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Nighttime insomnia symptoms and perceived health in the America Insomnia Survey (AIS)
James K Walsh1, Catherine Coulouvrat, Goeran Hajak
1Sleep Medicine and Research Center, St. Luke’s Hospital, St. Louis, MO, USA.
Study Objectives:
To explore the distribution of the 4 cardinal nighttime symptoms of insomnia-difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), early morning awakening (EMA), and nonrestorative sleep (NRS)-in a national sample of health plan members and the associations of these nighttime symptoms with sociodemographics, comorbidity, and perceived health.
Design/Setting/Participants:
Cross-sectional telephone survey of 6,791 adult respondents.
Intervention:
None.
Measurements/Results:
Current insomnia was assessed using the Brief Insomnia Questionnaire (BIQ)-a fully structured validated scale generating diagnoses of insomnia using DSM-IV-TR, ICD-10, and RDC/ICSD-2 inclusion criteria. DMS (61.0%) and EMA (52.2%) were more prevalent than DIS (37.7%) and NRS (25.2%) among respondents with insomnia. Sociodemographic correlates varied significantly across the 4 symptoms. All 4 nighttime symptoms were significantly related to a wide range of comorbid physical and mental conditions. All 4 also significantly predicted decrements in perceived health both in the total sample and among respondents with insomnia after adjusting for comorbid physical and mental conditions. Joint associations of the 4 symptoms predicting perceived health were additive and related to daytime distress/impairment. Individual-level associations were strongest for NRS. At the societal level, though, where both prevalence and strength of individual-level associations were taken into consideration, DMS had the strongest associations.
Conclusions:
The extent to which nighttime insomnia symptoms are stable over time requires future long-term longitudinal study. Within the context of this limitation, the results suggest that core nighttime symptoms are associated with different patterns of risk and perceived health and that symptom-based subtyping might have value.
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