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Assessment of Health Related Quality of Life and Associated Factors among Hypertensive Patients on Treatment at Public Hospitals in Mekelle, North Ethiopia

Alemayehu Hailu Jufar1*, Fiseha Girma Nuguse2 and Haftom Ghiwot Misgna2

1Department of Physiology, College of Health Sciences, Mekelle University, Mekelle, Ethiopia

2School of Nursing, College of Health Sciences, Mekelle University, Mekelle, Ethiopia

*Corresponding Author:
Jufar AH
Department of Physiology
College of Health Sciences
Mekelle University, P.O.BOX 1871
Mekelle, Ethiopia
Tel: +251911172095
Email: alemayehuhailu62@yahoo.com

Received Date: February 16, 2017; Accepted Date: February 26, 2017; Published Date: February 28, 2017

Citation: Jufar AH, Nuguse FG, Misgna HG (2017) Assessment of Health Related Quality of Life and Associated Factors among Hypertensive Patients on Treatment at Public Hospitals in Mekelle, North Ethiopia. J Hypertens 6: 239. doi:10.4172/2167-1095.1000239

Copyright: © 2017 Jufar AH, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License; which permits unrestricted use; distribution; and reproduction in any medium; provided the original author and source are credited.

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Abstract

Abstract Introduction: Hypertension is a prevalent and often asymptomatic chronic disease. Health related quality of life is emerging as an important outcome in hypertension. It can be adversely affected by hypertension itself and sideeffects of antihypertensive drugs. It is a multi-dimensional element of well-being affected by the physical, mental, emotional and social status of patients. The ability to identify indicators of poor health-related quality of life is crucial for both improving clinical care and determining targets of intervention for the prevention and treatment of disease. Objective: The aim of this study was to assess health related quality of life and identify associated factors. Methods: A cross sectional study was conducted to assess health related quality of life of hypertensive patient. A total of 243 hypertensive patients were included in the study. The study assessed the health related quality of life using a generic tool short form-36. Socio-demographic and clinical variables were used as explanatory variables. In the multivariate analysis the level of significance was set at p<0.05. Result: The current study revealed that a very similar physical component (64.83) and mental component (64.88) summary mean score. This study has also shown that health related quality of life was significantly influenced by marital status, level of education of the study participants, duration of hypertension, blood pressure status and presence of health complaints. Conclusion: Health related quality of life in hypertensive patients is still suboptimal. Because of the fact that, patient education and enhanced information can lead to better health related quality of life in hypertension patient, health care professionals should pay due emphasis in educating the patient about the importance of controlling their blood pressure.

Keywords

Health related quality of life; Hypertension short form-36; Blood pressure

Abbreviations

HRQOL: Health Related Quality of Life; BP: Blood Pressure; PCS: Physical Component Summary; MCS: Mental Component Summary

Introduction

The overall burden of hypertension related diseases is rapidly rising in the developing world [1]. Hypertension is a prevalent and often asymptomatic chronic disease. A systematic review of prevalence and associated factors in Ethiopia indicates the prevalence of hypertension in Ethiopia ranges from 0.8- 31.5% [2].

Despite effective medical therapy and evidence based treatment guidelines for managing high blood pressure, uncontrolled hypertension remains common [3,4]. Low antihypertensive medication adherence has been proposed as an important barrier to achieving hypertension control. Demographic, treatment, clinical and behavioural factors have been shown to be associated with medication adherence, and previous studies have indicated that psychosocial factors are important determinants of antihypertensive medication adherence in older adults [5-8]. Also, the low rate of controlled hypertension may be associated with worsened quality of life and a high incidence of adverse effects of blood-pressure-lowering drugs [9].

The concept quality of life refers to “the degree to which a person enjoy in the areas of being (who one is: physical being, psychological being, spiritual being), belonging (connections with one’s environments: physical belonging, social belonging, community belonging) and becoming (achieving personal goals, hopes, and aspirations: practical becoming, leisure becoming, growth becoming) the important possibilities of his or her life” [10]. It is a broad ranging concept affected in a complex way by the person’s physical health, psychological state, level of independence, social relationships, personal beliefs and their relationship to salient features of their environment [11].

