Sleep quality and associated factors among XXXX with @entity712 in Iran.

@entity1 @entity712 @entity25 @entity299
BACKGROUND: @entity25 are common among @entity1 with @entity712 ( @entity712 ), and it can have a significant effect on @entity1 ' daily activities as well as their health. The purpose of this study was to assess @entity25 and its predictors in Iranian @entity1 with chronic @entity712 . METHODS: This cross-sectional study was conducted on a sample of 200 @entity1 with @entity712 in two hospitals of Tehran University of Medical Sciences from June to November 2009. These @entity1 completed a demographic questionnaire, and their @entity25 was measured using the Pittsburgh Sleep Quality Index (PSQI). One-way analysis of variance (ANOVA), Kruskal-Wallis test, t-test and Linear regression were used for data analysis. RESULTS: Seventy-nine percent of @entity1 (n = 158) reported poor @entity25 (PSQI > 5). The range of global PSQI scores was 3-20. Also, a significant relationship was found between PSQI scores and @entity1 ' age (p<0.004), gender (p< 0.042), educational level (p< 0.001), occupational status (p< 0.038), number of hospitalizations (p< 0.005), type of referral (p< 0.001), @entity299 (p< 0.001), diuretic use (p< 0.021) and left ventricular ejection fraction (p< 0.015). Three predictors were identified using regression analyses with stepwise methods, and included age, type of referral and educational level. CONCLUSION: The high prevalence of poor @entity25 highlighted the importance of @entity25 in @entity712 @entity1 . There are many factors associated with @entity25 and @entity25 that health providers should recognize for improved and effective management.
