Literature DB >> 30697040

The relationship between sleep disturbances and quality of life in elderly patients with hypertension.

Izabella Uchmanowicz1, Karolina Markiewicz1, Bartosz Uchmanowicz1, Aleksandra Kołtuniuk2, Joanna Rosińczuk2.   

Abstract

PURPOSE: Sleep disorders, such as insomnia with objective short sleep duration, are associated with increased risk of hypertension. The objective of the study was to evaluate the effects of insomnia and daytime sleepiness on the quality of life (QOL) among elderly hypertensive patients. PATIENTS AND METHODS: This cross-sectional study covered 100 patients with hypertension. All participants completed standardized questionnaires, such as the Epworth Sleepiness Scale (ESS), the Athens Insomnia Scale (AIS), and the World Health Organization Quality of Life-Brief (WHOQOL-BREF), and clinical data were obtained from patients' medical records.
RESULTS: We showed that more than half of the patients experienced insomnia (AIS score ≥6) and 39% experienced daytime sleepiness. Daytime sleepiness was negatively associated with perceived QOL (r=-0.478, P<0.001). It was also shown that insomnia might be influenced by older age (P<0.001), occupational activity (P=0.011), overweight (body mass index [BMI] 25-30) (P=0.042), and longer duration of illness (P=0.049) among hypertensive patients.
CONCLUSION: Sleep problems have a significant negative impact on the QOL in patients with hypertension, especially in the physical domain of the QOL questionnaire. The occurrence of sleep problems in patients with hypertension is influenced by older age, primary education, overweight, occupational activity, and longer duration of illness.

Entities:  

Keywords:  Athens Insomnia Scale; Epworth Sleepiness Scale; daytime sleepiness; hypertension; insomnia; quality of life; sleep problems

Mesh:

Year:  2019        PMID: 30697040      PMCID: PMC6339653          DOI: 10.2147/CIA.S188499

Source DB:  PubMed          Journal:  Clin Interv Aging        ISSN: 1176-9092            Impact factor:   4.458


