Polysomnographic correlates of inflammatory complement components in young healthy males.

A growing body of evidence has delineated the predominant role of humoral mediators of inflammation in linking sleep with immunity. Nonetheless, characterization of the relationship between complement components with inflammatory functions and objective sleep measures has not been performed. In this study we investigated the relationships between objective measures of sleep and complement components with inflammatory functions. Thirty-six healthy male university students (age, 23.94±4.23 years; BMI, 23.44±2.67 kg/m(2)) completed the study. An RMS Quest 32 polysomnograph (PSG) was used for sleep recording. Non-fasting blood was collected before subjects went to bed on the second night in the sleep laboratory to estimate complement component 3 (C-3), complement component 4 (C-4), complement factor-H (Factor-H), C1-inhibitor (C1INH), complement factor I (CFI) and other inflammatory mediators, such as IL-6 and sICAM-1. Multiple linear regression analysis was used to assess the association between PSG sleep measures and inflammatory mediators. Higher values of C-3 and lower values of sICAM-1, C1INH, and CFI (adjusted model, R2=0.211, p<0.041) predicted longer sleep duration. Lower C-3 (adjusted model, R2=0.078, p<0.055) predicted higher N1 (%). Higher levels of C1INH and CFI and lower values of C-4 (model adjusted R2=0.269, p<0.008) predicted higher N3 (%). Higher C-3, higher C-4, lower IL-6, lower C1INH and lower CFI (model adjusted R2=0.296, p<0.007) predicted higher REM (%). Poor sleep measures were associated with increased levels of pro-inflammatory complement components and decreased anti-inflammatory complement components.

Dimensionality of the Pittsburgh Sleep Quality Index in the collegiate young adults.

PURPOSE: To explore and validate the factor structure of the Pittsburgh Sleep Quality Index (PSQI) in the collegiate young adults. METHODS: Six hundred university students were initially contacted and invited to participate in a survey of their sleep experience and history. Of this preliminary sample 418 of the students (age = 20.92 ± 1.81 years, BMI = 23.30 ± 2.57 kg/m(2)) fulfilled the screening criteria and ultimately completed the Pittsburgh Sleep Quality Index (PSQI), a self-report survey of respondents' sleep habits and sleep quality. The students were enrolled in various undergraduate and postgraduate programs at Jamia Millia Islamia, New Delhi, India. Exploratory factor analysis (EFA) investigated the latent factor structure of the scale. Confirmatory factor analysis evaluated both of the models found by EFA. RESULTS: The Kaiser's criteria, the Scree test, and the cumulative variance rule revealed that a 2-factor model accounted for most of the variability in the data. However, a follow up Parallel Analysis found a 1-factor model. The high correlation coefficient (r = 0.91) between the two factors of the 2-factor model and almost similar values of the fit indices supports the inference that the PSQI is a unidimensional scale. CONCLUSIONS: The findings validate the 1-factor model of the PSQI in the collegiate young adults.

Spontaneous K-Complex Density in Slow-Wave Sleep.

PURPOSE: To study spontaneous K-complex (KC) densities during slow-wave sleep. The secondary objective was to estimate intra-non-rapid eye movement (NREM) sleep differences in KC density. MATERIALS AND METHODS: It is a retrospective study using EEG data included in polysomnographic records from the archive at the sleep research laboratory of the Centre for Physiotherapy and Rehabilitation Sciences, Jamia Millia Islamia, India. The EEG records of 4459 minutes were used. The study presents a manual identification investigation of KCs in 17 healthy young adult male volunteers (age = 23.82±3.40 years and BMI = 23.42±4.18 kg/m2). RESULTS: N3 had a higher KC density than N2 (Z = -2.485, p = 0.013) for all of the probes taken together. Four EEG probes had a higher probe-specific KC density during N3. The inter-probe KC density differed significantly during N2 (χ2 = 67.91, p < .001), N3 (χ2 = 70.62, p < .001) and NREM (χ2 = 68.50, p < .001). The percent distribution of KC decreased uniformly with sleep cycles. CONCLUSION: The inter-probe differences during N3 establish the fronto-central dominance of the KC density regardless of sleep stage. This finding supports one local theory of KC generation. The significantly higher KC density during N3 may imply that the neuro-anatomical origin of slow-wave activity and KC is the same. This temporal alignment with slow-wave activity supports the sleep-promoting function of the KC.

Association between sleep quality and inflammatory complement components in collegiate males.

