RESEARCH IN BRIEF
Predictors of poor sleep quality and excessive daytime sleepiness in Turkish adults with type 2 diabetes € Belg€ uzar Kara and Ozge Kılıcß Accepted for publication: 10 September 2014
Aim To determine the prevalence of poor sleep quality and excessive daytime sleepiness in Turkish patients with type 2 diabetes and identify the effects of demographic/diseaserelated characteristics and physical activity on poor sleep quality and excessive daytime sleepiness.
Background Recent studies have demonstrated that sleep quantity and quality are associated with metabolic changes that may lead to cardiovascular diseases, insulin resistance, impaired glucose tolerance and type 2 diabetes. These results suggest that sleep problems in patients with type 2 diabetes may have serious consequences. However, studies on sleep quality and daytime sleepiness risk factors in this population are limited and have reported inconsistent results (Chasens et al. 2013, Song et al. 2013). The effects of income level, the caregiver’s presence and physical activity are also not clear.
Design and sample We conducted a cross-sectional study between November 2013 and February 2014. A total of 250 patients with type 2 diabetes followed by a diabetes outpatient clinic in a large Turkish city were enrolled. Inclusion criteria were age ≥18 years, type 2 diabetes diagnosis for at least one month, ability to communicate in Turkish and agreeing to particiAuthors: Belg€ uzar Kara, RN, Associate Professor, Instructor, Department of Internal Medicine Nursing, School of Nursing, € Gulhane Military Medical Academy, Ankara; Ozge Kılıcß, RN, Nurse, Department of Endocrinology and Metabolism Diseases, Gulhane Military Medical Academy, Ankara, Turkey
© 2014 John Wiley & Sons Ltd Journal of Clinical Nursing, doi: 10.1111/jocn.12710
What does this paper contribute to the wider global clinical community?
• The results of this study suggest that poor sleep qual•
ity and excessive daytime sleepiness are prevalent among patients with type 2 diabetes. Having no caregiver, poor self-rated health and a moderate or inadequate family income are associated with poor sleep quality and this in return is associated with excessive daytime sleepiness. This paper highlights the importance of implementing effective interventions by taking into account the factors contributing to poor sleep quality and excessive daytime sleepiness in patients with type 2 diabetes.
pate in the study. Exclusion criteria were a severe comorbid condition, major psychiatric disorder, cognitive impairment, sleep disorders, alcoholism, pregnancy, lactation, clinical instability and working in the night shift. One hundredeighty patients (594% female) met the inclusion criteria. This study was approved by the Hospital’s Local Ethics Committee. Written informed consent was obtained from all participants.
Methods A self-administered questionnaire was used to collect data on participants’ characteristics. A five-point Likert scale (self-rated health; SRH) ranging from ‘very poor’ to ‘very good’ was used for measuring perceived health status. The Correspondence: Belg€ uzar Kara, Associate Professor, Instructor, G€ ulhane Askeri Tıp Akademisi, Hemsßirelik Y€ uksekokulu, 06013 Ankara, Turkey. Telephone: +90 312 3041565. E-mail: [email protected]
This manuscript was presented as a poster presentation at the 50th National Diabetes Congress, Antalya, Turkey, April 23–27, 2014.
Research in Brief
SRH was classified into ‘poor’ (fair/poor/very poor) and ‘good’ health (good/very good). The sleep quality was assessed using the Turkish version of the Pittsburgh Sleep Quality Index (PSQI). The PSQI consists of 24 items. It is a four-point Likert scale ranging from 0 (not at all) to 3 (three or more times a week). The PSQI generates a global score (≥5 poor sleep quality; range = 0–21) and seven component scores (Agarg€ un et al. 1996). The Turkish version of the Epworth Sleepiness Scale (ESS) was used to measure excessive daytime sleepiness. It is an eight-item, four-point Likert scale (0 = never, 3 = always). The ESS yields a total score (≥10 excessive daytime sleepiness; range = 0–24) (Agarg€ un et al. 1999). The Cronbach’s alpha coefficients of the global PSQI and the ESS were high in the current study (075 and 088; respectively). The Turkish short version of the International Physical Activity Questionnaire (IPAQ-S) was used to measure physical activity. The metabolic equivalent of task (MET)minutes per week was calculated (duration 9 frequency 9 MET intensity). The intensity of physical activity was classified as low (3000 MET-min/ week) (Saglam et al. 2010). All statistical analyses were performed using the SPSS for Windows statistical software (version 15.0; SPSS Inc., Chicago, IL, USA). Descriptive statistics and reliability analyses were conducted. Univariate and multivariate logistic regression analyses with backward elimination were performed to determine independent risk factors associated with outcome variables. Variables with p values