Prevalence of poor sleep quality and its associated factors among hypertensive patients on follow up at Jimma University Medical Center

Sleep quality among patients with chronic illness in Ethiopia: systematic review and meta-analysis

Background

Poor sleep quality impedes the progression of chronic illnesses, while chronic illnesses themselves are caused by poor sleep quality. Despite this fact, there is no research that has been conducted in Ethiopia that provides a thorough estimate of the self-reported sleep quality among patients with chronic illnesses. In order to present a complete picture of poor sleep quality among diabetes, hypertension, heart failure, cancer, HIV/AIDS and epilepsy patients, this systematic review and meta-analysis was carried out.

Methods

Systematic review and meta-analysis was conducted to estimate the quality of sleep among patients with chronic illness in Ethiopia. The Preferred Reporting Items for Systematic Review and Meta Analysis standard was followed in the reporting of this systematic review and meta-analysis. An extensive exploration of digital repositories, including PubMed, EMBASE, Cochrane, Africa Journal of Online, Google Scholar, and an advanced Google search, was conducted to obtain published studies until December 1st, 2023 detailing poor sleep quality of patients with chronic illness. STATA version 17 commands were used to create the pooled estimate. The I2 test and Egger's test, respectively, were used to identify the presence of heterogeneity and publication bias. To manage heterogeneity, a subgroup analysis and random effect model were used.

Results

A total 21 articles with a total of 7393 participants were included in the final systematic review and meta-analysis. The pooled estimate of poor sleep quality among patients with chronic illness was 52% (95% of CI: 48%, 59%; I2 = 97.26%). In subgroup analysis, the highest pooled estimate of poor sleep quality was observed in cancer patients 63% (95% CI: (95% CI: 45% - 80%). Regarding to data collection period, the highest pooled estimate of poor sleep quality was seen during spring 68% (95% CI: 42% - 94%).

Conclusions

Patients with chronic illnesses in Ethiopia had a high pooled estimate of poor sleep quality. Patients with cancer had the highest pooled estimate of poor-quality sleep compared with other patients. Patients with chronic illnesses had trouble sleeping in the spring, according to this systematic review and meta-analysis. Therefore, attention and intervention should be given to enhance the quality of sleep for patients with chronic illnesses.

Poor sleep quality and associated factors among adult chronic kidney disease patients

Background

Poor sleep quality is a common concern in chronic kidney disease (CKD) patients, which can accelerate the progression of chronic renal disease and negatively impact their health-related quality of life, potentially leading to greater morbidity and mortality rates. It can also have an effect on the immune system, cognitive function, and emotional well-being of CKD patients. Furthermore, poor sleep quality may contribute to drug noncompliance and decreased participation in the entire treatment plan. Nonetheless, no research has been undertaken in Ethiopia on the prevalence of poor sleep quality and its associated factors among CKD patients.

Objective

This study aimed to assess the prevalence of poor quality of sleep and associated factors among chronic kidney disease patients at the University of Gondar Comprehensive Specialized and Felege Hiwot Referral Hospitals in 2020.

Methods

A cross-sectional study design was implemented at the University of Gondar Comprehensive Specialized and Felege Hiwot Referral Hospitals between February and April 2020. The study participants were chosen through systematic random sampling techniques. The Pittsburgh Sleep Quality Index (PSQI), a validated assessment tool, was utilized to measure sleep quality. A PSQI total score > 5 was used as an indicator of poor sleep quality. Subsequently, the data obtained were entered into Epi Data version 3.0 and then transferred to STATA 14 for analysis. Both bivariable and multivariable binary logistic regression analyses were performed to recognize factors associated with poor sleep quality. In the multivariable logistic regression analysis, variables demonstrating a p-value of ≤0.05 were considered statistically associated to poor sleep quality.

Results

In this study, 424 CKD patients were included. Among screened CKD patients, 42.9% tested positive for poor sleep quality with a 95% CI (38 to 47%). Independent predictors of poor sleep quality among CKD patients were common mental disorder [AOR = 1.8, 95% CI (1.19-2.89)], anemia [AOR = 2.7, 95% CI (1.71-4.36)], declined eGFR between 60 and 89.9 [AOR = 1.6; 95% CI (2.28-5.54)], 30-59.9 [AOR = 2.6, 95% CI (1.53-4.43)], and ≤ 30 [AOR = 3.8, 95% CI (1.17-12.61)], age > 50 years [AOR = 1.7(1.11-2.69)] and duration of disease 2.9 [AOR = 2.9, 95% CI (1.77-4.90)].

