Age modulates the predictive value of self-reported sleepiness for all-cause mortality risk: insights from a comprehensive national database of veterans.

STUDY OBJECTIVES: Excessive daytime sleepiness (EDS) is prevalent and overwhelmingly stems from disturbed sleep. We hypothesized that age modulates the association between EDS and increased all-cause mortality. METHODS: We utilized the Veterans' Health Administration data from 1999-2022. We enrolled participants with sleep related ICD9/10 codes or sleep services. A natural language processing (NLP) pipeline was developed and validated to extract the Epworth Sleepiness Scale (ESS) as a self-reported tool to measure EDS from physician progress notes. The NLP's accuracy was assessed through manual annotation of 470 notes. Participants were categorized into Normal-ESS, n-ESS, (ESS 0-10) and high-ESS, h-ESS, (ESS 11-24). We created three age groups: < 50 years; 50 to < 65 years; and ≥ 65 years. The adjusted odds ratio (aOR) of mortality was calculated for age, BMI, sex, race, ethnicity, and the Charlson Comorbidity Index (CCI), using n-ESS as the reference. Subsequently, we conducted age stratified analysis. RESULTS: The first ESS records were extracted from 423,087 veterans with a mean age of 54.8 (±14.6), mean BMI of 32.6 (±6.2), and 90.5% male. The aOR across all ages was 17% higher (1.15,1.19) in the h-ESS category. The aORs only became statistically significant for individuals aged ≥ 50 years in the h-ESS compared to the n-ESS category (< 50 years: 1.02 [0.96,1.08], 50 to < 65 years 1.13[1.10,1.16]; ≥ 65 years: 1.25 [1.21-1.28]). CONCLUSIONS: High ESS, predicted increased mortality only in participants aged 50 and older. Further research is required to identify this differential behavior in relation to age.

Sleep duration and its relationship with school performance in Iranian adolescents.

BACKGROUND: Inadequate or poor sleep quality is common problems in adolescent that affect on their learning, memory and school performance. The present study aimed to determine the association between sleep hours and academic performance in young adults. METHODS: This cross-sectional study was designed as a descriptive-analytic study. Samples of adolescents of 14-18 years old in Qazvin city were enrolled. The Pediatric sleep questionnaire and BEARS questionnaire used for all students to screen comprehensively major sleeps problems in them. Chi-square test, t-test, analysis of variance (ANOVA), and correlation were performed to determine the relationship between the data (P < 0.001). RESULTS: Between 653 adolescents, 40% were male and 60% were female. Sleep duration, sleep onset delay, sleep insufficient, rate of oversleeping and academic performance had a direct relationship with gender (P < 0.001). The sleep duration, rate of oversleeping and academic performance were significantly higher in boys, sleep onset delay and sleep insufficient was significantly higher in girls. Time of falling sleep at weekend nights and weekday nights have positively correlation with age (P < 0.001). Also, a significant relationship between students' sleep hours with academic performance was shown (P < 0.001). CONCLUSIONS: The overall result was that sleep duration, sleep onset delay, sleep insufficient and rate of oversleeping of students in this study had a significant influence on academic performance. Students without difficulty in falling asleep had good academic performance in compared to students with difficulty in falling asleep.

Sleep architecture and obstructive sleep apnea in obese children with and without metabolic syndrome: a case control study.

PURPOSE: Obesity and biochemical parameters of metabolic disorders are both closely related to obstructive sleep apnea (OSA). The aim of this study was to compare sleep architecture and OSA in obese children with and without metabolic syndrome. METHODS: Forty-two children with metabolic syndrome were selected as case group and 38 children without metabolic syndrome were matched for age, sex, and BMI as control group. The standardized Persian version of bedtime problems, excessive daytime sleepiness, awakenings during the night, regularity and duration of sleep, snoring (BEARS) and Children's Sleep Habits Questionnaires were completed, and polysomnography (PSG) was performed for all study subjects. Scoring was performed using the manual of American Academy of Sleep Medicine for children. Data were analyzed using chi-square test, T test, Mann-Whitney U test, and logistic regression analysis. RESULTS: Non-rapid eye movement (NREM) sleep and N1 stage in the case group were significantly longer than the control group, while REM sleep was significantly shorter. Waking after sleep onset (WASO) was significantly different between two groups. Severe OSA was more frequent in the control group. Multivariate logistic regression analysis showed that severe OSA (OR 21.478, 95 % CI 2.160-213.600; P = 0.009) and REM sleep (OR 0.856, 95 % CI 0.737-0.994; P = 0.041) had independent association with metabolic syndrome. CONCLUSIONS: Obese children with metabolic syndrome had increased WASO, N1 sleep stage, and severe OSA. But the results regarding sleep architecture are most likely a direct result of OSA severity. More longitudinal studies are needed to confirm the association of metabolic syndrome and OSA.