BACKGROUND: An accumulating amount of evidence has linked humoral mediators of inflammation with sleep measures. Nevertheless, important details of this association, in particular the role of the complement components in the context of chronic sleep attributes, have remained largely uncharacterized. MATERIALS AND METHODS: Fifty university students (age, 23.3 ± 3.8 years; BMI, 23.7 ± 2.9 kg/m(2)) completed the study. Four dichotomized sleep measures assessed by the Pittsburgh Sleep Quality Index (PSQI) were used in association analysis using binary logistic regression with complement component 3, 4, and complement factor I (CFI). The sleep measures were defined as sleep quality (good sleep/poor sleep; PSQI ≤5/PSQI >5), bedtime (early/late; before 00:00 h/after 0:00 h), sleep duration (short/normal ≤6 h/>6 h), and sleep onset latency (normal/disturbed; 0-1 score/2-3 score on the PSQI component of sleep latency). RESULTS: The complement component 4 was associated with sleep quality (unadjusted, OR = 1.025, p < 0.05; adjusted for age, OR = 1.025, p < 0.05; adjusted for BMI, OR = 1.027, p < 0.05) and sleep duration (unadjusted, OR = 1.041, p < 0.01; adjusted for age, OR = 1.041, p < 0.01; adjusted for BMI, OR = 1.046, p < 0.01). CFI was associated with bedtime (unadjusted, OR = 0.737, p < 0.01; adjusted for age, OR = 0.717, p < 0.01; adjusted for BMI, OR = 0.677, p < 0.01) and with sleep duration (unadjusted, OR = 0.796, p < 0.05; adjusted for age, OR = 0.796, p < 0.05). CONCLUSION: The findings indicate the importance of the role of complement components in the dynamics of sleep. Therefore, sleep should be assessed in conditions where complement components are affected.

Validity of the Pittsburgh Sleep Quality Index in Indian University Students.

OBJECTIVES: Despite the demonstrated utility of the Pittsburgh Sleep Quality Index (PSQI) in various demographic groups, it has never been validated in a sample of Indian subjects. To extend and confirm the PSQI's applicability for South Asian subjects, this preliminary study aimed to assess its psychometric and diagnostic validity in a sample of university students. METHODS: Forty-seven male students were recruited from Jamia Millia Islamia, a public central university in New Delhi, India. The mean age of the students was 23.4±3.9 years, and they had a mean body mass index (BMI) of 23.3±3.3kg/m(2). The PSQI was administered to all subjects and overnight polysomnographic testing was carried out as a concurrent validation measure. RESULTS: Cronbach's alpha for the questionnaire was found to be 0.736. Internal homogeneity was high, with the majority of correlations between questionnaire component scores and the summed global score being significant (p<0.010). Criterion validity-correlations between the PSQI global score and polysomnography (PSG) measures were low. However, the questionnaire component scores and the related polysomnographic measures did show some significant relationships. The optimal cut-off scores for distinguishing students with/without sleep problems was >6 and was generated using receiver operating characteristic curve analysis. The area under the curve, sensitivity, specificity, positive and negative likelihood ratios at the cut-off score were 0.838 (p<0.0001), 75.0%, 88.9%, 6.75, and 0.280, respectively. CONCLUSION: The study found evidence that the PSQI had internal consistency, internal homogeneity, and diagnostic characteristics that compared well with PSG among a sample of young adult male students in India. This supports the applicability and certain aspects of the validity of the PSQI in the population.

Sleep in university students across years of university education and gender influences.

PURPOSE: Assessment of the influence of gender and increasing years at university on sleep health of students. METHODS: Four hundred and eighteen students from different streams across years of undergraduate to postgraduate courses participated. Descriptive statistics, test of differences, and correlation were used. The sleep health data comprised of subjective evaluation using a questionnaire and personal interviews. RESULTS: Overall, 43.1% had sleep problems, females were more affected (51.67% vs. 48.33% in males) but were early bed goers. The prevalence of circadian rhythm sleep disorder (11.6% vs. 9.5%) and delayed sleep phase syndrome (4.5% vs. 2.7%) was slightly higher in males. The daytime dysfunction and hypnotic use significantly differed in students of the same class among gender. Bedtime got significantly delayed along years [H(2)=29.769, p<0.001], and hypnotic use [H(2)=8.807, p=0.012] differed significantly among them. The moderate-very strong correlational statistics among sleep health elements was very similar across gender and years of university education. However, more pronounced influence of years of university education than gender was seen in the significant differences for correlated correlation among sleep health parameters. CONCLUSION: Gender and years of university education influence sleep among university students both separately and concomitantly.