Introduction

Hypertension is a major risk factor for cardiovascular disease, including stroke, and it has a significant impact on cardiovascular morbidity and mortality.1–6 Mills et al7 estimated that in 2010, the global prevalence of hypertension was 1.39 billion (31% of all adults), representing a 5.2% increase in global prevalence between 2000 and 2017. Previous studies8–12 have shown that people with hypertension have poorer sleep quality than those with normal blood pressure. It has also been shown that sleep problems are associated with an increased risk of hypertension10,12–14 and vascular inflammation15 with uncontrolled and treatment-resistant hypertension16 and with higher all-cause mortality rates.17 The results of a study by Li et al18 have shown that treatment of sleep disorders in hypertensive patients can decrease blood pressure. Sleep problems, ie, insomnia or excessive daytime sleepiness, are widespread in the general population (about one-third of people suffer from them) and hence is a significant clinical problem.19 Most often, insomnia is defined by the presence of subjective report of difficulty with sleep resulting in too little sleep or poor-quality sleep.20 The general definition of insomnia according to the third edition of the International Classification of Sleep Disorders (ICSD-3) published by the American Academy of Sleep Medicine Board of Directors is characterized by “a persistent difficulty with sleep initiation, duration, consolidation, or quality that occurs despite adequate opportunity and circumstances for sleep, and results in some form of daytime impairment,”21 whereas excessive daytime sleepiness, according to the ICSD, is only a symptom of sleep disorders or other illnesses.19 In a holistic view of health and disease, health-related quality of life (HRQOL) is a key component of health assessment, just as important as the assessment of medical indicators. Achieving improvement in either of these two abovementioned areas is considered a success.22 In the literature, there is a strong correlation between QOL and one’s general state of health. The assessment of HRQOL is particularly important in the context of chronic illness, in which the return to complete efficiency is very difficult or even impossible to achieve. Moreover, QOL assessment is helpful in evaluating the effectiveness of treatment procedures and modifying them when it is necessary.23 The main goals of the assessment of QOL in patients with hypertension include improvement of the quality of provided services, selection of the relevant treatment options or modifying them, individualization of pharmacological treatment, or detection of the adverse reactions during antihypertensive therapy.24 QOL assessment in patients with hypertension is difficult due to the time needed to achieve the effects of the therapy. Antihypertensive therapy is long lasting, and the patient does not notice the results immediately. Undoubtedly, numerous studies underline decreased QOL in patients with hypertension in comparison to the healthy population.25–27 The lowest QOL scores among hypertensive patients are found in terms of physical activity, daily activities related to health, general health, and emotional state. Using effective antihypertensive treatment can reduce the gap between the QOL scores in patients with hypertension and those in the healthy population.28 Factors influencing the HRQOL of patients with hypertension are divided into three groups as follows: sociodemographic, clinical, and other/non-specific. The first group includes age, sex, education, as well as genetic and familial conditions of hypertension. Clinical factors include blood pressure, the presence of organ damage and side effects, comorbidities, the number and types of medications used, and the presence of side effects of pharmacotherapy, obesity, and sexual dysfunctions. Other/non-specific factors are disease diagnosis (the effect of labeling), physical activity, and psychological stress.29 A high HRQOL rating means that a person, in spite of his/her illness, perceives himself/herself as functioning well in every area, whereas a low HRQOL value shows that the disease is a limitation and is an obstacle to proper functioning. Every disease is also associated with the financial burden associated with treatment. Taking into consideration the above, the risk of psychological disorders is much higher in those with chronic illness than in the healthy population. Fear of threats to one’s health, sometimes even to one’s life, leads to mood diminishment or depression. Mental illnesses should not be underestimated; they represent a serious threat to the course of the therapeutic process. Long-term chronic patients learn to live in a “new” situation and to deal with various chronic conditions.29 Undoubtedly, QOL is a very important issue in anti-hypertensive therapy. Both pharmacological and non-pharmacological treatments cause normalization of pressure and reduce the risk of organ complications that contribute to a poorer QOL. Appropriate hypertensive therapy that involves the choice of the right medication group and the individualization of treatment may contribute to QOL improvement and thus encourage the patient to cooperate and adhere to therapeutic recommendations. It has been shown that sleep affects vitality and health status10 and that sleep problems affect daily functioning30 and QOL,8,31–36 and so it can be assumed that in patients with hypertension, sleep problems will have a negative effect on QOL, but this has not been investigated. Therefore, the aim of this study is to evaluate the relationship between insomnia and daytime sleepiness and the QOL in elderly patients being treated for hypertension.

Patients and methods

Study design and settings

This cross-sectional study was conducted from September 2016 to June 2017. The STrengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for reporting of observational studies were followed.

Study participants and selection

The study sample was a group of 100 patients being treated for hypertension in the Clinic of Angiology, Hypertension, and Diabetology at the University Clinical Hospital in Wroclaw, Poland. Inclusion criteria were as follows: 1) age over 18 years; 2) clinically diagnosed hypertension for more than 6 months; 3) absence of mental disorder; and (4) signed informed consent to participate in the study. Exclusion criteria were as follows: 1) previous diagnosis or treatment for sleep problems, eg, sleeping pills and/or antidepressants; 2) previous diagnosis of mental disorder, eg, depression and/or anxiety, and 3) night shift work.

Ethical considerations

The research was approved by the Bioethics Committee of the Wroclaw Medical University, Poland (approval number KB-388/2017). The investigation conforms to the principles outlined in the Declaration of Helsinki and recommendations of Good Clinical Practice. Participation in this study was anonymous and voluntary. All participants gave written informed consent at the beginning of the study. They were also informed of its purpose and of the possibility to withdraw participation at any stage. The dignity and rights of participants were respected at all times.

