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Although insomnia is reliably associated with anxiety symptoms, aspects of insomnia may differentially relate to one anxiety symptom versus another. Therefore, treatment for insomnia comorbidity with anxiety might be individually tailored to optimize treatment response. Working from this hypothesis, we analyzed data from a survey of 1007 community-dwelling adults. Insomnia was measured using the Insomnia Severity Index (ISI), categorizing items as nighttime disturbances, daytime dysfunction, or self-perceived dissatisfaction. Anxiety symptoms were measured with the Generalized Anxiety Disorder 7-item questionnaire (GAD-7). Linear and binomial logistic regression were used and adjusted for covariates. Post hoc forward stepwise analyses determined which components of the insomnia contributed to individual anxiety symptoms. Significant associations between nighttime disturbance (β = 0.88 [0.44, 1.3]), daytime dysfunction (β = 1.30 [0.81, 1.80]), dissatisfaction (β = 1.20 [0.60, 1.7]) and total GAD-7 score were maintained after adjusting for covariates. Nighttime disturbance was associated with excess worrying, restlessness, irritability, and fear of catastrophe. Daytime dysfunction was associated with all symptoms except for fear of catastrophe, and self-perceived dissatisfaction was associated with all symptoms except irritability. Stepwise analyses revealed that daytime dysfunction and dissatisfaction were most consistently related to anxiety symptoms. Greater attention should be paid to daytime dysfunction in patients with insomnia and anxiety, as improving daytime functioning may improve anxiety. [ABSTRACT FROM AUTHOR]

Introduction: Although psychosocial problems are commonly associated with both alcohol misuse and insomnia, very little is known about the combined effects of insomnia and current alcohol dependence on the severity of psychosocial problems. The present study evaluates whether the co-occurrence of insomnia and alcohol dependence is associated with greater psychosocial problem severity., Methods: Alcohol dependent individuals (N = 123) were evaluated prior to participation in a placebo-controlled medication trial. The Short Index of Problems (SIP), Addiction Severity Index (ASI), Insomnia Severity Index (ISI), and Time Line Follow Back (TLFB), were used to assess psychosocial, employment, and legal problems; insomnia symptoms; and alcohol consumption, respectively. Bivariate and multivariate analyses were used to evaluate the relations between insomnia and psychosocial problems., Results: Subjects' mean age was 44 years (SD = 10.3), 83% were male, and their SIP sub-scale scores approximated the median for normative data. A quarter of subjects reported no insomnia; 29% reported mild insomnia; and 45% reported moderate-severe insomnia. The insomnia groups did not differ on alcohol consumption measures. The ISI total score was associated with the SIP total scale score (β = 0.23, p = 0.008). Subjects with moderate-severe insomnia had significantly higher scores on the SIP total score, and on the social and impulse control sub-scales, and more ASI employment problems and conflicts with their spouses than others on the ASI., Conclusion: In treatment-seeking alcohol dependent subjects, insomnia may increase alcohol-related adverse psychosocial consequences. Longitudinal studies are needed to clarify the relations between insomnia and psychosocial problems in these subjects., (Published by Elsevier Ltd.)

Background: Little is known about the social determinants of sleep attainment. This study examines the relationship of race/ethnicity, socio-economic status (SES) and other factors upon sleep quality., Methods: A cross-sectional survey of 9,714 randomly selected subjects was used to explore sleep quality obtained by self-report, in relation to socioeconomic factors including poverty, employment status, and education level. The primary outcome was poor sleep quality. Data were collected by the Philadelphia Health Management Corporation., Results: Significant differences were observed in the outcome for race/ethnicity (African-American and Latino versus White: unadjusted OR = 1.59, 95% CI 1.24-2.05 and OR = 1.65, 95% CI 1.37-1.98, respectively) and income (below poverty threshold, unadjusted OR = 2.84, 95%CI 2.41-3.35). In multivariable modeling, health indicators significantly influenced sleep quality most prominently in poor individuals. After adjusting for socioeconomic factors (education, employment) and health indicators, the association of income and poor sleep quality diminished, but still persisted in poor Whites while it was no longer significant in poor African-Americans (adjusted OR = 1.95, 95% CI 1.47-2.58 versus OR = 1.16, 95% CI 0.87-1.54, respectively). Post-college education (adjusted OR = 0.47, 95% CI 0.31-0.71) protected against poor sleep., Conclusions: A "sleep disparity" exists in the study population: poor sleep quality is strongly associated with poverty and race. Factors such as employment, education and health status, amongst others, significantly mediated this effect only in poor subjects, suggesting a differential vulnerability to these factors in poor relative to non-poor individuals in the context of sleep quality. Consideration of this could help optimize targeted interventions in certain groups and subsequently reduce the adverse societal effects of poor sleep.