@article {834, title = {Association of sleep time with diabetes mellitus and impaired glucose tolerance.}, journal = {Arch Intern Med}, volume = {165}, year = {2005}, month = {2005 Apr 25}, pages = {863-7}, abstract = {

BACKGROUND: Experimental sleep restriction causes impaired glucose tolerance (IGT); however, little is known about the metabolic effects of habitual sleep restriction. We assessed the cross-sectional relation of usual sleep time to diabetes mellitus (DM) and IGT among participants in the Sleep Heart Health Study, a community-based prospective study of the cardiovascular consequences of sleep-disordered breathing.

METHODS: Participants were 722 men and 764 women, aged 53 to 93 years. Usual sleep time was obtained by standardized questionnaire. Diabetes mellitus was defined as a serum glucose level of 126 mg/dL or more (> or =7.0 mmol/L) fasting or 200 mg/dL or more (> or =11.1 mmol/L) 2 hours following standard oral glucose challenge or medication use for DM. Impaired glucose tolerance was defined as a 2-hour postchallenge glucose level of 140 mg/dL or more (> or =7.8 mmol/L) and less than 200 mg/dL. The relation of sleep time to DM and IGT was examined using categorical logistic regression with adjustment for age, sex, race, body habitus, and apnea-hypopnea index.

RESULTS: The median sleep time was 7 hours per night, with 27.1\% of subjects sleeping 6 hours or less per night. Compared with those sleeping 7 to 8 hours per night, subjects sleeping 5 hours or less and 6 hours per night had adjusted odds ratios for DM of 2.51 (95\% confidence interval, 1.57-4.02) and 1.66 (95\% confidence interval, 1.15-2.39), respectively. Adjusted odds ratios for IGT were 1.33 (95\% confidence interval, 0.83-2.15) and 1.58 (95\% confidence interval, 1.15-2.18), respectively. Subjects sleeping 9 hours or more per night also had increased odds ratios for DM and IGT. These associations persisted when subjects with insomnia symptoms were excluded.

CONCLUSIONS: A sleep duration of 6 hours or less or 9 hours or more is associated with increased prevalence of DM and IGT. Because this effect was present in subjects without insomnia, voluntary sleep restriction may contribute to the large public health burden of DM.

}, keywords = {Age Factors, Aged, Aged, 80 and over, Blood Glucose, Diabetes Mellitus, Disease Progression, Female, Glucose Intolerance, Humans, Male, Middle Aged, Odds Ratio, Prevalence, Prospective Studies, Sleep, Surveys and Questionnaires, Time Factors, United States}, issn = {0003-9926}, doi = {10.1001/archinte.165.8.863}, author = {Gottlieb, Daniel J and Punjabi, Naresh M and Newman, Ann B and Resnick, Helaine E and Redline, Susan and Baldwin, Carol M and Nieto, F Javier} } @article {1252, title = {A novel approach to prediction of mild obstructive sleep disordered breathing in a population-based sample: the Sleep Heart Health Study.}, journal = {Sleep}, volume = {33}, year = {2010}, month = {2010 Dec}, pages = {1641-8}, abstract = {

This manuscript considers a data-mining approach for the prediction of mild obstructive sleep disordered breathing, defined as an elevated respiratory disturbance index (RDI), in 5,530 participants in a community-based study, the Sleep Heart Health Study. The prediction algorithm was built using modern ensemble learning algorithms, boosting in specific, which allowed for assessing potential high-dimensional interactions between predictor variables or classifiers. To evaluate the performance of the algorithm, the data were split into training and validation sets for varying thresholds for predicting the probability of a high RDI (>=7 events per hour in the given results). Based on a moderate classification threshold from the boosting algorithm, the estimated post-test odds of a high RDI were 2.20 times higher than the pre-test odds given a positive test, while the corresponding post-test odds were decreased by 52\% given a negative test (sensitivity and specificity of 0.66 and 0.70, respectively). In rank order, the following variables had the largest impact on prediction performance: neck circumference, body mass index, age, snoring frequency, waist circumference, and snoring loudness.

}, keywords = {Age Factors, Aged, Algorithms, Body Mass Index, Cohort Studies, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Risk Factors, ROC Curve, Sleep Apnea Syndromes, Snoring, Waist Circumference}, issn = {0161-8105}, author = {Caffo, Brian and Diener-West, Marie and Punjabi, Naresh M and Samet, Jonathan} } @article {1253, title = {Utility of sleep stage transitions in assessing sleep continuity.}, journal = {Sleep}, volume = {33}, year = {2010}, month = {2010 Dec}, pages = {1681-6}, abstract = {

STUDY OBJECTIVES: Sleep continuity is commonly assessed with polysomnographic measures such as sleep efficiency, sleep stage percentages, and the arousal index. The aim of this study was to examine whether the transition rate between different sleep stages could be used as an index of sleep continuity to predict self-reported sleep quality independent of other commonly used metrics.

