Factors Associated With Sleep Quality in HIV

Factors Associated With Sleep Quality in HIV

Feature Factors Associated With Sleep Quality in HIV Jiaojiao Ren, MPH Miaomiao Zhao, MPH Baohua Liu, MPH Qunhong Wu, MD* Yanhua Hao, MD Mingli Jiao,...

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Factors Associated With Sleep Quality in HIV Jiaojiao Ren, MPH Miaomiao Zhao, MPH Baohua Liu, MPH Qunhong Wu, MD* Yanhua Hao, MD Mingli Jiao, MD Lemeng Qu, MPH Ding Ding, MD Ning Ning, MD Zheng Kang, MD Libo Liang, MD Huan Liu, MPH Tong Zheng, MPH

Jiaojiao Ren, MPH, is a graduate student, Harbin Medical University, Department of Social Medicine, School of Public Health, Harbin, Heilongjiang, China. Miaomiao Zhao, MPH, is a graduate student, Harbin Medical University, Department of Social Medicine, School of Public Health, Harbin, Heilongjiang, China. Baohua Liu, MPH, is a graduate student, Harbin Medical University, Department of Social Medicine, School of Public Health, Harbin, Heilongjiang, China. Qunhong Wu, MD, is the Director, Office of Department of Social Medicine, School of Public Health, and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. (*Correspondence to: [email protected]). Yanhua Hao, MD, is a Professor, Office of Department of Social Medicine, School of Public Health, and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. Mingli Jiao, MD, is a Professor, Office of Department of Social Medicine, School of Public Health and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. Lemeng Qu, MPH, is a staff member, Office of School of Public Health, Jinzhou Medical

University, Jinzhou, Liaoning, China. Ding Ding, MD, is an Associate Professor, School of Public Health, Dalian Medical University, Dalian, China. Ning Ning, MD, is an Associate Professor, Office of Department of Social Medicine, School of Public Health, and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. Zheng Kang, MD, is an Associate Professor, Office of Department of Social Medicine, School of Public Health, and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. Libo Liang, MD, is an Associate Professor, Office of Department of Social Medicine, School of Public Health, and Collaborative Innovation Centre of Social Risks Governance in Health, Sub-center of Harbin Medical University, Harbin, Heilongjiang, China. Huan Liu, MPH, is a graduate student at Harbin Medical University, Department of Social Medicine, School of Public Health, Harbin, Heilongjiang, China. Tong Zheng, MPH, is a graduate student, Harbin Medical University, Department of Social Medicine, School of Public Health, Harbin, Heilongjiang, China.

JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. -, No. -, -/- 2018, 1-8 https://doi.org/10.1016/j.jana.2018.04.006 Copyright Ó 2018 Association of Nurses in AIDS Care

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The purpose of our research was to (a) identify sleep quality complications experienced by patients living with HIV infection and treated with antiretroviral therapy (ART), and (b) explore factors associated with sleep quality complications. From March to August in 2013, a cross-sectional study was conducted at HIV-designated hospitals in Harbin of Heilongjiang Province, China. Participants completed a questionnaire using the Spiegel scale to assess sleep quality; 32.1% of patients were negatively affected by sleep disturbances. Nighttime dreams and waking up were the most serious complications. We found that anxiety was the most prominent factor contributing to poor sleep quality, followed by ART medication types and family and social support. Patients with HIV infection and receiving ART experienced many different types of sleep complications. More attention should be given to the development of treatment guidelines for proper management of sleep disturbances experienced by patients with HIV. (Journal of the Association of Nurses in AIDS Care, -, 1-8) Copyright Ó 2018 Association of Nurses in AIDS Care Key words: AIDS, antiretroviral therapy, HIV, sleep quality

H

IV is an infection characterized by a reduction in the number of CD41 T cells, which results in immune dysfunction and a variety of opportunistic infections and tumors. Since the first HIV case was reported in the United States in 1981, the disease has spread rapidly on a global scale. In 2015, approximately 36.7 million people were infected with HIV, and 1.1 million people have died (Joint United Nations Programme on HIV/AIDS, 2016). Since the first patient with HIV appeared in China in 1985, the number of HIV infections in China has increased year by year. In 2003, China developed a policy to provide free antiretroviral therapy (ART) for patients with HIV infection. ART is the administration of a combination of three or more antiretroviral drugs. ART regimens can be used as first-line and second-line treatments, and are known to help protect the immune function of people living with HIV (PLWH). However, maintaining immune function for patients has some limitations. One of these limitations is adverse drug reactions, including

