@article {996, title = {Relationship between reported and measured sleep times: the sleep heart health study (SHHS).}, journal = {J Clin Sleep Med}, volume = {3}, year = {2007}, month = {2007 Oct 15}, pages = {622-30}, abstract = {

STUDY OBJECTIVE: Subjective and objective assessments of sleep may be discrepant due to sleep misperception and measurement effects, the latter of which may change the quality and quantity of a person{\textquoteright}s usual sleep. This study compared sleep times from polysomnography (PSG) with self-reports of habitual sleep and sleep estimated on the morning after a PSG in adults.

DESIGN: Total sleep time and sleep onset latency obtained from unattended home PSGs were compared to sleep times obtained from a questionnaire completed before the PSG and a Morning Survey completed the morning after the PSG.

PARTICIPANTS: A total of 2,113 subjects who were > or = 40 years of age were included in this analysis.

MEASURES AND RESULTS: Subjects were 53\% female, 75\% Caucasian, and 38\% obese. The mean habitual sleep time (HABTST), morning estimated sleep time (AMTST), and PSG total sleep times (PSGTST) were 422 min, 379 min, and 363 min, respectively. The mean habitual sleep onset latency, morning estimated sleep onset latency, and PSG sleep onset latency were 17.0 min, 21.8 min, and 16.9 min, respectively. Models adjusting for related demographic factors showed that HABTST and AMTST differ significantly from PSGTST by 61 and 18 minutes, respectively. Obese and higher educated people reported less sleep time than their counterparts. Similarly, small but significant differences were seen for sleep latency.

CONCLUSIONS: In a community population, self-reported total sleep times and sleep latencies are overestimated even on the morning following overnight PSG.

}, keywords = {Adult, Attitude to Health, Female, Health Status, Humans, Male, Middle Aged, Polysomnography, Psychometrics, Sleep Initiation and Maintenance Disorders, Sleep Stages, Surveys and Questionnaires, Time Factors, Wakefulness}, issn = {1550-9389}, author = {Silva, Graciela E and Goodwin, James L and Sherrill, Duane L and Arnold, Jean L and Bootzin, Richard R and Smith, Terry and Walsleben, Joyce A and Baldwin, Carol M and Quan, Stuart F} } @article {1059, title = {Effect of sleep disordered breathing on the sleep of bed partners in the Sleep Heart Health Study.}, journal = {Sleep}, volume = {31}, year = {2008}, month = {2008 Oct}, pages = {1449-56}, abstract = {

OBJECTIVE: To study the sleep quality of bed partners of persons with sleep disordered breathing in a non-clinical population based sample in a home environment.

DESIGN: Cross-sectional study in a community sample.

METHODS: 110 pairs of subjects living in the same household from the Tucson, Minnesota, and Pittsburgh sites of the Sleep Heart Health Study (SHHS) were included if both partners had an in-home, unattended polysomnogram (PSG) performed as a part of SHHS exam cycle 2. Sleep disordered breathing (SDB) was considered present if the respiratory disturbance index (RDI) was > or =10 events/h and no SDB if RDI was <5 events/h. Pairs were classified according to their SDB status and assigned to one of 3 groups: 1) NoSDB-NoSDB (n = 46), 2) NoSDB-SDB (n = 42), and 3) SDB-SDB (n = 22).

RESULTS: There were no differences between the NoSDB-NoSDB and the SDB-SDB partners in their demographic, PSG, or quality of life variables. However, within the NoSDB-SDB group, NoSDB in comparison to their SDB partners weighed less (mean BMI: 26 vs. 29 kg/m2, P < 0.0003), had decreased stage 2\% (55 vs. 64, P < 0.0001), increased stage 3 and 4\% (21 vs. 11, P <0.0005) and a lower arousal index (13.8 vs. 20 events/h, P < 0.0001). When comparing the NoSDB subjects from the NoSDB-SDB group to subjects in the NoSDB-NoSDB group and to subjects in the SDB-SDB group, significant differences were seen for RDI and BMI but not for any other parameter.

