were associated with mild cognitive problems (RRR=2.09, p<0.0005), (RRR=2.22, p<0.0005), (RRR=2.44, p<0.0005), and severe cognitive problems (RRR=1.77, p=0.001), (RRR=3.04, p<0.0005), (RRR=4.22, p<0.0005), respectively. There was an interaction between sleep duration and sleep difficulties (p<0.05). Among those denying sleep difficulties, only >=9hrs of sleep was associated with cognitive problems. Among those with mild, moderate, and severe sleep difficulties, both short and long sleep were associated with cognitive problems. Conclusion In an Israeli population sample, both sleep duration and quality were associated with cognitive problems. Among those with sleep difficulties, short and long sleep duration were associated with cognitive problems, but among those denying sleep difficulties, only long sleep was associated with cognitive problems. These results suggest that the impact of sleep loss on real-world cognition may also rely on the presence of poor sleep quality. Support Dr. Grandner is supported by R01MD011600

scholarly journals Sleep-Wake Patterns during the Acute Phase after First-Ever Stroke

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Linda N. Bakken ◽  
Kathryn A. Lee ◽  
Hesook Suzie Kim ◽  
Arnstein Finset ◽  
Anners Lerdal
Keyword(s):  
Sleep Quality ◽  
Sleep Time ◽  
Structured Interview ◽  
Quality Data ◽  
Clinical Factors ◽  
Subjective Sleep Quality ◽  
Wake Time ◽  
Subjective Sleep ◽  
Wrist Actigraphy ◽  
Wake Patterns

This study describes the pattern of day and night sleep and explores relationships between these patterns and sociodemographic and clinical factors as well as sleep environmental context and the patient's subjective sleep quality. Data from 110 patients with first-ever stroke was collected by structured interview surveys, medical record, and objective estimated sleep data from wrist actigraphy. The variability in estimated sleep is large. Half the patients slept either <6 hours or >8 hours per night, and 78% had more than nine awakenings per night. Men slept less than women, and patients sleeping at home had fewer awakenings than those who slept in hospital. It was estimated sleep during daytime in all, except 4, patients. Longer stay in hospital was related to more daytime sleep, and the subjective sleep quality correlated with estimated sleep time, wake time, and wake percentage.

scholarly journals Asthma-related lung function, sleep quality, and sleep duration in urban children

Sleep Health ◽  
2017 ◽  
Vol 3 (3) ◽  
pp. 148-156 ◽  
Author(s):  
Daphne Koinis-Mitchell ◽  
Sheryl J. Kopel ◽  
Ronald Seifer ◽  
Monique LeBourgeois ◽  
Elizabeth L. McQuaid ◽  
...  
Keyword(s):  
Lung Function ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Urban Children

Personality and Sleep: Neuroticism and Conscientiousness Predict Behaviourally Recorded Sleep Years Later

2019 ◽  
Vol 33 (2) ◽  
pp. 133-153 ◽  
Author(s):  
Zlatan Križan ◽  
Garrett Hisler
Keyword(s):  
Sleep Quality ◽  
Personality Traits ◽  
Sleep Duration ◽  
The United States ◽  
Subjective Quality ◽  
Quality Data ◽  
Daily Routine ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Sleep Continuity

Sleep is one key feature of people's lives that defines their daily routine and reflects overall health and well–being. To test the relevance of personality for core aspects of sleep, we examined if personality traits across the five broad personality domains predicted behaviourally recorded, week–long sleep characteristics up to five years later (alongside subjective sleep quality). Data from 382 participants (63% female, aged 34–82 years) were drawn from the longitudinal study on Midlife in the United States Study—Biomarker project. In terms of mean tendencies, both neuroticism and conscientiousness signalled more sleep continuity (fewer interruptions) alongside better subjective quality. In terms of intra–individual sleep variability, neuroticism predicted more variability in sleep duration, continuity, and subjective sleep quality, while conscientiousness predicted less variability in sleep duration and sleep continuity. Extraversion, agreeableness, and openness traits did not generally foreshadow behaviourally recoded sleep, only higher ratings of subjective quality. These links were robust to the impact of demographic factors and were not moderated by the duration of time between personality and sleep assessments. The findings distinguish which personality traits foreshadow core aspects of sleep and also implicate multiple traits as predictors of variability, not just mean tendencies, in behaviourally recorded sleep. © 2019 European Association of Personality Psychology

