Information processing in sleep-onset insomnia : a test of the neurocognitive model /

The present thesis study is a systematic investigation of information processing at sleep onset, using auditory event-related potentials (ERPs) as a test of the neurocognitive model of insomnia. Insomnia is an extremely prevalent disorder in society resulting in problems with daytime functioning (e.g., memory, concentration, job performance, mood, job and driving safety). Various models have been put forth in an effort to better understand the etiology and pathophysiology of this disorder. One of the newer models, the neurocognitive model of insomnia, suggests that chronic insomnia occurs through conditioned central nervous system arousal. This arousal is reflected through increased information processing which may interfere with sleep initiation or maintenance. The present thesis employed event-related potentials as a direct method to test information processing during the sleep-onset period. Thirteen poor sleepers with sleep-onset insomnia and 1 2 good sleepers participated in the present study. All poor sleepers met the diagnostic criteria for psychophysiological insomnia and had a complaint of problems with sleep initiation. All good sleepers reported no trouble sleeping and no excessive daytime sleepiness. Good and poor sleepers spent two nights at the Brock University Sleep Research Laboratory. The first night was used to screen for sleep disorders; the second night was used to investigate information processing during the sleep-onset period. Both groups underwent a repeated sleep-onsets task during which an auditory oddball paradigm was delivered. Participants signalled detection of a higher pitch target tone with a button press as they fell asleep. In addition, waking alert ERPs were recorded 1 hour before and after sleep on both Nights 1 and 2.As predicted by the neurocognitive model of insomnia, increased CNS activity was found in the poor sleepers; this was reflected by their smaller amplitude P2 component seen during wake of the sleep-onset period. Unlike the P2 component, the Nl, N350, and P300 did not vary between the groups. The smaller P2 seen in our poor sleepers indicates that they have a deficit in the sleep initiation processes. Specifically, poor sleepers do not disengage their attention from the outside environment to the same extent as good sleepers during the sleep-onset period. The lack of findings for the N350 suggest that this sleep component may be intact in those with insomnia and that it is the waking components (i.e., Nl, P2) that may be leading to the deficit in sleep initiation. Further, it may be that the mechanism responsible for the disruption of sleep initiation in the poor sleepers is most reflected by the P2 component. Future research investigating ERPs in insomnia should focus on the identification of the components most sensitive to sleep disruption. As well, methods should be developed in order to more clearly identify the various types of insomnia populations in research contexts (e.g., psychophysiological vs. sleep-state misperception) and the various individual (personality characteristics, motivation) and environmental factors (arousal-related variables) that influence particular ERP components. Insomnia has serious consequences for health, safety, and daytime functioning, thus research efforts should continue in order to help alleviate this highly prevalent condition.

Comparison of non-HDL cholesterol and waist circumference vs. triglyceride levels and waist circumference in predicting coronary heart disease risk

BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.