Research instruments

Participants completed several standardized questionnaires such as the Epworth Sleepiness Scale (ESS),37 the Athens Insomnia Scale (AIS),38 the Polish version of the World Health Organization Quality of Life-Brief (WHOQOL-BREF),39 and the questionnaire designed by the authors for purposes of this study. The questionnaire designed by the authors is a non-validated, self-administered survey that has been designed specifically to be completed by patients with hypertension and collects sociodemographic data (age, sex, height, weight, body mass index [BMI], place of residence, education, marital status, and occupational activity) and includes questions about clinical conditions (hypertension stage, comorbidities, frequency of blood pressure measurements, ability to recognize symptoms of hypertension, knowledge of hypertension complications, past hospitalizations due to hypertension, and recent medications). The ESS is a self-reported scale used for the assessment of daytime sleepiness. Respondents are asked to rate, on a four-point scale (0–3), their usual chances of dozing off or falling asleep while engaged in eight different activities. Overall score ranges from 0 to 24 points, with higher scores indicating greater daytime sleepiness. In general, ESS scores can be interpreted as follows: 0–5 lower normal daytime sleepiness; 6–10 higher normal daytime sleepiness; 11–12 mild excessive daytime sleepiness; 13–15 moderate excessive daytime sleepiness; and 16–24 severe excessive daytime sleepiness.37 The AIS is a self-administered psychometric instrument designed to quantify sleep difficulty. It consists of eight items as follows: the first five pertain to sleep induction, awakenings during the night, final awakening, total sleep duration, and sleep quality, whereas the last three refer to well-being, functioning capacity, and sleepiness during the day. A cutoff score of ≥6 on the AIS is used to establish the diagnosis of insomnia.38 Internal consistency as measured by Cronbach’s alpha was 0.89 in our sample. The WHOQOL-BREF consists of 26 questions assessing the respondents’ overall perception of their HRQOL that gives an overall picture of their health condition. Responses to the first two questions that correspond to the perception of QOL and satisfaction from health were analyzed separately. The remaining 24 questions assess the four domains of the QOL (physical, psychological, social, and environmental QOL). Responses are given using a five-point scale (1–5). QOL in each domain was expressed as a mean value, according to the key and guidelines provided by Wołowicka and Jaracz.39 Higher scores indicate better QOL.

Data analysis

Descriptive statistics (mean, SD, median, quartiles, minimum, and maximum) were calculated for continuous variables. Categorical variables were described as frequencies and percentages of each category. Relationships between categorical variables were analyzed using the chi-squared test (with Yates correction for 2 × 2 tables) or Fisher’s exact test in cases where expected frequencies were low. Normality was checked with the Shapiro–Wilk test. Group differences in continuous variables were analyzed using Student’s t-test (for parametric variables) or the Mann–Whitney test (for non-parametric variables) where there were only two groups. ANOVA (normally distributed variables) or the Kruskal–Wallis test (non-normally distributed variables) was used to analyze group differences where there were three or more groups. Overall effects were subjected to post hoc analysis using Tukey’s HSD test (parametric variables) or Dunn’s test (non-parametric variables). Correlations between continuous variables were analyzed using Pearson’s (for a normal distribution) or Spearman’s correlation coefficient (for non-normal distribution). Correlation coefficients were interpreted as follows: |r|≥0.9 – very strong correlation; 0.7 ≤ |r|<0.9 – strong correlation; 0.5 ≤ |r|<0.7 – moderately strong correlation; 0.3 ≤ |r|<0.5 – weak correlation; and |r|≥0.3 – very weak (negligible) correlation.40 In all analyses, the level of statistical significance was set at P<0.05. The analyses were conducted with R software version 3.3.2.

Results

This study was undertaken among 100 patients with hypertension (54 men and 46 women). The mean age was 65.5±15.6 years. The detailed sociodemographic characteristics of the study participants are shown in Tables 1 and 2.
Table 1