CONCLUSION: In a non-clinical population based sample, the sleep quality of bed partners of SDB subjects without SDB is better than their SDB bed partner. However, their sleep quality was not different in comparison to the sleep of those without SDB who also had a bed partner without SDB.

}, keywords = {Aged, Arousal, Cohort Studies, Female, Humans, Male, Middle Aged, Polysomnography, Quality of Life, Sleep Apnea, Obstructive, Snoring, Spouses}, issn = {0161-8105}, author = {Sharief, Imran and Silva, Graciela E and Goodwin, James L and Quan, Stuart F} } @article {1125, title = {Longitudinal evaluation of sleep-disordered breathing and sleep symptoms with change in quality of life: the Sleep Heart Health Study (SHHS).}, journal = {Sleep}, volume = {32}, year = {2009}, month = {2009 Aug}, pages = {1049-57}, abstract = {

STUDY OBJECTIVES: Findings from population studies evaluating the progression and incidence of sleep disordered breathing have shown evidence of a longitudinal increase in the severity of sleep disordered breathing. The present study evaluates the association among changes in sleep disordered breathing, sleep symptoms, and quality of life over time.

DESIGN: Prospective cohort study. Data were from the Sleep Heart Health Study.

SETTING: Multicenter study.

PARTICIPANTS: Three thousand seventy-eight subjects aged 40 years and older from the baseline and follow-up examination cycles were included.

MEASUREMENTS: The primary outcomes were changes in the Physical Component Summary and Mental Component Summary scales obtained from the Medical Outcomes Study Short-Form Health Survey. The primary exposure was change in the respiratory disturbance index obtained from unattended overnight polysomnograms performed approximately 5 years apart. Other covariates included measures of excessive daytime sleepiness and difficulty initiating and maintaining sleep.

RESULTS: Mean respiratory disturbance index increased from 8.1 +/- 11 SD at baseline to 10.9 +/- 14 (P < 0.0001) at follow-up. The mean Physical Component Summary and Mental Component Summary scores were 48.5 and 54.1 at baseline and 46.3 and 54.8 at follow-up. No associations between change in respiratory disturbance index and changes in Physical Component Summary or Mental Component Summary scores were seen. However, worsening of difficulty initiating and maintaining sleep and excessive daytime sleepiness were significantly associated with lower quality of life.

CONCLUSIONS: A slight increase in severity of sleep disordered breathing was seen over 5 years; this was not associated with worsening of quality of life. However, subjective symptoms of quality of sleep and daytime sleepiness were associated with declining quality of life.

}, keywords = {Aged, Attitude to Health, Cohort Studies, Comorbidity, Disease Progression, Disorders of Excessive Somnolence, Female, Humans, Longitudinal Studies, Male, Middle Aged, Polysomnography, Quality of Life, Sleep Apnea, Obstructive, Sleep Initiation and Maintenance Disorders}, issn = {0161-8105}, author = {Silva, Graciela E and An, Ming-Wen and Goodwin, James L and Shahar, Eyal and Redline, Susan and Resnick, Helaine and Baldwin, Carol M and Quan, Stuart F} } @article {1342, title = {Identification of patients with sleep disordered breathing: comparing the four-variable screening tool, STOP, STOP-Bang, and Epworth Sleepiness Scales.}, journal = {J Clin Sleep Med}, volume = {7}, year = {2011}, month = {2011 Oct 15}, pages = {467-72}, abstract = {

STUDY OBJECTIVE: The Epworth Sleepiness Scale (ESS) has been used to detect patients with potential sleep disordered breathing (SDB). Recently, a 4-Variable screening tool was proposed to identify patients with SDB, in addition to the STOP and STOP-Bang questionnaires. This study evaluated the abilities of the 4-Variable screening tool, STOP, STOP-Bang, and ESS questionnaires in identifying subjects at risk for SDB.