gastrointestinal symptoms, rash, abdominal pain, bone marrow suppression, and sleep disturbances (Han, 2014). Sleep disturbances, a common complaint among PLWH, can interfere with normal physical, mental, and emotional function (White et al., 1995). Studies have shown that 30% to 100% of adults with HIV have experienced sleep disturbances (Nokes & Kendrew, 2001; Rubinstein & Selwyn, 1998). In one study, data collected from a cohort of 317 PLWH indicated that 56% experienced sleep disturbances (Lee et al., 2009). Insomnia is one of the sleep disturbances associated with the initiation of efavirenz (EFV). It is estimated that 73% of adult PLWH report various degrees of insomnia symptoms, defined as difficulty falling asleep and staying asleep, awakening too early, or unrefreshing sleep, in combination with at least one daytime symptom such as sleepiness or irritability (Duchna, 2006; Rubinstein & Selwyn, 1998). According to Spiegel (1984), sleep latency, sleep duration, night waking occurrences, sleep depth, nighttime dreams, and a feeling of waking up have been used to evaluate insomnia and determine sleep quality. The pathophysiology of insomnia among PLWH is unclear, but may be related to psychological factors, the impact of antiretroviral medications, central nervous system opportunistic infections, or substance abuse (Osvick et al., 2004). The mental status of PLWH is often problematic due to depression, anxiety, or other emotional disorders, which are triggered by serious physical symptoms, side effects of medications, financial burdens, stigma, and discrimination (Bhatia & Munjal, 2014). Mental disorders exacerbate insomnia, which may consequently exacerbate HIV symptoms, thus leading to a vicious and detrimental cycle (Crum-Cianflone et al., 2012). With the increased life expectancy of PLWH, sleep disturbances may adversely affect quality of life and work performance. Despite the potentially devastating effects of sleep disturbances among PLWH, little research has been done to highlight the factors associated with sleep disturbances in this population during the ART era. Therefore, we aimed to explore sleep quality and its associated factors in PLWH who are taking ART in order to find optimal management strategies for PLWH who experience sleep disturbances.

Ren et al. / Factors Associated With Sleep Quality in HIV

Methods Study Design and Participants Before conducting the study, we applied for an ethics review from Harbin Medical University. A formal letter of approval was granted and was submitted to the Research Ethics Committees of the HIV-designated hospitals at which we intended to conduct the research. Support letters were obtained from the HIV-designated hospitals. During our research, we emphasized that participation was voluntary. All participants were asked to sign a consent form after they were introduced to the purpose of the study and the procedures were explained. Privacy was strictly protected by conducting interviews in private places, and all personal identifiers were removed from the questionnaires to ensure confidentiality. From March to August in 2013, a cross-sectional study was conducted at the HIV- designated hospitals in Harbin of Heilongjiang Province. Heilongjiang Province is located in northeast China, with a population of more than 38 million. In 2016, the gross domestic product per capita in Heilongjiang reached $6,373.50 USD, ranking in the lower range of all provinces (National Bureau of Statistics of the People’s Republic of China, 2017). The survey was carried out by researchers from the Department of Social Medicine of Harbin Medical University in Heilongjinag Province. Patients who were at least 18 years of age, diagnosed with an HIV infection, and receiving ART were enrolled. Patients who were using illicit drugs (as determined by selfreport or by positive urine drug testing); worked at night (at least 4 hours between 12 a.m. and 6 a.m.); reported having bipolar disorder, schizophrenia, or dementia; or had been pregnant within the prior 3 months were excluded. The questionnaire was developed to collect demographic, psychosocial, and clinical data. It included participant age, gender, education level, marriage status, income, HIV transmission route, discrimination, hostile psychology, depression, anxiety, family and social support, medication adherence, ART type, CD41 T cell count, duration of disease, and the duration of ART. In addition, each participant was administered the Spiegel scale, the Burns Depression Checklist