Conclusion

In our study, almost 1 out of 2 CKD patients assessed for poor sleep quality tested positive. It was noted that poor sleep quality was more frequent among CKD patients with common mental disorders, anemia, decreased eGFR levels, individuals aged over 50 years, and those with a longer duration of the disease. Consequently, it's advised to regularly screen these CKD patients for poor sleep quality.

Bidirectional associations between sleep quality/duration and multimorbidity in middle-aged and older people Chinese adults: a longitudinal study

BACKGROUND

Multimorbidity and sleep disorder possess high incidence rates in the middle-aged and older people populations, posing a significant threat to quality of life and physical and mental health. However, investigators have previously only analysed the unidirectional association between sleep status and multimorbidity. We aimed to investigate bidirectional associations between sleep quality or duration and multimorbidity in middle-aged and older Chinese adults from a longitudinal perspective.

METHOD

We enrolled a total of 9823 participants 45 years and older from the China Health and Retirement Longitudinal Study from 2015 to 2018 in our study. Multimorbidity was defined as two or more coexisting chronic diseases in the same individual based on 14 self-reported disease questions. Sleep quality was classified as "good" (restless < 1 day per week) and "poor" (restless ≥ 1 days per week); and sleep duration was divided into short (< 6 h), medium (6-9 h), and long (> 9 h). The bidirectional association between multimorbidity and sleep condition was examined using multivariate logistic regression models with adjustments for covariates.

RESULTS

Individuals with poor sleep quality showed a significantly higher prevalence of multimorbidity in the future. The adjusted OR (95% CI) values of individuals with poor sleep quality with respect to developing two diseases, three diseases, and ≥ 4 diseases were 1.39 (1.19, 1.63), 1.56 (1.23, 2.03), and 2.36 (1.68, 3.33), respectively. In addition, individuals with multimorbidity exhibited a significantly higher risk of poor sleep quality in the future. Short sleep duration led to multimorbidity in the future (OR = 1.49; 95 CI%, 1.37-1.63), while multimorbidity contributed to short sleep duration (< 6 h) in the future (OR = 1.39; 95% CI, 1.27-1.51) after full adjustment.

CONCLUSIONS

There was a bidirectional association between sleep quality or short sleep duration and multimorbidity in middle-aged and older Chinese adults. We recommend that greater attention be given to clinical management among adults with sleep disorders or physical multimorbidities.

The association between passive smoking and sleep quality in a Chinese hypertensive population: A cross-sectional study

INTRODUCTION

This study evaluates the association between passive smoking, specifically secondhand smoke (SHS) and thirdhand smoke (THS) exposure, and sleep quality in a hypertensive population.

METHODS

We enrolled 1427 eligible hypertensive patients from a 2022 national cross-sectional survey in China. Data on tobacco smoke exposure and sleep were collected via questionnaires. Multiple logistic regression and linear regression were employed to assess the relationship between passive smoking and sleep quality characteristics, as well as the correlation between passive smoking exposure characteristics and sleep quality.

RESULTS

Among 589 hypertensive patients with no tobacco smoke exposure, 679 exposed to SHS, and 159 exposed to THS, SHS exposure was associated with a higher risk of poor sleep quality, even after adjusting for potential confounding factors (β=0.10; 95% CI: 0.32-0.95). No significant relationship was observed between THS exposure and sleep quality. SHS exposure was associated with various sleep quality characteristics, including shorter sleep duration (AOR=1.71; 95% CI: 1.06-2.76) and increased frequency of 1-2 sleep disturbances per week (AOR=1.68; 95% CI: 1.25-2.26). Individuals exposed to SHS were more likely to experience poorer subjective sleep quality (AOR=1.53; 95% CI: 1.07-2.21) and have sleep efficiency <65% (AOR=1.82; 95% CI: 1.22-2.71). Exposure to passive smoking at home, in the community, in public places, exposure to passive smoking with family and friends, and increased frequency of exposure, were all associated with a higher risk of poor sleep quality.