Effects of Quarantine Due to the COVID-19 on Sleep Duration and Quality in Algerians

2020 ◽  
Vol 60 (2) ◽  
pp. 182-193
Author(s):  
Kacem Abdelhadi ◽  
Houar Abdelatif ◽  
Zerf Mohamed ◽  
Bengoua Ali
Keyword(s):  
Statistical Analysis ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Online Survey ◽  
Public Awareness ◽  
Italian Version ◽  
Sleep Timing ◽  
Algerian Population ◽  
Significant Change ◽  
The Impact

SummaryThis study tests the impact of COVID-19 on sleep of Algerian population before and during the COVID-19 quarantine by an estimated online survey, adapted from the PSQI Italian version. Including 1210 participants (age between 18-60 years old). The statistical analysis was carried out using SPSS version 22.0 software. Our results showed a significant change in sleeping quality during quarantine, the sleep timing markedly changed, we also noticed additional use of sleeping medications. Algerian scientists recommend to build public awareness and to provide necessary information regarding Algerian sleep quality, especially for Algerian adults.

621 Association of E-cigarette and Tobacco Use with Adolescent Sleep Quality

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A244-A244
Author(s):  
Clare Malhotra ◽  
Deepti Gunge ◽  
Ira Advani ◽  
Shreyes Boddu ◽  
Sedtavut Nilaad ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Sleep Latency ◽  
Depression Scale ◽  
Mean Difference ◽  
Dual Use ◽  
Safe Alternative ◽  
Wake Time ◽  
Patient Health ◽  
Targeted Marketing

Abstract Introduction Recently, targeted marketing has encouraged teen e-cigarette vaping. Although e-cigarettes are often presented as a safe alternative to conventional tobacco, their toxicity is unclear. In adults, we have previously observed a link between dual usage of e-cigarettes and tobacco with increased sleep latency. We hypothesized an association between dual usage and increased sleep latency. Methods Participants were recruited to complete social media surveys. We performed three surveys: Survey 1 (n=47) in 2018, Survey 2 (n=1198) in 2019, and Survey 3 (n=564) in 2020. Surveys 1 and 2 had three sections: past and current inhalant use, the Pittsburgh Sleep Quality Index (PSQI), and the Leicester Cough Questionnaire (LCQ). Survey 3 did not include the LCQ, instead including the Hospital Anxiety and Depression Scale (HADS) and Patient Health Questionnaire (PHQ9). The adolescent data (aged 13–20 years; n=609) were isolated. Results Adolescents reported an increase in sleep duration with increasing age by one-way ANOVA. Males reported no change with increasing age, while, by Tukey’s multiple comparisons test, females got significantly more sleep at ages 19 and 20 than at age 14(p&lt;0.01). There was no significant correlation between inhalant use and sleep duration. When broken down by gender, female dual users slept more than female nonsmokers,(p=0.01; mean difference=43.8 minutes; CI=0.11 to 1.36), while there was no difference in males. We observed a significant association between inhalant use and sleep(p=0.0008), with dual use correlated with a longer sleep latency than nonsmokers (mean difference=6.27 minutes; CI=1.40 to 11.13. We saw no correlation between inhalant use and anxiety or depression, nor between inhalant use and cough severity and prevalence. Conclusion In female adolescents, we observed a peak in sleep hours at age 19 but significantly less sleep in fourteen-year olds. College-aged females may have a later wake time relative to middle-school and high-school aged females. Dual inhalant use in females was associated with a long sleep duration, raising concern for sleep disruption caused by dual use. Dual use’s association with increased sleep latency raises concern for nicotine-induced wakefulness. Further data are required in order to define public health strategies. Support (if any) LCA is supported by NIH.

scholarly journals 651 Longitudinal, unobtrusive, and ecologically valid sleep metric estimation from a smart bed to predict the pathology of COVID-19

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A255-A255
Author(s):  
Dmytro Guzenko ◽  
Gary Garcia ◽  
Farzad Siyahjani ◽  
Kevin Monette ◽  
Susan DeFranco ◽  
...  
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Predictive Model ◽  
Sleep Duration ◽  
Wearable Sensors ◽  
Test Results ◽  
Cloud Data ◽  
Cardiorespiratory Function ◽  
Group Data ◽  
Rich Information