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(BDC), and the Self-Rating Anxiety Scale. The Spiegel scale consists of six items that assessed sleep quality in the previous month, including sleep latency, sleep duration, night waking occurrences, sleep depth, nighttime dreams, and a feeling of waking up. Each item was scored from 0 to 5, with the final score ranging between 0 and 30. The higher the score, the worse the quality of sleep, and scores equal to or greater than 18 indicated poor sleep quality. The BDC was used to assess depression. It is a 15question survey that assessed each item on a scale of 0 to 4. Higher total scores indicated more severe depression symptoms (Chen et al., 2013). In our study, a BDC score greater than 11 was used to identify depression. Anxiety was assessed by a SelfRating Anxiety Scale designed by Zung (1971). It included 20 items to measure anxiety levels. Each question was scored on a Likert-type scale of 1-4. The total raw scores ranged from 20-80. An Anxiety Index score, converted from raw scores, determined the patient’s anxiety level. A score greater than 45 indicated anxiety. In total, 237 valid questionnaires were collected, and the response rate on the questionnaires was 100%. Statistical Analysis We used descriptive statistics to summarize demographic characteristics and presented the scores of the Spiegel scale data as mean 6 standard deviation. Univariate analysis was performed using chisquared or t-tests, and the multivariate logistic regression was used to examine associations between sleep quality and its associated factors after controlling for confounding factors. The outcome variable was treated as a nominal measure: poor sleep quality versus good sleep quality. The level of statistical significance was set at p , .05. All analyses were performed using SPSS version 22 software for Windows (IBM Corporation, Armonk, NY).

Results Characteristics of Study Participants Most participants were male (95.8%) and ages 18 to 45 years (75.5%). The majority of participants

4 JANAC Vol. -, No. -, -/- 2018 Table 1.

Association Between Sleep Quality and Characteristics of Study Participants

Variables Gender Male Female Age #45 years old .45 years old Education level Junior college and less Undergraduate and more Marriage status Married Divorced/widowed/ unmarried Income # $472.90 USD . $472.90 USD Transmission route Sex contact Blood/drug use/ other CD41 T cell count #350 cells/mm3 .350 cells/mm3 Duration of infection #5 years .5 years Duration of ART #3 months .3 months Depression Yes No Anxiety Yes No Discrimination Yes No Family and social support Yes No Hostile psychology Yes No Medication adherence Yes

Table 1.

Poor-Quality Good-Quality Sleep Sleep n 5 76 (%) n 5 161 (%) p Value .403 74 (32.6) 2 (20.0)

153 (67.4) 8 (80.0)

55 (30.7) 21 (36.2)

124 (69.3) 37 (63.8)

63 (38.4)

101 (61.6)

13 (17.8)

60 (82.2)

27 (38.6) 49 (29.3)

43 (61.4) 118 (70.7)

67 (36.4) 9 (17.0)

117 (63.6) 44 (83.0)

60 (31.1) 16 (36.4)

133 (68.9) 28 (63.6)

40 (32.0) 36 (32.1)

85 (68.0) 76 (67.9)

37 (29.4) 39 (35.1)

89 (70.6) 72 (64.9)

22 (25.0) 54 (36.2)

66 (75.0) 95 (63.8)

75 (32.2) 1 (25.0)

158 (67.8) 3 (75.0)

20 (55.6) 56 (27.9)

16 (44.4) 145 (72.1)

66 (32.7) 10 (28.6)

136 (67.3) 25 (71.4)

.437

.002

.165

.002

.499

.981

.342

.073

1.000

.001

.631

.004 47 (26.9) 29 (46.8)

128 (73.1) 33 (53.2)

8 (33.3) 68 (31.9)

16 (66.7) 145 (68.1)

.889

3 (60.0)

.385 2 (40.0) (Continued )

(Continued )

Variables No ART medication type EFV-based No-EFV-based Mean Spiegel score (SD)

Poor-Quality Good-Quality Sleep Sleep n 5 76 (%) n 5 161 (%) p Value 73 (31.5)

159 (68.5)

57 (39.6) 19 (20.4) 17.12 (5.0)

87 (60.4) 74 (79.6) 5.27 (2.8)

.002

.0001

Note. ART 5 antiretroviral therapy; EFV 5 efavirenz; SD 5 standard deviation; USD 5 U.S. dollars.

(69.2%) reported graduating from junior college or less education, with 30.8% acquiring undergraduate or more education. In the sample, 29.5% were married and 70.5% were divorced, widowed, or unmarried. In addition, 77.6% of participants received less than $472.90 USD for a monthly income. HIV infection routes were categorized as sexually transmitted (81.4%) or other (18.6%). Slightly less than half (47.3%) of participants had more than a 350 cells/mm3 CD41 T cell count. Slightly more than half of participants (53.2%) had had HIV for less than 5 years. About a third (32.1%) rated their sleep quality as poor. The characteristics of the participants and their significant associations with sleep quality are shown in Table 1. Sleep Quality Assessment The mean Spiegel score of participants in the poorquality sleep group and the good-quality sleep group was 17.12 6 5.00 (median 5 16.00; range 5 0-11) and 5.27 6 2.8 (median 5 5.0; range 5 12-30), respectively. There was a significant difference between the poor-quality sleep group and the goodquality sleep group (p 5 .0001). Of all sleep complications listed in the Spiegel scale, the poor-quality sleep group had the highest mean score (3.80 6 2.07) for nighttime dreams, followed by a feeling of waking up (3.63 6 1.80), and night waking occurrences (3.37 6 2.13), while nighttime dreams and the feeling of waking up had higher mean scores (1.45 6 1.33; 1.46 6 1.19) than other items in the good-quality sleep group. The mean scores of sleep duration and sleep latency were lower in both groups. There were also significant differences between all