Health related QOL (HRQOL) is emerging as an important outcome in hypertension. On the individual level, this includes physical and mental health perceptions and their correlates-including health risks and conditions, functional status, social support, and socioeconomic status. At the community level, HRQOL includes resources, conditions, policies, and practices that influence a population’s health perceptions and functional status [12]. HRQOL can be adversely affected by hypertension itself and side-effects of antihypertensive drugs [13]. It is often considered to be equally, if not more important than quantity of life. It is a multi-dimensional element of well-being affected by the physical, mental, emotional and social status of patients, which is increasingly used to assess the health status of the general public and patients, as well as the impact of health care interventions [14].

The assessment of HRQL is a particularly interesting endeavour in patients with hypertension as this condition is traditional risk factor for cardiovascular disease and therefore has a significant impact on the physical, social and mental domains that determine the patients’ overall well-being and status. Hypertension is highly correlated with other chronic diseases, such as diabetes and kidney disease [15]. Moreover, assessing HRQOL of Hypertension patients take accounts of their perceived physical and mental health and function which become an important component of health surveillance and are generally considered valid indicators of service needs and intervention outcomes [16]. In addition, the ability to identify indicators of poor healthrelated quality of life (HRQoL) is crucial for both improving clinical care and determining targets of intervention for the prevention and treatment of disease [12]. Furthermore, assessing health status also proved to be more powerful predictor of mortality and morbidity than many objective measures of health [17].

However, the impact of hypertension on individual’s physical and mental quality of life is less clear. We couldn’t find published article that addresses this issue in the country. Therefore, the aim of this study is to assess the HRQoL profile of the hypertensive patients, and to determine the socio-demographic and clinical characteristics associated with poor HRQoL.

Materials and Methods

Study area

The study was carried out in Mekelle town, a capital city of Tigray regional state, northern Ethiopia, which is located at 780 km from Addis Ababa, capital of Ethiopia. There are three general hospitals and one referral hospital, which provides a broad range of medical services to both in and out patients of all age groups.

Study design

An institution based cross sectional study design was employed.

Study population

All hypertensive patients on follow up at chronic clinics who met the inclusion criteria were included in the study.

Eligibility criteria and inclusion criteria

Patients with age 18 years and above.

Exclusion criteria

Patients who denied consent for the interview.

In-patients.

Sample size and sampling technique

Sample size calculation: Sample size was determined using data from a previous study, where the SD for HRQOL scores in hypertensive patients was 15.61 and assuming an alpha of 0.01 and a 2 tailed test with CI of 5 points. The total sample size was 255 [18].

Sampling technique: To get the number of patient to be taken from each hospital, proportionate allocation formula was employed. Patient’s card number was used as a sampling frame and individual patients were selected by using simple random sampling technique from each hospital.

Study variables

Dependent variable

HRQOL of hypertensive patients

Physical health component

Mental health component

Independent variable

Socio-demographic and clinical factors variables are shown in Table 1.

Socio demographic Clinical factors
Age
Gender Number of symptoms
Religion Duration of hypertension
Marital status Duration of hypertension
Number of children Blood pressure
Educational level Number of comorbidities
Monthly family income Number of antihypertensive drugs
Occupation History of admission
Distance from the hospital

Table 1: Independent variables.

Operational definition

Physical health subscales: Includes physical functioning, role limitations due to physical health problems, bodily pain, and general health perception.

Mental health subscales: Includes social functioning, role limitations due to emotional problems, mental health and vitality.

Low HRQOL: Because no previously established cut points for defining the scores are available, participants were categorized as having low HRQOL if their score is in the lowest tertile of the distribution for the current study population.