METHODS: A total of 4,770 participants who completed polysomnograms in the baseline evaluation of the Sleep Heart Health Study (SHHS) were included. Subjects with RDIs >= 15 and >= 30 were considered to have moderate-to-severe or severe SDB, respectively. Variables were constructed to approximate those in the questionnaires. The risk of SDB was calculated by the 4-Variable screening tool according to Takegami et al. The STOP and STOP-Bang questionnaires were evaluated including variables for snoring, tiredness/sleepiness, observed apnea, blood pressure, body mass index, age, neck circumference, and gender. Sleepiness was evaluated using the ESS questionnaire and scores were dichotomized into < 11 and >= 11.

RESULTS: The STOP-Bang questionnaire had higher sensitivity to predict moderate-to-severe (87.0\%) and severe (70.4\%) SDB, while the 4-Variable screening tool had higher specificity to predict moderate-to-severe and severe SDB (93.2\% for both).

CONCLUSIONS: In community populations such as the SHHS, high specificities may be more useful in excluding low-risk patients, while avoiding false positives. However, sleep clinicians may prefer to use screening tools with high sensitivities, like the STOP-Bang, in order to avoid missing cases that may lead to adverse health consequences and increased healthcare costs.

}, keywords = {Blood Pressure, Body Mass Index, Cohort Studies, Female, Humans, Male, Mass Screening, Middle Aged, Polysomnography, Predictive Value of Tests, Prospective Studies, Risk, ROC Curve, Sensitivity and Specificity, Severity of Illness Index, Sleep Apnea Syndromes, Snoring, Surveys and Questionnaires}, issn = {1550-9397}, doi = {10.5664/JCSM.1308}, author = {Silva, Graciela E and Vana, Kimberly D and Goodwin, James L and Sherrill, Duane L and Quan, Stuart F} } @article {1566, title = {The Impact of Sleep-Disordered Breathing on Body Mass Index (BMI): The Sleep Heart Health Study (SHHS).}, journal = {Southwest J Pulm Crit Care}, volume = {3}, year = {2011}, month = {2011 Dec 08}, pages = {159-168}, abstract = {

INTRODUCTION: It is well known that obesity is a risk factor for sleep-disordered breathing (SDB). However, whether SDB predicts increase in BMI is not well defined. Data from the Sleep Heart Health Study (SHHS) were analyzed to determine whether SDB predicts longitudinal increase in BMI, adjusted for confounding factors. METHODS: A full-montage unattended home polysomnogram (PSG) and body anthropometric measurements were obtained approximately five years apart in 3001 participants. Apnea-hypopnea index (AHI) was categorized using clinical thresholds: < 5 (normal), >= 5 to <15 (mild sleep apnea), and >= 15 (moderate to severe sleep apnea). Linear regression was used to examine the association between the three AHI groups and increased BMI. The model included age, gender, race, baseline BMI, and change in AHI as covariates. RESULTS: Mean (SD) age was 62.2 years (10.14), 55.2\% were female and 76.1\% were Caucasian. Five-year increase in BMI was modest with a mean (SD) change of 0.53 (2.62) kg/m(2) (p=0.071). A multivariate regression model showed that subjects with a baseline AHI between 5-15 had a mean increase in BMI of 0.22 kg/m(2) (p=0.055) and those with baseline AHI >= 15 had a BMI increase of 0.51 kg/m(2) (p<0.001) compared to those with baseline AHI of <5. CONCLUSION: Our findings suggest that there is a positive association between severity of SDB and subsequent increased BMI over approximately 5 years. This observation may help explain why persons with SDB have difficulty losing weight.

}, issn = {2160-6773}, author = {Brown, Mark A and Goodwin, James L and Silva, Graciela E and Behari, Ajay and Newman, Anne B and Punjabi, Naresh M and Resnick, Helaine E and Robbins, John A and Quan, Stuart F} }