Ren et al. / Factors Associated With Sleep Quality in HIV

observed items between the poor-quality sleep group and the good-quality sleep group (Table 2).

Table 3.

Associated Factors That Contributed to Sleep Quality in Patients with HIV Infection and Receiving ART

Education level (Junior college and less vs Undergraduate and more) Income (#$472.90 USD vs . $472.90 USD) Anxiety (Yes vs. No) Family and social support (No vs. Yes) ART medication (EFV-based vs. no-EFV-based)

Results of Multivariate Logistic Regression Between Sleep Quality and its Associated Factors

Variables

As indicated in Table 1, gender, age, marital status, transmission route, CD41 T cell count, duration of disease, duration of ART, depression, discrimination, hostile psychology, and medication adherence were not significantly associated with sleep quality. In multivariate logistic regression analysis, anxiety was identified as the most important factor contributing to sleep quality (odds ratio [OR] 2.727), followed by ART medication type (OR 2.299). In addition, family and social support also played significant roles in sleep quality of PLWH (OR 1.928). Those patients who received more family and social support had better sleep quality overall. The logistic regression model results showed that education level and income did not have significant effects on sleep quality (Table 3).

Discussion

Comparisons of Each Component Score of the Spiegel Scale Between Patients With Poor and Good Quality Sleep

Item Sleep latency Sleep duration Night waking occurrences Sleep depth Nighttime dream The feeling of waking up

Poor-Quality Sleep Mean (SD)

Good-Quality Sleep Mean (SD) p Value

2.28 (2.28) 1.11 (1.38) 3.37 (2.13)

0.29 (0.58) 0.35 (0.55) 0.80 (1.00)

.0001 .0001 .0001

2.93 (1.78) 3.80 (2.07) 3.63 (1.80)

0.92 (0.95) 1.45 (1.33) 1.46 (1.19)

.0001 .0001 .0001

Note. SD 5 standard deviation.

b

SE Wald Sig.

OR (95% CI)

0.633 0.379 2.786 0.095 1.883 (0.896-3.960)

0.698 0.433 2.594 0.107 2.009 (0.860-4.695)

1.003 0.391 6.566 0.010 2.727 (1.266-5.874) 0.656 0.332 3.907 0.048 1.928 (1.006-3.697)

0.832 0.325 6.579 0.010 2.299 (1.217-4.342)

Note. OR 5 odds ratio; CI 5 confidence interval; USD 5 U.S. dollar; ART 5 antiretroviral therapy; EFV 5 efavirenz.

associated with ART have had a negative impact on PLWH, especially in terms of sleep quality. Sleep Quality Assessed by the Spiegel Scale

The rapid spread of HIV on a global scale has become a serious public health and social issue. With the emergence of ART, the immune function of PLWH has improved, and mortality rates have declined significantly. However, various side effects Table 2.

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We used the Spiegel scale to assess sleep quality in PLWH and receiving ART (N 5 237) and observed that 32.1% had poor-quality sleep. Similar studies using the Spiegel scale have been conducted (Le Guen et al., 2014; Yan et al., 2013). Some studies reported higher poor-quality sleep rates of 46.7% and 46%, respectively (Crum-Cianflone et al., 2012; Ferreira & Ceolim, 2012). In one study, patients with poorquality sleep tended to stay in bed throughout the day due to sleep disturbances and interruptive thoughts experienced during the night (Harvey et al., 2005). Our rates were lower than reported in that study, which might be due to our exclusion criteria and use of different scales. Estimates of poor-quality sleep among PLWH vary from 29.0% to 100%, which is attributed partly to different methods and definitional criteria (Phillips et al., 2006; Reid & Dwyer, 2005). In the Spiegel scale, nighttime dream was the most severe concern compared to other sleep