Sociodemographic and clinical data of persons with and without drowsiness

FeaturesDrowsiness (N=39)Lack of drowsiness (N=61)Total (N=100)Pa
N%N%N%
Sex
 Female1641.033049.184646.000.554
 Male2358.973150.825454.00
BMI
 18.5–25: normal weight717.952337.703030.000.064
 25–30: overweight2358.972642.624949.00
 30–35: obesity923.08813.111717.00
 35–40: obesity II°00.0011.6411.00
 >40: obesity III°00.0034.9233.00
Marital status
 Single2051.282845.904848.000.749
 In relationship1948.723354.105252.00
Education
 Primary1128.211118.032222.000.037
 Secondary2256.412642.624848.00
 Higher615.382439.343030.00
Place of residence
 City1743.593455.745151.000.327
 Countryside2256.412744.264949.00
Occupational activity
 Working1641.033963.935555.000.041
 Not working2358.972236.074545.00
Hypertension
 Stage 137.691422.951717.000.139
 Stage 22256.412845.905050.00
 Stage 31435.901931.153333.00
Comorbidities
 Diabetes2051.281321.313333.000.004
 Hypercholesterolemia1641.033557.385151.000.164
 Ischemic heart disease1230.771524.592727.000.654
 Renal failure820.5146.561212.000.056
 Heart failure25.1346.5666.001
Blood pressure measurement
 2–3 a day25.13711.4899.000.651
 Once a day1435.902439.343838.00
 Once a week923.081016.391919.00
 When feeling bad1435.902032.793434.00
Ability to recognize symptoms of hypertension
 Yes1641.034370.495959.000.007
 No2358.971829.514141.00
Knowledge of hypertension complications
 Yes1230.773760.664949.000.007
 No2769.232439.345151.00
Hospitalizations due to hypertension
 1–21948.724777.056666.000.007
 3–52051.281422.953434.00
Medications
 Angiotensin-converting enzyme37.691321.311616.000.125
 Angiotensin receptor antagonists1333.332032.793333.001
 Diuretics1333.331524.592828.000.471
 Adrenergic blockers1435.901422.952828.000.239
 Calcium channel blockers37.69711.481010.000.736
FeaturesDrowsiness (N=39)Lack of drowsiness (N=61)Total (N=100)Pb
M (SD)Me (Q1–Q3)M (SD)Me (Q1–Q3)M (SD)Me (Q1–Q3)
Age (years)69.8 (14.2)70 (61–79.5)60.9 (15.6)64 (49–70)64.4 (15.6)65.5 (52–77)0.005
High (cm)168.5 (10.8)172 (163.5–178.5)170.3 (10.8)170 (165–179)169.6 (10.8)170 (164–179)0.557
Weight (kg)78.4 (12.8)78 (69–89)77.8 (13.8)76 (69–85)78.1 (13.3)76.5 (69–88)0.761
Disease duration (years)16.9 (7.6)15 (11–21.5)13.7 (7.8)13 (7–18)15 (7.8)14 (9.8–20)0.049

Notes:

For BMI, renal and heart failure, the frequency of blood pressure measurements, and intake of calcium channel blockers – the exact Fisher’s test (due to the low expected values in the table); for other variables – chi-squared test.

For age – Student’s t-test (normal distribution); for other variables – Mann–Whitney U test (due to the lack of normal distribution). N, number of patients; P, level of statistical significance.

Abbreviations: BMI, body mass index; M, mean; Me, median; Q1, first quartile; Q3, third quartile.

Table 2

Sociodemographic and clinical data of persons with and without insomnia

FeaturesInsomnia (N=59)Lack of insomnia (N=41)Total (N=100)Pa
N%N%N%
Sex
 Female2542.372151.224646.000.503
 Male3457.632048.785454.00
BMI
 18.5–25: normal weight1423.731639.023030.000.042
 25–30: overweight3457.631536.594949.00
 30–35: obesity1016.95717.071717.00
 35–40: obesity II°11.6900.0011.00
 >40: obesity III°00.0037.3233.00
Marital status
 Single3152.541741.464848.000.375
 In relationship2847.462458.545252.00
 Education
 Primary1525.42717.072222.000.109
 Secondary3152.541741.464848.00
 Higher1322.031741.463030.00
Place of residence
 City2949.152253.665151.000.81
 Countryside3050.851946.344949.00
Occupational activity
 Working2542.373073.175555.000.005
 Not working3457.631126.834545.00
Hypertension
 Stage 1711.861024.391717.000.014
 Stage 22644.072458.545050.00
 Stage 32644.07717.073333.00
Comorbidities
 Diabetes2338.981024.393333.000.19
 Hypercholesterolemia2338.982868.295151.000.007
 Ischemic heart disease2135.59614.632727.000.036
 Renal failure1016.9524.881212.000.115
 Heart failure58.4712.4466.000.396
Blood pressure measurement
 2–3 a day610.1737.3299.000.361
 Once a day2644.071229.273838.00
 Once a week915.251024.391919.00
 When feeling bad1830.511639.023434.00
Ability to recognize symptoms of hypertension
 Yes2949.153073.175959.000.028
 No3050.851126.834141.00
Knowledge of hypertension complications
 Yes2135.592868.294949.000.003
 No3864.411331.715151.00
Hospitalizations due to hypertension
 1–22949.153790.246666.00<0.001
 3–53050.8549.763434.00
Medications
 Angiotensin-converting enzyme1016.95614.631616.000.973
 Angiotensin receptor antagonists2338.981024.393333.000.19
 Diuretics1830.511024.392828.000.657
 Adrenergic blockers1525.421331.712828.000.644
 Calcium channel blockers58.47512.201010.000.736
FeaturesInsomnia (N=39)Lack of insomnia (N=61)Total (N=100)Pb
M (SD)Me (Q1–Q3)M (SD)Me (Q1–Q3)M (SD)Me (Q1–Q3)
Age (years)69.4 (14.6)70 (60.5–80)57.1 (14.2)59 (49–68)64.4 (15.6)65.5 (52–77)<0.001
High (cm)168.2 (10.5)169 (161–174.5)171.7 (11)171 (166–181)169.6 (10.8)170 (164–179)0.053
Weight (kg)76.6 (11.1)78 (69–88)80.1 (16)75 (70–90)78.1 (13.3)76.5 (69–88)0.521
Disease duration (years)16.7 (7.9)15 (11–22)12.5 (7.1)12 (7–17)15 (7.8)14 (9.8–20)0.049

