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1.
J Clin Sleep Med ; 14(7): 1161-1168, 2018 07 15.
Article in English | MEDLINE | ID: mdl-29991418

ABSTRACT

STUDY OBJECTIVES: Few studies have objectively evaluated sleep characteristics during pregnancy or investigated the relationship between altered spectral electroencephalogram (EEG) bands and sleep-disordered breathing (SDB). The study aimed to describe changes in sleep as measured by polysomnography (PSG) and spectral EEG bands during pregnancy and to examine the relationship between delta power in non-rapid eye movement (NREM) sleep and SDB. METHODS: This is a secondary analysis of a prospective study. One hundred twenty-three women underwent full PSG in early pregnancy, and 97 repeated PSG in late pregnancy. Spectral analysis of the EEG in NREM sleep was performed. We used linear and logistic mixed-model regression to analyze the sleep measures and linear regression to explore the association between delta power and apnea-hypopnea index (AHI) changes during pregnancy. RESULTS: In late pregnancy, women had shorter sleep duration, poorer sleep efficiency, more awakenings, more stage N2 sleep, less slow wave sleep, less REM sleep, higher AHI, and higher periodic limb movement index compared to early pregnancy. The percentage of stage N1 sleep, sleep latency, REM sleep latency, and arousal index frequency did not change. Regarding EEG-spectra, delta and theta powers decreased, but beta-2 power increased during pregnancy. In multivariable analyses, greater reduction of delta power was associated with larger increases in AHI (ß [95% confidence interval] = -0.038 [-0.073, -0.002], P = .040). Estimates suggest that each one-unit increase in AHI reduces delta power by 4% in late pregnancy. CONCLUSIONS: PSG-measured sleep characteristics change during pregnancy. Delta power decreases when the severity of SDB increases during pregnancy. COMMENTARY: A commentary on this article appears in this issue on page 1095.


Subject(s)
Electroencephalography/statistics & numerical data , Polysomnography/statistics & numerical data , Pregnancy Complications/physiopathology , Sleep Apnea Syndromes/physiopathology , Sleep Stages/physiology , Adult , Female , Humans , Longitudinal Studies , Pennsylvania , Pregnancy , Pregnancy Complications/diagnosis , Pregnancy Trimester, First , Pregnancy Trimester, Third , Prospective Studies , Sleep Apnea Syndromes/diagnosis
2.
Behav Sleep Med ; 14(6): 687-98, 2016.
Article in English | MEDLINE | ID: mdl-27159249

ABSTRACT

Although it is widely acknowledged that there are not enough clinicians trained in either Behavioral Sleep Medicine (BSM) in general or in Cognitive Behavioral Therapy for Insomnia (CBT-I) in specific, what is unclear is whether this problem is more acute in some regions relative to others. Accordingly, a geographic approach was taken to assess this issue. Using national directories as well as e-mail listservs (Behavioral Sleep Medicine group and Behavioral Treatment for Insomnia Roster), the present study evaluated geographic patterning of CBSM and BSM providers by city, state, and country. Overall, 88% of 752 BSM providers worldwide live in the United States (n = 659). Of these, 58% reside in 12 states with ≥ 20 providers (CA, NY, PA, IL, MA, TX, FL, OH, MI, MN, WA, and CO), and 19% reside in just 2 states (NY and CA). There were 4 states with no BSM providers (NH, HI, SD, and WY). Of the 167 U.S. cities with a population of > 150,000, 105 cities have no BSM providers. These results clearly suggest that a targeted effort is needed to train individuals in both the unserved and underserved areas.


Subject(s)
Behavioral Medicine , Cognitive Behavioral Therapy , Geographic Mapping , Medically Underserved Area , Sleep Initiation and Maintenance Disorders/therapy , Sleep Medicine Specialty/organization & administration , Behavioral Medicine/organization & administration , Behavioral Medicine/statistics & numerical data , Cities/statistics & numerical data , Cognitive Behavioral Therapy/statistics & numerical data , Humans , Sleep Initiation and Maintenance Disorders/psychology , Sleep Medicine Specialty/statistics & numerical data , United States/epidemiology , Workforce
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