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complications. One study showed that patients reported an increase in nightmares after ART, which was consistent with our results (Moyle et al., 2006). Many PLWH, especially women, have experienced sleep disturbances, and nightmares were one of their major concerns (Chen, Lee, et al., 2013). Contributory Factors to Sleep Quality in PLWH Receiving ART Multivariate logistic regression showed that anxiety was the most significant independent predictor of sleep quality in our participants. One study indicated that anxiety was a major factor associated with sleep quality and might induce clinically significant sleep disturbances (Ford & Kamerow, 1989). Another study revealed that patients with anxiety had longer sleep-onset latency, a greater number of arousals, and more wake time during the night (Fuller et al., 1997), which further exacerbated the drowsiness already felt by the patient. Anxiety and depression often occur together, and the lifelong comorbid rate of anxiety and depression is high (Kessler et al., 2003). Axelson and Birmaher (2001) showed a synergist effect between anxiety and depression; anxiety associated with depression had more severe symptoms than anxiety occurring alone. Partial correlation analysis from our study indicated that excluding the influence of depression, sleep quality had a linear relationship with anxiety. Furthermore, some therapeutic medications used to treat anxiety might stabilize a patient’s mood and improve sleep quality. Treatment of sleep disturbances may reduce the incidence of anxiety because of the bidirectional relationship between these two symptoms (Ford & Kamerow, 1989). Our results showed that ART medication type was the second highest contributory factor that influenced sleep quality. Although ART can reduce the morbidity and mortality of HIV to some extent, they can cause adverse reactions and lead to more serious health conditions. In general, adverse reactions include changes in appetite, nausea, vomiting, skin rashes, headache, dizziness, fatigue, diarrhea, hepatotoxicity, and osteoporosis. One study indicated that 56% of patients regarded sleep disturbance as an adverse effect of ART (Naidoo, 2009). The initiation of EFV has been commonly associated with sleep

complications. Our study showed that 60.8% of the patients in our study took EFV. The risk of experiencing sleep complications for patients on EFV was 2.299 times higher than for those not on EFV. Patients with an EFV-based regimen have been found to have poor sleep quality (Nu~nez et al., 2001). Moreover, plasma levels of EFV have been shown to be higher in patients with insomnia and reduced sleep efficiency (Gallego et al., 2004). Guidance on drug replacements and treatment programs can help reduce sleep disturbances. The application of nanotechnology can also reduce adverse reactions of ART, which, in turn, can help improve sleep quality (Zhang et al., 2015). In addition, it has been suggested that monitoring adverse reactions to ART should be strengthened and promptly handled (Li et al., 2015). In addition, family and social support was a potential protective factor for sleep quality in our study (No vs. Yes, OR 1.928). Better family and social support was associated with better sleep quality. Social support can have a positive effect on mood, preventing social isolation and promoting healthy sleep habits. Moreover, social support may help maintain a more consistent and consolidated sleep-wake schedule and may affect sleep by attenuating the effects of psychological stress on sleep. Our study had several potential limitations. First, the study was a cross-sectional study and based on self-rated measures, which introduced bias in our results. To improve the quality of this type of research, studies should include more objective clinical assessments of patients. Second, owing to limited resources, the survey was conducted only in Heilongjiang province. Third, our study had a small sample size, which may have limited statistical power. Further investigation with a larger sample is needed.

Conclusion In our study, PLWH who were receiving ART experienced many different sleep complications. Nighttime dreams and the feeling of waking up had significant impacts on the sleep quality of patients. Anxiety, ART medication type, and family and social support were regarded as important factors contributing to sleep quality. More attention should be given to the

Ren et al. / Factors Associated With Sleep Quality in HIV

development of treatment guidelines for proper management of sleep disturbances experienced by PLWH. Efforts should be made to recognize sleep disorders early through routine assessments to improve function and reduce complications for PLWH.

Disclosures The authors report no real or perceived vested interests that relate to this article that could be construed as a conflict of interest.

Key Considerations  People living with HIV (PLWH) who are on antiretroviral therapy (ART) experience unacceptable rates of poor-quality sleep, especially nighttime dreams.  Determinants of sleep quality in PLWH who are on ART include anxiety, type of ART medication, and family and social support.  More attention should be given to treatment guidelines for proper management of sleep disturbances in PLWH. Efforts should be made to improve early recognition of sleep problems through routine assessment and to initiate treatment to improve function and reduce complications for PLWH.

Acknowledgments The authors would like to thank all the participants in this study. This study was funded by CMB Distinguished Professorship Awards and grant #G16916400 (Principal Investigator: Qunhong Wu).

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