Notes:

For BMI, renal and heart failure, the frequency of blood pressure measurements, and intake of calcium channel blockers – the exact Fisher’s test (due to the low expected values in the table); for other variables – chi-squared test.

For age – Student’s t-test (normal distribution); for other variables – Mann–Whitney U test (due to the lack of normal distribution). N, number of patients; P, level of statistical significance.

Abbreviations: BMI, body mass index; M, mean; Me, median; Q1, first quartile; Q3, third quartile.

We showed that 39% of the patients reported daytime sleepiness (37% mild and 2% moderate) on the ESS scale, and 59% were suffering from insomnia according to the AIS scale. Mean levels of QOL and health perception according to the WHOWOL-BREF scale were 3.68±0.68 and 3.24±0.65, respectively. Particular results for each domain were 13.8±2.27 for physical, 13.24±2.23 for psychological, 14.73±3.32 for social, and 13.19±2.41 for environmental. Daytime sleepiness was more common in the elderly (P=0.005), the less well-educated (P=0.03), and the nonoccupational (P=0.04). Sleepiness was also more common in patients with longer duration of hypertension (P=0.049), with diabetes as a comorbidity (P=0.004), who are characterized by the lack of knowledge about symptoms of hypertension (P=0.007), and its complications (P=0.007) and patients who were more frequently hospitalized due to complications of hypertension (P=0.007). The results are presented in Table 1. Insomnia was more common in participants who were elderly (P<0.001), non-working (P=0.005), overweight (P=0.042), clinically diagnosed with third stage hypertension (P=0.014), clinically diagnosed with comorbid hypercholesterolemia (P=0.007) or ischemic heart disease (P=0.036), characterized by a lack of knowledge about the symptoms of hypertension (P=0.028) or complications of hypertension (P=0.003), and patients who were more frequently hospitalized due to complications of hypertension (P<0.001). The results are presented in Table 2. Many of the sociodemographic variables were associated with both sleepiness and insomnia. The results are presented in Tables 3 and 4.
Table 3

Correlations between sociodemographic variables and the result of the ESS questionnaire

VariablesSpearman correlation coefficient (rho)Pa
M (SD)Me (Q1–Q3)
Agerho =0.3380.001
Disease durationrho =0.2480.013
Sex
 Female9.35 (2.84)9 (8–12)0.379
 Male9.85 (2.84)10 (7.25–12)
BMI
 Normal weight8.57 (2.66)8.5 (7–10)0.042
 Overweight10.22 (2.69)10 (8–13)
 Obesity9.71 (3.12)10 (8–12)
Marital status
 Single9.77 (2.88)10 (8–12)0.555
 In relationship9.48 (2.82)9.5 (7–12)
Education
 Primary10.5 (2.48)10.5 (9–12)0.022
 Secondary9.9 (2.87)10 (7.75–12)
 Higher8.53 (2.78)8 (6.25–10)
Place of residence
 City9.06 (2.79)9 (7–12)0.043
 Countryside10.2 (2.8)10 (8–12)
Occupational activity
 Working9 (2.68)9 (7–11)0.011
 Not working10.38 (2.87)11 (9–13)
Hypertension
 Stage 18.47 (2.53)8 (7–9)0.077
 Stage 29.56 (3.09)9.5 (7–12)
 Stage 310.3 (2.43)10 (9–12)

Notes:

Mann–Whitney U test or Kruskal–Wallis test. P, level of statistical significance.

