Sleep-disordered breathing is a common disorder with a range of harmful sequelae. Obesity is a strong causal factor for sleep-disordered breathing, and because of the ongoing obesity epidemic, ...previous estimates of sleep-disordered breathing prevalence require updating. We estimated the prevalence of sleep-disordered breathing in the United States for the periods of 1988-1994 and 2007-2010 using data from the Wisconsin Sleep Cohort Study, an ongoing community-based study that was established in 1988 with participants randomly selected from an employed population of Wisconsin adults. A total of 1,520 participants who were 30-70 years of age had baseline polysomnography studies to assess the presence of sleep-disordered breathing. Participants were invited for repeat studies at 4-year intervals. The prevalence of sleep-disordered breathing was modeled as a function of age, sex, and body mass index, and estimates were extrapolated to US body mass index distributions estimated using data from the National Health and Nutrition Examination Survey. The current prevalence estimates of moderate to severe sleep-disordered breathing (apnea-hypopnea index, measured as events/hour, ≥15) are 10% (95% confidence interval (CI): 7, 12) among 30-49-year-old men; 17% (95% CI: 15, 21) among 50-70-year-old men; 3% (95% CI: 2, 4) among 30-49-year-old women; and 9% (95% CI: 7, 11) among 50-70 year-old women. These estimated prevalence rates represent substantial increases over the last 2 decades (relative increases of between 14% and 55% depending on the subgroup).
Excess weight and sleep-disordered breathing Young, Terry; Peppard, Paul E; Taheri, Shahrad
Journal of applied physiology (1985),
10/2005, Letnik:
99, Številka:
4
Journal Article
Recenzirano
1 Department of Population Health Sciences, University of Wisconsin-Madison, Madison Wisconsin; and 2 Henry Wellcome Laboratories for Integrated Neuroscience and Endocrinology (LINE), University of ...Bristol, Bristol, United Kingdom
Excess weight is a well-established predictor of sleep-disordered breathing (SDB). Clinical observations and population studies throughout the United States, Europe, Asia, and Australia have consistently shown a graded increase in the prevalence of SDB as body mass index, neck girth, or other measures of body habitus increases. Clinical studies of weight loss and longitudinal population studies provide strong support for a causal association. The role of excess body weight, a modifiable risk factor, with SDB raises many questions relevant to clinical practice and public health. The topic takes on added importance with the alarming rate of weight gain in children as well as adults in industrialized nations. Among adults ages 3069 yr, averaging over the estimated United States 2003 age, sex, and BMI distributions, we estimate that 17% of adults have mild or worse SDB (apnea-hypopnea index 5) and that 41% of those adults have SDB "attributable" to having a body mass index of 25 kg/m 2 . Similarly, we estimate that 5.7% of adults have moderate or worse SDB (apnea-hypopnea index 15) and that 58% of those adults have SDB attributable to excess weight. Clearly, if the expanding epidemic of obesity seen in the United States continues, the prevalence of SDB will almost certainly increase, along with the proportion of SDB attributable to obesity.
apnea-hypopnea index; body mass index
Address for reprint requests and other correspondence: T. Young, 1070 MSC, 1300 Univ. Ave., Madison, WI 53706 (e-mail: tbyoung{at}wisc.edu )
Screening studies in the United States, Europe, and Australia have shown that a substantial proportion of the adult population has mild-to-moderate sleep-disordered breathing, a condition ...characterized by repeated episodes of apnea and hypopnea during sleep.
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Apnea and hypopnea cause temporary elevations in blood pressure in association with blood oxygen desaturation, arousal, and sympathetic activation and may cause elevated blood pressure during the daytime and, ultimately, sustained hypertension.
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Recent reviews judged the epidemiologic evidence relating sleep-disordered breathing to hypertension to be inconclusive, but they noted that study designs were inappropriate, that there was inadequate control for confounding factors such as . . .
Obstructive sleep apnea (OSA) is associated with hypertension.
We aimed to quantify the independent association of OSA during REM sleep with prevalent and incident hypertension.
We included adults ...enrolled in the longitudinal community-based Wisconsin Sleep Cohort Study with at least 30 minutes of REM sleep obtained from overnight in-laboratory polysomnography. Studies were repeated at 4-year intervals to quantify OSA. Repeated measures logistic regression models were fitted to explore the association between REM sleep OSA and prevalent hypertension in the entire cohort (n = 4,385 sleep studies on 1,451 individuals) and additionally in a subset with ambulatory blood pressure data (n = 1,085 sleep studies on 742 individuals). Conditional logistic regression models were fitted to longitudinally explore the association between REM OSA and development of hypertension. All models controlled for OSA events during non-REM sleep, either by statistical adjustment or by stratification.