CONCLUSIONS

Our study suggests that SHS exposure in hypertensive populations is associated with poor sleep quality and various characteristics of sleep quality. No significant association was found between THS exposure and sleep quality. These findings underscore the need to enhance tobacco control efforts in China, particularly for individuals with chronic diseases, to safeguard public health.

Sweet dreams are not made of this: no association between diet and sleep quality

STUDY OBJECTIVES

Numerous studies have emphasized the significance of nutrition on the quality of sleep, but few have evaluated the effect of various coexisting dietary markers on middle-aged adults. We assessed the association between sleep quality and a large array of dietary markers among middle-aged, community-dwelling participants.

METHODS

Data from the first, second, and third follow-ups of CoLaus|PsyCoLaus, a population-based study in Lausanne, Switzerland, was used. Sleep quality was assessed by the Pittsburgh Sleep Quality Index. Dietary intake was assessed by a validated food frequency questionnaire.

RESULTS

Data from 3857 (53% women, 57.2 ± 10.4 years), 2370 (52% women, 60.7 ± 9.5 years), and 1617 (52% women, 63.5 ± 9.0 years) participants from the first, second, and third follow-ups was used. Bivariate correlations showed fish, vegetables, fruit, and cheese intake to be associated with a better sleep quality (lower Pittsburgh Sleep Quality Index), while rusks, sugar, and meat intake were associated with a poorer sleep quality (higher Pittsburgh Sleep Quality Index). After multivariable adjustment, participants reporting poor sleep quality (Pittsburgh Sleep Quality Index > 5) had a lower Mediterranean diet score and a lower likelihood of complying with the meat and fish recommendations, but the results were inconsistent between surveys. No association was found between sleep quality and macro- or micronutrients in the three surveys.

CONCLUSIONS

No consistent associations were found between a large panel of nutritional markers and sleep quality. Components of the Mediterranean diet such as dairy, fruits, and vegetables might favor good sleep quality, while increased consumption of sugary foods or meat might favor poor sleep quality.

CITATION

Oliveira JL, Marques-Vidal P. Sweet dreams are not made of this: no association between diet and sleep quality. J Clin Sleep Med. 2023;19(12):2005-2014.

Modifiable behavioral risk factors for NCDs and sleep in Brazilian adolescents

OBJECTIVE

To analyze the association between modifiable behavioral risk factors for non-communicable diseases and sleep parameters in Brazilian adolescents.

METHODS

This was a cross-sectional study that used data from the RPS Cohort Consortium, São Luís, Brazil for the follow-up of adolescents aged 18-19 years (n = 2,515). The outcomes were excessive daytime sleepiness (Epworth Sleepiness Scale - ESS) and sleep quality (Pittsburgh Sleep Quality Index - PSQI). The exposures of interest were the behavioral risk factors for non-communicable diseases (NCDs): screen time, physical inactivity, alcohol, smoking, illicit drugs, caffeine intake, and consumption of sugar-sweetened beverages. Excess weight was considered a possible mediator of this association between the exposures of interest and the outcomes. The models were analyzed by modeling with structural equations.

RESULTS

Physical inactivity (standardized coefficient, SC = 0.112; p = 0.001), higher consumption of alcohol (SC = 0.168; p = 0.019) and of sugar-sweetened beverages (SC = 0.128; p < 0.001) were associated with excessive daytime sleepiness in adolescents; better socioeconomic status was also associated with this outcome (SC = 0.128; p < 0.001). Physical inactivity (SC = 0.147; p < 0.001) and higher consumption of sugar-sweetened beverages (SC = 0.089; p = 0.003) were also associated with poor sleep quality. Overweight was neither a mediator nor associated with sleep quality or excessive daytime sleepiness.

CONCLUSIONS

The main modifiable behavioral risk factors for NCDs are associated with worse sleep parameters already in adolescence, which serves as a warning toward the accumulation of risks for sleep disorders in the future.

Hypertension, sleep quality, depression, and cognitive function in elderly: A cross-sectional study

Background

Hypertension, sleep disorders, and depression are highly prevalent in the elderly population and are all associated with cognitive impairment, but the role that sleep quality and depression play in the association between hypertension and cognitive impairment is unclear. The aim of this study was to investigate whether sleep quality and depression have a mediating role in the association between hypertension and cognitive impairment.