Abbreviations: BMI, body mass index; ESS, Epworth Sleepiness Scale; M, mean; Me, median; Q1, first quartile; Q3, third quartile.

Table 4

Correlations between sociodemographic variables and the result of the AIS questionnaire

VariablesSpearman correlation coefficient (rho)Pa
M (SD)Me (Q1–Q3)
Agerho =0.3370.001
Disease durationrho =0.1770.078
Sex
 Female7.7 (4.7)6.5 (4–11)0.716
 Male7.61 (4.76)8 (3.25–10)
BMI
 Normal weight6.8 (5.25)4.5 (3–9.5)0.137
 Overweight8.22 (4.04)9 (5–10)
 Obesity7.52 (5.37)6 (4–11)
Marital status
 Single8.38 (4.92)8 (4.75–11)0.113
 In relationship6.98 (4.45)6.5 (3–9.25)
Education
 Primary8.64 (4.68)8.5 (5–11.75)0.071
 Secondary8.06 (4.75)8 (4–10.25)
 Higher6.27 (4.51)4 (3–8.75)
Place of residence
 City7.18 (4.05)7 (3.5–10)0.621
 Countryside8.14 (5.31)8 (4–11)
Occupational activity
 Working6.13 (3.88)5 (3–8)<0.001
 Not working9.51 (5)10 (6–12)
Hypertension
 Stage 16.71 (4.37)5 (4–8)0.185
 Stage 27.3 (5.08)6.5 (3–10.75)
 Stage 38.67 (4.23)9 (6–10)

Notes:

Mann–Whitney U test or Kruskal–Wallis test. P, level of statistical significance.

Abbreviations: AIS, Acceptance of Illness Scale; BMI, body mass index; M, mean; Me, median; Q1, first quartile ; Q3, third quartile.

We also found that sleepiness affected all domains of QOL in patients with hypertension: the greater their daytime sleepiness, the lower their QOL. Daytime sleepiness had the greatest effect on physical QOL (r=−0.565, P<0.001) and psychological QOL (r=−0.554, P<0.001). Insomnia affected the QOL in patients with hypertension. There was a negative correlation between AIS score and all domains of QOL as measured by the WHOQOL-BREF. Insomnia had most effect on physical (r=−0.582, P<0.001) and psychological domain of QOL (r=−0.520, P<0.001). The results are presented in Table 5.
Table 5

Correlations for sleep disturbances and QOL

WHOQOL-BREFCorrelations with questionnaires
ESSAIS
Pearson correlationP-valuePearson correlationP
QOL perception−0.478<0.001−0.432<0.001
Health perception−0.2780.005−0.2950.003
Physical domain−0.565<0.001−0.582<0.001
Psychological domain−0.554<0.001−0.52<0.001
Social domain−0.544<0.001−0.446<0.001
Environmental domain−0.546<0.001−0.437<0.001

Note: P, level of statistical significance.

Abbreviations: AIS, Acceptance of Illness Scale; ESS, Epworth Sleepiness Scale; QOL, quality of life; WHOQOL-BREF, World Health Organization Quality of Life-Brief.

The results for the relationship between sleep disturbances for all domains of the ESS questionnaire and QOL perception are presented in Figure 1.
Figure 1

Correlations for sleep disturbances in ESS and QOL.

Abbreviations: ESS, Epworth Sleepiness Scale; QOL, quality of life.