Data collection instrument

Health related quality of life was measured using a generic tool SF-36. The tool is comprised of 36 questions that measure four physical health subscales (physical functioning, role limitations due to physical health problems, bodily pain, and general health perception) and four mental health’s subscales (social functioning, role limitations due to emotional problems, mental health and vitality) and has previously been used to measure health related quality of life in similar populations.

Data collection procedure

Data were collected when the patient comes for follow up by using a pre tested structured questionnaire, and by reviewing patient chart. Patients were approached after they finished consultation with physician. Their socio demographic characteristics and clinical data were noted. The items were formulated in a manner that elicits the required data from the chart.

Data analysis procedure

Scores on each of the eight subscales were calculated. Subscales were weighted and aggregated to create PCS and MCS summary scores. Quantitative variables were expressed as mean and standard deviation. Qualitative variables were expressed as absolute numbers and percentages. Multivariate analysis was performed by constructing a model for each outcome. The HRQOL score was considered as outcome. Socio-demographic and clinical variables were used as explanatory variables and were considered a candidate for multivariate analysis when they had p values <0.20 in the bivariate analysis. In the multivariate analysis the level of significance was set at p<0.05.

Data quality management

An English version of SF-36 is adopted and was translated to Tigrigna and retranslated back into English. Four BSc nurse data collectors were trained ahead of the actual data collection period. The training was focused on familiarizing interviewers with the questionnaire and giving them the opportunity to practice using it. At time of data collection filled questionnaires were checked for completeness and consistency of information by the supervisor on daily basis and typographic errors were manually edited.

Ethical Consideration

Before the data collection, ethical clearance letter was obtained from ethical review committee of Mekelle University College of health science. Respondents were informed about the purpose of the study, and their oral consent was obtained. The respondents’ right to refuse or withdraw from participating in the interview was fully maintained and the information provided by each respondent was kept strictly confidential.

Results

Socio-demographic characteristics

Out of the total 255 study participants planned, 243 study participants were interviewed using structured questionnaires with a response rate 95.3%. From the 243 study participant 93 (38.3%) of them were male and 150 (61.7%) of them were female. The mean age of the participants was 55 years. Majority of the respondent 231 (95.1%) of them were orthodox followers followed by Muslim 8 (3.3%). Most, 223 (91.8%) of the participant were Tigray in their ethnicity. One hundred forty nine (61.3%) and 53 (21.8%) of subjects were married and widowed respectively. Regarding their educational status, 91 (37.9%) of them were illiterate and 43 (17.9%) were with diploma and above educational level. Majority of the participants 161 (66.3%) of them they can access health care with less than 1 hour time and for 82 (33.7%) of the participants more than one hour is needed to access treatment (Table 2).

Variable Category Frequency Percentage
age Less than 55 96 39.5
55 and above 147 60.5
sex male 93 38.3
female 150 61.7
Ethnicity Tigray 223 91.8
Amhara 19 7.8
Others 1 0.4
Religion Orthodox 231 95.1
Muslim 8 3.3
Protestant 4 1.6
Marital status Single 11 4.5
Married 149 61.3
Divorced 30 12.3
Widowed 53 21.8
Number of children Less than four 143 59.1
5 and above 100 40.9
occupation Government employee 45 18.5
Farmer 19 7.8
Daily laborer 17 7
Merchant 35 14.4
House wife 75 30.9
Student 4 1.6
Others 48 19.8
Level of education illiterate 91 37.9
Grade 1-6 29 12.1
Grade 7-12 77 32.1
Diploma and above 43 17.9
Family income Less than 500 70 29.4
500-1000 84 34.3
Above 1000 84 34.3
Distance Less than 1 hour 161 66.3
Greater than 1 hour 82 33.7

Table 2: Socio-demographic characteristics of the study participants (n=243), in government hospital, Mekelle, 2016.

Clinical factor

From the study participants, 96 (39.9%) of them knew they have hypertension less than one year period while 59 (24.3%) have been diagnosed for the last three years and above. 10 (4.1%), 11 (4.5%) of them have the complaint of swelling and kidney problem respectively. Majority of them, 156 (64.2%) took only one medication and 87 (35.8%) took two and more medication with frequency of 188 (77.4%) took once a day and 55 (22.6%) of them twice and more per day (Table 3).