DESIGN AND SETTING: Analysis of the Sleep Heart Health Study polysomnographic data.

PARTICIPANTS: A community cohort.

MEASUREMENTS AND RESULTS: Sleep recordings on 5,684 participants were deemed to be of sufficient quality to allow visual scoring of NREM and REM sleep. For each participant, we tabulated the frequency of transitions between wake, NREM sleep, and REM sleep. An overall transition rate was determined as the number of all transitions per hour sleep. Stage-specific transition rates between wake, NREM sleep, and REM sleep were also determined. A 5-point Likert scale was used to assess the subjective experience of restless and light sleep the morning after the sleep study. Multivariable regression models showed that a high overall sleep stage transition rate was associated with restless and light sleep independent of several covariates including total sleep time, percentages of sleep stages, wake time after sleep onset, and the arousal index. Compared to the lowest quartile of the overall transition rate (<7.76 events/h), the odds ratios for restless sleep were 1.27, 1.42, and 1.38, for the second (7.77-10.10 events/h), third (10.11-13.34 events/h), and fourth (>=13.35 events/h) quartiles, respectively. Analysis of stage-specific transition rates showed that transitions between wake and NREM sleep were also independently associated with restless and light sleep.

CONCLUSIONS: Assessing overall and stage-specific transition rates provides a complementary approach for assessing sleep continuity. Incorporating such measures, along with conventional metrics, could yield useful insights into the significance of sleep continuity for clinical outcomes.

}, keywords = {Age Factors, Aged, Arousal, Body Mass Index, Cohort Studies, Female, Humans, Male, Middle Aged, Polysomnography, Predictive Value of Tests, Risk Factors, Sex Factors, Sleep Stages, Sleep Wake Disorders}, issn = {0161-8105}, author = {Laffan, Alison and Caffo, Brian and Swihart, Bruce J and Punjabi, Naresh M} } @article {1540, title = {Sleep-disordered breathing and caffeine consumption: results of a community-based study.}, journal = {Chest}, volume = {142}, year = {2012}, month = {2012 Sep}, pages = {631-638}, abstract = {

BACKGROUND: Sleepiness is one of the most burdensome symptoms of sleep-disordered breathing (SDB). While caffeine is frequently used to avert sleepiness, the association between SDB and caffeine use has not been thoroughly explored. The current study examined whether SDB is associated with caffeine consumption and if factors such as sex, age, and daytime sleepiness explain or modify the association.

METHODS: Data from the Sleep Heart Health Study, a community-based study on the consequences of SDB, were used to characterize the association between SDB and caffeine intake. SDB was assessed with full-montage polysomnography. Caffeine use was quantified as the number of cans of soda or the cups of coffee or tea consumed daily. The Epworth Sleepiness Scale was used to assess daytime sleepiness. Multivariable negative binomial regression models were used to characterize the independent association between SDB and caffeine use.

RESULTS: Caffeinated soda, but not tea or coffee, intake was independently associated with SDB severity. Compared with participants without SDB, the relative ratios for caffeinated soda consumption in women with mild, moderate, and severe SDB were 1.20 (CI, 1.03-1.41), 1.46 (CI, 1.14-1.87), and 1.73 (CI, 1.23-2.42), respectively. For men, an association was only noted with severe SDB and caffeinated soda use. Age did not modify the SDB-caffeine association, and sleepiness could not explain the observed associations.

CONCLUSIONS: SDB is independently associated with caffeinated soda use in the general community. Identifying excessive caffeine used in SDB has potential significance given the cardiovascular effects of caffeine and untreated SDB.

}, keywords = {Age Factors, Aged, Caffeine, Carbonated Beverages, Coffee, Data Collection, Drinking Behavior, Female, Humans, Male, Middle Aged, Polysomnography, Prevalence, Retrospective Studies, Sex Factors, Sleep Apnea Syndromes, Tea}, issn = {1931-3543}, doi = {10.1378/chest.11-2894}, author = {Aurora, R Nisha and Crainiceanu, Ciprian and Caffo, Brian and Punjabi, Naresh M} }