Discussion

Insomnia is one of the most common sleep problems, and because of its prevalence, it is a serious problem in the modern society.17,41 General population studies in Asia42,43 and in Europe33,44 have shown that the proportion of people suffering from sleep problems, including insomnia, is significantly lower than in Poland,45 where the majority reports subjective insomnia. These differences are most likely due to differences in diagnostic methods. The proportion of people with insomnia is higher among the population of people visiting their general practitioner (GP) than in the general population,30,46 perhaps because people seeing their GP have other diseases and disorders that may affect the risk of developing insomnia. Over 40% of the patients seeing their GP for hypertension were found to have poor sleep8 or insomnia;47 these proportions are similar to those obtained in this study. Studies by Al-Tannir et al9 and Hinz et al33 showed that adults who were not occupationally active were more likely to complain of sleep problems, which was corroborated in this study. Alebiosu et al8 confirmed that patients who have been ill for a long time are more likely to complain about sleep problems, and we found that patients with longer duration of hypertension were more likely to complain of daytime sleepiness and insomnia. Egyptian31 and Chinese43 studies found that people who are single or divorced often suffer from insomnia, but our results did not corroborate this. We also found no evidence that insomnia was more prevalent in rural residents than urban residents.43 We did, however, find that people with a BMI of >25 were more likely to complain of insomnia, corroborating the finding of Hinz et al.33 Recent research studies in samples of elderly people31 and patients with chronic diseases47 such as diabetes,36 rheumatoid arthritis,34 and Parkinson’s disease32 have shown that sleep problems have a negative effect on QOL, which is also confirmed in this study. To the best of our knowledge, this study is the first to evaluate the relationship between insomnia, sleepiness, and QOL in patients with hypertension. It should be recommended to assess sleep patterns and behaviors in patients and plan their care around these responses. Assessment of sleep routines and practical strategies that may improve patients’ sleep may be essential for a patient and may be important as a part of nursing care. In the case of long-time sleep problems, the medical team should recommend a medication regimen. There are some potential limitations of this study that are discussed briefly. First of all, in this study, there were mixed sleep disturbances including insomnia and sleepiness among patients with hypertension. It should be pointed out that sleepiness is not a typical symptom of insomnia and probably it would have been better to specify study outcomes and evaluate tiredness. The best solution would be to analyze the relationship between insomnia and HRQOL in these patients with hypertension (without sleepiness) as the main outcome. Also, sleepiness must be taken into account as a possible symptom of undiagnosed sleep disorders in general, such as obstructive sleep apnea. Another limitation is that the study lacks an external control group, which would be valuable to compare the obtained results. Last but not least, objective tools such as respiratory polygraphy or polysomnography for diagnosis of sleep-disordered breathing were not used; however, they should be considered in the future studies.

Conclusion

This observational study shows that sleep problems have a significant negative impact on the QOL of patients with hypertension. Sleep problems have a significant negative impact on the QOL in patients with hypertension, especially in the physical domain of the QOL questionnaire. The occurrence of sleep problems in patients with hypertension is influenced by older age, primary education, overweight, occupational activity, and longer duration of illness.
  40 in total

1.  Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.

Authors: 
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Review 2.  Health related quality of life outcome instruments.

Authors:  Gunnar Németh
Journal:  Eur Spine J       Date:  2005-12-01       Impact factor: 3.134

Review 3.  Insomnia: definition, prevalence, etiology, and consequences.

Authors:  Thomas Roth
Journal:  J Clin Sleep Med       Date:  2007-08-15       Impact factor: 4.062

4.  Hypertension and health-related quality of life. an epidemiological study in Sweden.

Authors:  C Bardage; D G Isacson
Journal:  J Clin Epidemiol       Date:  2001-02       Impact factor: 6.437

5.  Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria.

Authors:  C R Soldatos; D G Dikeos; T J Paparrigopoulos
Journal:  J Psychosom Res       Date:  2000-06       Impact factor: 3.006

6.  The relationship between insomnia and health-related quality of life in patients with chronic illness.

Authors:  David A Katz; Colleen A McHorney
Journal:  J Fam Pract       Date:  2002-03       Impact factor: 0.493

7.  Quality of sleep among hypertensive patients in a semi-urban Nigerian community: a prospective study.

Authors:  Olutayo C Alebiosu; Olawale O Ogunsemi; Oluranti B Familoni; P B Adebayo; O E Ayodele
Journal:  Postgrad Med       Date:  2009-01       Impact factor: 3.840

8.  A new method for measuring daytime sleepiness: the Epworth sleepiness scale.

Authors:  M W Johns
Journal:  Sleep       Date:  1991-12       Impact factor: 5.849

Review 9.  Health-related quality of life--an introduction.