Variable Category Frequency Percentage
Year since diagnosis Less than 1 year 96 39.9
1-2 year 46 18.9
2-3 year 41 16.9
Above 3years 59 24.3
Presence of any health complaint Yes 66 27.2
No 177 72.8
Number of drug One 156 64.2
Two and above 87 35.8
Frequency of drug Once 188 77.4
More than twice 55 22.6
BP status Controlled 72 29.6
  Uncontrolled 171 70.4
Previous history of admission Present 26 10.7
Absent 117 89.3
Co morbidity None 198 81.5
One or more 45 18.5

Table 3: Distribution of study participants by clinical characteristics (n=243), in government hospital, Mekelle, 2016.

Regarding type of medication, Enalapril was a part of treatment regimen for 98 (40.3%) of the study participant, next to Enalapril. Nifidipine (32.1%) and Hydrochlothiazide (32.1%) were drugs prescribed frequently (Table 4).

Type of drug Yes No
Freq  % Freq %
Frusemide 11 4.5 232 95.5
Hydrochlorothiazide 78 32.1 165 67.9
Nifidipine 78 32.1 165 67.9
Enalapril 98 40.3 145 59.7
Atenolol 6 2.5 237 97.5
Spironlactone 3 1.2 240 98.8

Table 4: Type and number of drugs study participants taking currently, government hospital, Mekelle, 2016.

Health related quality of life of hypertension patient

Using the generic tool SF-36 this study assessed the eight domain of HRQOL. Though the scores of all domains found to be above average, there is a marked difference between the eight domains.

The physical functioning and general health mean score were found to be little above average. The bodily pain mean score (87.77) was recorded to be the highest score from all physical and mental component domains. The current study revealed that a very similar physical component (64.83) and mental component (64.88) summary mean score. The mental health subscales mean score ranges from 53.2 9 (Vitality) to 78.86 (social functioning) (Table 5).

Domains Mean SD
Physical functioning 53.37 36.3
Role limitations due to physical problems 60.39 47.16
Bodily Pain 87.77 22.12
General Health 57.77 22.19
Social functioning 78.86 21.58
Role limitations due to emotional problems 61.73 46.97
vitality 53.29 19.21
Mental health 65.66 21.58
PCS 64.83 18.79
MCS 64.88 21.3
HRQOL 64.86 19

Table 5: Mean and standard deviation of study participant’s (HRQOL) domain score, (n=243), in government hospital, Mekelle, 2016.

Factors associated with HRQOL

To identify predictor variables, logistic regression has been done. At the beginning, the association of all independent variables with quality of life has been assessed using bivariate logistic regression. Among socio-demographic variables, age of the respondent, marital status, occupation, level of education, monthly family income and distance from health care facility were found to be associated with HRQOL (Table 6).

Variable Category HRQOL COR(CI) P-Value
Good Low
Age Less than 55 78 18 3.16 (1.7-5.8)  0
55 and above 85 62 1 0.69
Sex Male 61 32 0.89(0.52-1.55)  
Female 102 48 1 0.48
Ethnicity Tigray 151 72 1.40(0.55-3.57)  
Amhara and others 12 8 1 0.55
Religion Orthodox 154 77 0.67(017-2.53)  
Others 9 3 1  
Marital status Married 113 36 1 0.654
Single 9 2 1.43(0.3-6.94) 0.001
Divorced 13 17 0.24(0.11- 0.55) 0.002
Widowed 28 25 0.36(0.19-0.69) 0.04
Number of children Less than four 103 40 1.75(1.02-3.00)  
5 and above 59 40 1  
occupation Government employee 43 2 1 0.001
Farmer 11 8 0.06(0.01-0.35) 0.04
Daily laborer 13 4 0.15(0.03-0.92) 0.002
Merchant 22 13 0.08(0.01-0.38) 0.001
House wife 46 29 0.07(0.02-0.33) 0
Others 28 23 0.05(0.01-0.25)  
Level of education Illiterate 48 43 1 0.381
Grade 1-6 18 11 1.47(0.62-3.45) 0.014
Grade 7-12 55 22 2.24(1.18-4.26) 0
Diploma and above 40 3 11.94(3.45-41.41) 0.077
Family income Less than 500 46 24 0.52(0.26-1.07) 0.005
500-1000 49 35 0.38(0.19-0.75)  
Above 1000 66 18 1 0.044
Distance Less than 1 hour 115 46 1.77(1.02-3.09)  
Greater than 1 hour 48 34 1  