Methods

A cross-sectional study was conducted to collect data from the Tongji Hospital Comprehensive Geriatric Assessment Database. Sleep quality, depression and cognitive function were measured by the Pittsburgh Sleep Quality Index (PSQI), the Geriatric Depression Scale (GDS-15) and the Mini-Mental State Examination (MMSE), respectively. Correlation analysis, regression analysis and Bootstrap analysis were used to examine correlations between key variables and mediating effects of sleep quality and depression. Adjustments for multiple comparisons were performed using Benjamini-Hochberg adjustment for multiple testing.

Results

A total of 827 participants were included, hypertension was present in 68.3% of the sample. After correcting for covariates, hypertensive patients aged 65 years or older had worse cognitive function, poorer-sleep quality and higher levels of depression. Sleep quality was significantly negatively associated with depression and cognitive function, while depression was negatively associated with cognitive function. Mediation analysis revealed that hypertension can affect cognitive function in older adults through a single mediating effect of sleep quality and depression and a chain mediating effect of sleep quality and depression.

Conclusion

This study found that sleep quality and depression can mediate the relationship between hypertension and cognitive function in elderly. Enhanced supervision of sleep quality and depression in elderly patients with hypertension may be beneficial in maintaining cognitive function.

Poor sleep quality is associated with new-onset hypertension in a diverse young and middle-aged population

BACKGROUND

Sleep disorders have been proposed as the potential risk factors for hypertension, thus we aimed to investigate the association of sleep quality with new-onset hypertension.

METHODS

We evaluated sleep quality using Pittsburgh Sleep Quality Index (PSQI) and it's seven components in normotensive population aged 18 years old and over in Emin Xinjiang, China in 2016 and followed up till 2019 using annual health checkup data. Poor sleep quality was defined as a PSQI score>5, and good sleep quality was defined as a PSQI score⩽5.

RESULTS

Among 9344 analytic sample 57.29% were female. A total of 2958 (31.66%) subjects developed hypertension during 22,960 person-years of follow-up. Poor sleep quality (HR 1.131, 95% CI 1.045, 1.224) showed had higher risk of development hypertension in total population in adjusted Cox models. Fairly bad subjective sleep quality (HR 1.148, 95% CI 1.015, 1.298), habitual sleep efficiency of <65%-75% group (HR 1.174, 95% CI 1.026, 1.344), and mild (HR 1.194, 95% CI 1.098, 1.299) and moderate (HR 1.264, 95% CI 1.080, 1.479) sleep disturbance increased the risk of developing hypertension compared to their counterparts. In age stratification, poor sleep quality (HR 1.100, 95% CI 1.007, 1.202) had higher risk of developing hypertension in the young and middle-aged population after adjusted all covariates.

CONCLUSIONS

Poor sleep quality is associated with higher risk of new-onset hypertension in young and middle-aged population.

Sleep Disorders in Individuals With High Risk for Diabetes in Indian Population

Background:

Sleep restores physiology and neurochemical components of our body and is essential for physical and mental health. Sleep disorders (SDs) are associated with insulin resistance and metabolic disorders. The association between SDs and diabetes needs to be understood in the Indian population.

Purpose:

The purpose was to investigate the association between SD and diabetes in the Indian population.

Methods:

As a part of nationwide Niyantrita Madhumeha Bharata Abhiyaan-2017 (NMB-2017), a cross-sectional study was conducted and data was collected from seven zones of India, after screening through the Indian Diabetes Risk Score (IDRS). The sleep quality was assessed on a scale of 1 to 4 (very good = 1, very bad = 4). The time taken to fall asleep (sleep latency) was assessed on a scale of 0 to 5 (“0” = nil and “5” = >1.5 h). Stress was assessed by the perceived stress scale.

Results:

Bad sleep quality was positively (odds ratio 1.055, CI [1.001, 1.113], and P < .01) associated with self-reported known diabetes. Increased time taken to fall in sleep (sleep latency) was associated significantly with IDRS high risk (odds ratio 1.085, CI [1.008, 1.168], and P = .01), with an average sleep latency /time takes to fall in sleep (maximum range 5 [>1.5 h], mode 2 [10 to 30 min]) minutes. Moderate stress was significantly associated with bad sleep quality (odds ratio 1.659).

Conclusion:

A positive association of bad sleep quality and stress with diabetes, and an increased sleep latency in the IDRS high-risk population point to the role of modifiable risk factors. Behavioral modification and stress reduction by using yoga may be beneficial in the better management of diabetes.