Abstract Introduction Pathophysiologic responses to viral respiratory challenges such as SARS-CoV-2 may affect sleep duration, quality and concomitant cardiorespiratory function. Unobtrusive and ecologically valid methods to monitor longitudinal sleep metrics may therefore have practical value for surveillance and monitoring of infectious illnesses. We leveraged sleep metrics from Sleep Number 360 smart bed users to build a COVID-19 predictive model. Methods An IRB approved survey was presented to opting-in users from August to November 2020. COVID-19 test results were reported by 2003/6878 respondents (116 positive; 1887 negative). From the positive group, data from 82 responders (44.7±11.3 yrs.) who reported the date of symptom onset were used. From the negative group, data from 1519 responders (48.4±12.9 yrs.) who reported testing dates were used. Sleep duration, sleep quality, restful sleep duration, time to fall asleep, respiration rate, heart rate, and motion level were obtained from ballistocardiography signals stored in the cloud. Data from January to October 2020 were considered. The predictive model consists of two levels: 1) the daily probability of staying healthy calculated by logistic regression and 2) a continuous density Hidden Markov Model to refine the daily prediction considering the past decision history. Results With respect to their baseline, significant increases in sleep duration, average breathing rate, average heart rate and decrease in sleep quality were associated with symptom exacerbation in COVID-19 positive respondents. In COVID-19 negative respondents, no significant sleep or cardiorespiratory metrics were observed. Evaluation of the predictive model resulted in cross-validated area under the receiving-operator curve (AUC) estimate of 0.84±0.09 which is similar to values reported for wearable-sensors. Considering additional days to confirm prediction improved the AUC estimate to 0.93±0.05. Conclusion The results obtained on the smart bed user population suggest that unobtrusive sleep metrics may offer rich information to predict and track the development of symptoms in individuals infected with COVID-19. Support (if any):

scholarly journals 653 Are Daily Variations in Sleep Quality and Quantity Related to General Stress and COVID-19-Related Anxiety?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A255-A256
Author(s):  
Veronica Hire ◽  
Casey Thurmon ◽  
Hope Snyder ◽  
Ryan Harra ◽  
Jamie Walker ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Fixed Effects ◽  
Daily Basis ◽  
Subjective Rating ◽  
Coping With Stress ◽  
Sleep Diaries ◽  
Daily Variations ◽  
General Stress ◽  
Stress Levels

Abstract Introduction Sleep modulates a number of psychological and cognitive processes, such as emotion regulation, executive control, and coping with stress. It is therefore not surprising that insufficient sleep quality or quantity are associated with greater self-reported stress levels. The COVID-19 pandemic has led to a particularly stressful and unprecedented time in history. While stress has been undoubtedly high during the past year, it’s less clear to what extent sleep has affected people’s perceived stress on a daily basis. The aim of this research was to estimate whether daily variations in sleep quality and duration were associated with general stress and/or stress related to COVID-19. Methods The study used a nationally representative sample to assess daily variations in sleep and stress for a period of two weeks during the COVID-19 pandemic. Morning assessments were conducted using online sleep diaries. These diaries were used to estimate sleep duration (in minutes) and sleep quality (subjective rating on a 5-point Likert scale). Evening assessments were also completed online and prompted participants to rate (0 to 100) their current “general” stress level, as well as their current anxiety in relation to COVID-19. Separate mixed effects models were conducted with days (Level 1) nested within participants (Level 2). Stress variables were lagged by a day to estimate the association between sleep (AM assessment) and stress (PM assessment). TST and SQ were entered as fixed effects and intercepts were allowed to vary randomly. Results 4,048 participants (Mage = 46.3 years; 78% women) were included as part of the analyses. The results supported that lower self-reported sleep quality predicted greater general stress levels (b = -1.43, p &lt; 0.001). Lower self-reported sleep quality also predicted greater COVID-19 related anxiety (b = -0.543, p &lt; 0.001). In contrast, sleep duration was not significantly related to general stress or COVID-19 anxiety after controlling for sleep quality. Conclusion The present data supports that daily variations in sleep quality are related to a person’s overall stress levels and COVID-19 anxiety. These findings may have implications for the role of good sleep in mitigating the increases in stress that have resulted from the COVID-19 pandemic. Support (if any) Vargas: K23HL141581

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