Table 6: Association of socio-demographic factors with HRQOL, government hospital, Mekelle, 2016.

Bivariate analysis also showed significant association between duration of hypertension, presence of health complaint, Blood pressure status and presence of co morbidity and HRQOL (Table 7).

Variable Category HRQOL COR P-Value
Good Low
Year since diagnosis Less than 2 year 92 51 0.46(0.22-0.95) 0.035
2-3 year 24 17 0.36(0.148-0.88) 0.024
Above 3years 47 12 1  
Presence of any health complaint Yes 33 33 1  
No 130 47 2.77(1.54-4.97) 0.001
Number of drug One 106 50 1.17(0.67-2.06) 0.566
Two and above 54 30 1  
Frequency Once 127 61 1.1(0.58-2.07) 0.77
BID or more 36 19 1  
BP status Controlled 59 13 2.92(1.49-5.74) 0.002
Uncontrolled 104 67 1  
Previous history of admission Present 15 11 1  
Absent 148 69 1.57(0.69-3.6) 0.28
Co morbidity None 139 59 2.06(1.07-3.99) 0.032
One or more 24 21 1  

Table 7: Association of clinical factors with HRQOL, government hospital, Mekelle, 2016.

Multivariate logistic regression was performed by constructing a model for HRQOL as an outcome variable. Socio-demographic and clinical variables were used as explanatory variables and considered when they had <0.2 P-values in bivariate analysis.

When assessing the effect of Socio-demographic factors on the HRQOL, it was revealed that HRQOL was significantly influenced by marital status and level of education of the study participants.

The findings of this study showed that those patients who got divorced had less chance (OR=0.21 CI=0.08-0.55) of having good quality of life compared to those who are married. Regarding level of education the current study demonstrated that those who are illiterate were found to have lower quality of life than those who completed at least grade 7 to 12(OR=3.25 CI=1.47-7.2) and have a college diploma and above(OR=23.1 CI=5.5-97.2). Regarding clinical factors, HRQOL was found to be influenced by, duration of hypertension, Presence of health complaint and blood pressure status.

The findings of this study showed a significant association between duration of hypertension and quality of life, in which the odds of good HRQOL was lower in those who were diagnosed with in the past three years compared with those who have known their diagnosis before 3 years.

On the topic of blood pressure status, our study revealed those participants who had controlled their blood pressure had 4.2 (OR=4.2 CI=4.2 (1.88-9.33) times higher chance of having good quality of life than those who didn’t control their blood pressure.

Based on the finding of the study, participants who had no health complaint like, paralysis of the limb, visual impairment, swelling/ edema and other had higher (OR=4.2) chance of having good quality of life than their counterpart (Table 8).

Variable Category HRQOL COR(CI) AOR (CI)
Good Low
Year since diagnosis Less than 2year 56 41 0.46(0.22-0.95) 0.4(0.16-0.97)
 2-3 year 24 17 0.36(0.148-0.88) 0.3(0.1-0.91)
Above 3years 47 12 1  
Level of education Illiterate 48 43 1  
Grade 1-6 18 11 1.47(0.62-3.45) 1.4(0.53-3.67)
Grade 7-12 55 22 2.24(1.18-4.26) 3.25(1.47-7.2)
Diploma and above 40 3 11.94(3.45-41.41) 23.1(5.5-97.2)
Presence of any health complaint Yes 33 33 1  
No 130 47 2.77(1.54-4.97) 4.22(2.03-8.75)
Marital Status Married 113 36 1 1
Single 9 2 1.43(0.3-6.94) 0.55(0.09-3.23)
Divorced 13 17 0.24(0.11- 0.55) 0.21(0.08-0.55)
Widowed 28 25 0.36(0.19-0.69) 0.71(0.33-1.52)
BP status Controlled 59 13 2.92(1.49-5.74) 4.2(1.88 -9.31)
Uncontrolled 104 67 1  