Authors:  Dinesh Khanna; Joel Tsevat
Journal:  Am J Manag Care       Date:  2007-12       Impact factor: 2.229

10.  Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.

Authors:  Salim Yusuf; Steven Hawken; Stephanie Ounpuu; Tony Dans; Alvaro Avezum; Fernando Lanas; Matthew McQueen; Andrzej Budaj; Prem Pais; John Varigos; Liu Lisheng
Journal:  Lancet       Date:  2004 Sep 11-17       Impact factor: 79.321

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  14 in total

1.  Mental Health of the Participants of the Third Age University Program: A Cross-Sectional Study.

Authors:  Mateusz Cybulski; Łukasz Cybulski; Urszula Cwalina; Krystyna Kowalczuk; Elżbieta Krajewska-Kułak
Journal:  Front Psychiatry       Date:  2020-07-10       Impact factor: 4.157

2.  Insomnia in Older Adults.

Authors:  Vivian Nguyen; Tessy George; Glenna S Brewster
Journal:  Curr Geriatr Rep       Date:  2019-10-22

3.  Association between poor sleep quality and depression symptoms among the elderly in nursing homes in Hunan province, China: a cross-sectional study.

Authors:  Zhao Hu; Xidi Zhu; Atipatsa Chiwanda Kaminga; Tingting Zhu; Yu Nie; Huilan Xu
Journal:  BMJ Open       Date:  2020-07-13       Impact factor: 2.692

4.  Association between sleep disorder and quality of life in patients with type 2 diabetes: a cross-sectional study.

Authors:  Yoshitaka Hashimoto; Ryosuke Sakai; Kenichiro Ikeda; Michiaki Fukui
Journal:  BMC Endocr Disord       Date:  2020-06-30       Impact factor: 2.763

5.  Sleep disorders among educationally active elderly people in Bialystok, Poland: a cross-sectional study.

Authors:  Mateusz Cybulski; Lukasz Cybulski; Elzbieta Krajewska-Kulak; Magda Orzechowska; Urszula Cwalina; Krystyna Kowalczuk
Journal:  BMC Geriatr       Date:  2019-08-19       Impact factor: 3.921

6.  Psycho-behavioural factors associated with medication adherence among male out-patients with hypertension in a Ghanaian hospital.

Authors:  Irene A Kretchy; Vincent Boima; Kofi Agyabeng; Augustina Koduah; Bernard Appiah
Journal:  PLoS One       Date:  2020-01-29       Impact factor: 3.240

7.  Evaluation of a multi-component, non-pharmacological intervention to prevent and reduce sleep disturbances in people with dementia living in nursing homes (MoNoPol-sleep): study protocol for a cluster-randomized exploratory trial.

Authors:  Martin N Dichter; Almuth Berg; Jonas Hylla; Daniela Eggers; Denise Wilfling; Ralph Möhler; Burkhard Haastert; Gabriele Meyer; Margareta Halek; Sascha Köpke
Journal:  BMC Geriatr       Date:  2021-01-12       Impact factor: 3.921

8.  Factors associated with insomnia in older adult outpatients vary by gender: a cross-sectional study.

Authors:  Yu-Ting Peng; Ying-Hsin Hsu; Ming-Yueh Chou; Che-Sheng Chu; Chen-San Su; Chih-Kuang Liang; Yu-Chun Wang; Tsan Yang; Liang-Kung Chen; Yu-Te Lin
Journal:  BMC Geriatr       Date:  2021-12-07       Impact factor: 3.921

9.  The prevalence of poor sleep quality and associated risk factors among Chinese elderly adults in nursing homes: A cross-sectional study.

Authors:  Xidi Zhu; Zhao Hu; Yu Nie; Tingting Zhu; Atipatsa Chiwanda Kaminga; Yunhan Yu; Huilan Xu
Journal:  PLoS One       Date:  2020-05-15       Impact factor: 3.240

10.  Preoperative sleep quality affects postoperative pain and function after total joint arthroplasty: a prospective cohort study.

Authors:  Ze-Yu Luo; Ling-Li Li; Duan Wang; Hao-Yang Wang; Fu-Xing Pei; Zong-Ke Zhou
Journal:  J Orthop Surg Res       Date:  2019-11-21       Impact factor: 2.359

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