Fully adjusted models demonstrated significant dose-relationships between REM apnea-hypopnea index (AHI) and prevalent hypertension. The higher relative odds of prevalent hypertension were most evident with REM AHI greater than or equal to 15. In individuals with non-REM AHI less than or equal to 5, a twofold increase in REM AHI was associated with 24% higher odds of hypertension (odds ratio, 1.24; 95% confidence interval, 1.08-1.41). Longitudinal analysis revealed a significant association between REM AHI categories and the development of hypertension (P trend = 0.017). Non-REM AHI was not a significant predictor of hypertension in any of the models.
Our findings indicate that REM OSA is cross-sectionally and longitudinally associated with hypertension. This is clinically relevant because treatment of OSA is often limited to the first half of the sleep period leaving most of REM sleep untreated.
Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used ...neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph-a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.
Sleep spindles are discrete, intermittent patterns of brain activity observed in human electroencephalographic data. Increasingly, these oscillations are of biological and clinical interest because ...of their role in development, learning and neurological disorders. We used an Internet interface to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects.
...the "big three" risk factors for OSA are male sex, higher body mass, and greater age (8). ...these same outcomes may also result from long-term "accretive" processes, due to years of exposure to ...OSA, via a host of mechanisms that promote vascular or neural injury (22). ...far, epidemiologic investigations have made little effort to disentangle acute versus longterm cumulative effects, as traditional longitudinal studies have minimal ability to measure acute effects, and cross-sectional studies cannot distinguish acute from long-term effects. ...with respect to point 1, larger, longer-running epidemiology studies of OSA are technically and ethically feasible. EHR rarely have high-quality data on important covariates, such as physical activity, diet, education, etc., and suffer from the lack of standardization for basic, but critical, measures, such as height and weight. ...although the use of EHR to address questions regarding associations between OSA and outcomes is attractive, without sufficient care, large EHR-based investigations may simply result in estimated associations characterized by tight confidence intervals around dubious point estimates.
Lead (Pb) is a ubiquitous environmental contaminant with an array of detrimental health effects in children and adults, including neurological and immune dysfunction. Emerging evidence suggests that ...Pb exposure may alter the composition of the gut microbiota, however few studies have examined this association in human populations. The purpose of this study was to examine the association between urinary Pb concentration and the composition of the adult gut microbiota in a population-based sample of adults.
Data used in this study were collected as part of the Survey of the Health of Wisconsin (SHOW) and its ancillary microbiome study. The SHOW is a household-based health examination survey of Wisconsin residents, collecting a variety of survey data on health determinants and outcomes, as well as objective measurements of body habitus, and biological specimens including urine. The ancillary microbiome study added additional questions and biological specimen collection, including stool, from participants age 18+. Pb concentration was analyzed in urine samples, and gut microbiota composition was assessed using DNA sequencing of the 16S rRNA V4 region, extracted from stool samples. Data processing and statistical analyses were performed in mothur, Python, R, and SAS.
Of 696 participants, urinary Pb concentration was highest in those age 70+, females, those with a high school diploma or lower, current and former smokers, and those without indoor pets. In adjusted models, increasing urinary Pb levels were associated with increases in microbial α-diversity (p = 0.071) and richness (p = 0.005). Differences in microbial β-diversity were significantly associated (p = 0.003) with differences in urinary Pb level. Presence of Proteobacteria, including members of the Burkholderiales, was significantly associated with increased urinary Pb.
These results suggest that Pb exposure is associated with differences in the composition of the adult gut microbiota in a population-based human sample. Further investigation of this association is warranted.
•Urinary Pb level was associated with altered adult gut microbial composition.•Increasing urinary Pb was associated with gut microbial α-diversity and richness.•Community composition (β-diversity) differed with increased urinary Pb level.•Presence of Proteobacteria in the gut increased with urinary Pb level.
CONTEXT Excess body weight is positively associated with sleep-disordered breathing
(SDB), a prevalent condition in the US general population. No large study
has been conducted of the longitudinal ...association between SDB and change
in weight. OBJECTIVE To measure the independent longitudinal association between weight change
and change in SDB severity. DESIGN Population-based, prospective cohort study conducted from July 1989
to January 2000. SETTING AND PARTICIPANTS Six hundred ninety randomly selected employed Wisconsin residents (mean
age at baseline, 46 years; 56% male) who were evaluated twice at 4-year intervals
for SDB. MAIN OUTCOME MEASURES Percentage change in the apnea-hypopnea index (AHI; apnea events + hypopnea
events per hour of sleep) and odds of developing moderate-to-severe SDB (defined
by an AHI ≥15 events per hour of sleep), with respect to change in weight. RESULTS Relative to stable weight, a 10% weight gain predicted an approximate
32% (95% confidence interval CI, 20%-45%) increase in the AHI. A 10% weight
loss predicted a 26% (95% CI, 18%-34%) decrease in the AHI. A 10% increase
in weight predicted a 6-fold (95% CI, 2.2-17.0) increase in the odds of developing
moderate-to-severe SDB. CONCLUSIONS Our data indicate that clinical and public health programs that result
in even modest weight control are likely to be effective in managing SDB and
reducing new occurrence of SDB.
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