Table 8: Multivariate analyses show predictor variables of HRQOL, government hospital, Mekelle, 2016.

Discussion

For many chronic diseases like hypertension assessing Health related quality of life can help in evaluating the physical and psychosocial impact of these diseases on the affected population. It could be also used as important outcome measure for different therapeutic interventions (Figure 1).

hypertension-open-access-component

Figure 1: Physical and mental health component summary score of the study participants.

The SF- 36 scale is a generic instrument available in different language and had been used to assess quality of life in many chronic disease conditions.

In this study the physical health component summary mean score and mental health summary mean scored are 64.83 and 64.88 respectively. This finding is consistent with similar studies conducted in Nigeria and Brazil [18,19]. The lowest scores from the SF-36 domains were Physical function and vitality. The lower quality of life on this physical domain may be explained by the fact that the SF-36 scale is more associated with physical illness. In addition, the lower score in Vitality domain may be explained by lack of disposition and enthusiasm and because of the association of hypertension with symptoms such as headache, anxiety and the effects of antihypertensive drugs such as fatigue and sleep disorders.

In this study there is a positive association between educational level and quality of life. This finding agree with other similar studies conducted in Nigeria, Brazil and Pakistan which showed study participants with a higher educational level also had a higher HRQOL [18-20]. This association may be explained by the fact that education develops a level of interest and concern in patients related to improving their own health, which is a key determinant of successful medical treatment. In addition, it is a common observation that bettereducated people are less likely to develop complications to chronic conditions, or are often in the “controlled” status. In addition to pharmacotherapy, better-educated patients are more likely to adapt to life style modification and preventive measures which result in an improvement in HRQOL.

Regarding other Socio-demographic characteristics our study revealed a statistically significant association between marital status and quality of life. Those participants who got divorced had a lower chance of having good quality of life than those who were married. This finding is in not in accordance with many studies, which showed no significant association between these variables. But few studies showed an association between physical function domain and any of the eight domains respectively [19-21].

Evidence from this study showed a good HRQOL among participants who had no health complaint/symptoms. The finding is consistent with previous studies done in Nigeria and India which shows a positive correlation between number of symptoms and quality of life [22].

Our study found out that there is a positive association between duration of hypertension and quality of life, showing a good quality of life among participants who knew their diagnosis before 3 years. This is in disagreement between many studies which showed no statistically significant association between these variables [18,19,22-25].

The relationship between blood pressure status of the participant and HRQOL was also found to be statistically significant, in which participants having increasing/uncontrolled blood pressure were less likely to had good quality of life than their counterparts. The result is consistent with similar studies [18,21-25]. Even though patients with elevated blood pressure mostly have no physical symptoms but may have behavioural or emotional impairment which lowers their quality of life.

Conclusion

From the results of our study, HRQOL in hypertensive patients was still suboptimal. In this study we found that education, marital status had marked effect on HRQOL in hypertensive patients. HRQOL was significantly better in the group of hypertensive that had controlled blood pressure. Duration of hypertension, presence of health compliant were also found as major predictor of HRQOL among hypertension patient.

Acknowledgments

First of all we would like to thank Mekelle University College of health science for funding this project. Also we would like to appreciate health professional working in chronic follow up clinic at Ayder referral hospital, Mekelle hospital and Quiha hospital for their unreserved cooperation during data collection.

Finally, we would like to show our gratitude to all data collectors, facilitator and study participants involved in this study.

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