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BMC Research Notes

, 12:86 | Cite as

Prevalence and predictors of self care practices among hypertensive patients at Jimma University Specialized Hospital, Southwest Ethiopia: cross-sectional study

  • Busha Gamachu LabataEmail author
  • Muktar Beshir Ahmed
  • Ginenus Fekadu Mekonen
  • Fekede Bekele Daba
Open Access
Research note

Abstract

Objective

Hypertension is a major risk factor and precursor of myocardial infarction, chronic kidney disease, heart failure and premature death. These vascular events increased costs of hypertension management. Self-care Practices were recommended to control blood pressure among hypertensive patients. Therefore, the objective of this study is to assess predictors of self-care practices among hypertensive patients at Jimma University Specialized Hospital.

Results

A 341-hypertensive patients participated in the study. The mean age of the participants was 54.35 ± 12.48 years with range of 26 to 89 years. One hundred seventy-seven (51.9%) respondents were males and male to female ratio is 1.08. About 61.9% of respondents were adherent to medication usage and 30.5%, 44.9%, 88.3%, 93.5% and 56.9% of respondents were adherent to low salt diet, physical activity, non-alcohol drinking, nonsmoking and weight management respectively. Normal weight (AOR = 1.822, 95% CI 1.073–3.093) was independent predictor of medication usage whereas good self-efficacy (AOR = 2.584, 95% CI 1.477–4.521) and being female (AOR = 0.517, 95% CI 0.301–0.887) were independent predictor of low salt diet and physical activity respectively. Also being female (AOR = 3.626, 95% CI 1.211–10.851) was independent predictors of non-smoking.

Keywords

Hypertension Predictors Self-care practices 

Abbreviations

AOR

adjusted odds ratio

BP

blood pressure

DASH

dietary approaches to stop hypertension

ETB

Ethiopian Birr

H-SCALE

hypertension self-care activity level effects

JUSH

Jimma University Specialized Hospital

SCP (s)

self-care practice (s)

Introduction

Hypertension is a condition in which the blood vessels have persistently raised pressure and the average of two or more properly measured, seated blood pressure (BP) readings on each of two or more clinic visits is used [1]. Hypertension is a major risk factor and precursor of myocardial infarction, chronic kidney disease, heart failure and premature death. These vascular events increased costs of hypertension management [2].

About one-third of adults in the world have hypertension [3]. These are predicted to 1.56 billion by the year 2025 [4]. Ethiopian epidemiology of hypertension was not well studied. Nevertheless, in southwest Ethiopia, the overall prevalence of hypertension is 13.2% [5] while in Gondar city is 28.3% [6].

Self-care practices (SCPs) includes that the medication taking, non-smoking, weight management, low-sodium and low-fat diet, physical activity and moderate alcohol consumption [7]. Self-care is multidimensional as it relates to chronic disease management [8]. Adherences to SCPs were the similarity between recommended practice and actual practice [9].

Smoking cessation has immediate as well as long-term benefits for patients with hypertension, prevents cardiovascular disease and premature deaths [10, 11]. Similarly, reducing of dietary sodium intake less than 2400 mg/day and implementing dietary approaches to stop hypertension (DASH) through proper diet program like fruits and vegetables leads to reduce BP [10]. The literature studies revels that DASH diet reduced systolic BP by 8–14 mmHg, moderation of alcohol reduce systolic BP by 2–4 mmHg [12] and reduction in weight by 5–10 kg shows significant impact on systolic and diastolic BP [13]. WHO recommend at least 150 min of moderate-intensity aerobic physical activity throughout the week to lower BP [14, 15].

Patients who involved in SCPs benefit from the BP control, but adopting and maintaining SCPs for chronic disease management often require life-long practices, motivation and support [16]. Older age, female, self-efficacy and longer duration of hypertension were predictors of SCPs [16, 17]. Therefore, the objective of this study was to assess Predictors of SCPs among hypertensive patients on follow up at Jimma University Specialized Hospital (JUSH) ambulatory unit using adapted Hypertension Self-Care Activity Level Effects (H-SCALE) questionnaire [17].

Main text

Patients and methods

Study design and period

Hospital based cross-sectional study was conducted from April 4 to May 30, 2016.

Study population

Adult hypertensive patients on follow up in the ambulatory care unit of JUSH, and who were placed on treatment for more than 6 months were included in the study [18]. Patients unable to communicate and mentally ill were excluded from the study.

Sample size and sampling technique

Sample size was calculated using a single population proportion formula considering a 95% confidence level, margin of error (0.05), proportion of adherence with antihypertensive medication (P = 0.557) [19].
$${\text{n }} = \frac{{\left( {{\text{Z}}_{\alpha / 2} } \right)^{ 2} {\text{p }}\left( { 1- {\text{p}}} \right)}}{{{\text{d}}^{ 2} }}$$
The formula yields 380 hypertensive patients. Since the estimated total population of hypertensive patients was, less than 10,000 we used correction formula.
$${\text{nf}} = {{\text{n}} \mathord{\left/ {\vphantom {{\text{n}} {\left( {1 + \frac{{\text{n}}}{{\text{N}}}} \right)}}} \right. \kern-0pt} {\left( {1 + \frac{{\text{n}}}{{\text{N}}}} \right)}}$$
N = total targeted population on chronic follow up (2015).

Then the final sample size according to these equation yields 320 and adding 10% for nonresponse it becomes 352. Therefore, using patients’ card number 352 patients were recruited by simple random sampling technique from 2015 hypertensive patients and were interviewed after they re-fill their medication.

Data collection instrument

Sociodemographic, hypertension knowledge, and social support of patients’ data were obtained by structured questionnaire. Hypertension self-care practices were assessed by adapted H-SCALE questionnaire [17].

Ethical considerations

Approval for this study was obtained from the Institutional Review Board of Jimma University and JUSH clinical director in 2016. Written approval consent was obtained from literate participants and oral approval was considered in case of illiterate participants.

Operational definitions

Self-care practice: Is a framework for patient centred hypertension self-management and care.

Self-efficacy: A confidence in one‘s ability to participate in a given activities.

Medication adherence: Three items assessed the number of days in the last week that an individual takes medication, at recommended dosage and at same time. Responses were summed (range 0–21). Score = 21 were considered adherent.

Low-salt diet: six items assessed practices related to eating a healthy diet. A mean score is calculated. Scores of 6 or better were considered adherent.

Physical activity: Past 7 days physical activity of patients’ was assessed by 2 items. Responses were summed (range 0–14). Participants who scored ≥ 8 were adhering to physical activity.

Non-smoker: Respondents who reported 0 day smoking in the past 7 days.

Alcohol: Alcohol intake is assessed using 3-items. Participants who usually did not drink at all were considered abstainers.

Weight management: Seven items, strongly disagree (1) to strongly agree (5), assessed weight management. Responses were summed creating a range of scores from 7 to 35. Score ≥ 28 were considered adherent to weight management practices.

Social support: It was assessed with 12 questions and answers range from 12 to 60.

Range of 12–42 has low, 43–52 has medium and 53–60 has greater social support.

Knowledge: Assessed by 15 questions by giving 1 to correct answer and 0 to the wrong answer. Scores < 8 were taken as poor, 8–12 average, and 13–15 adequate knowledge of hypertension.

Urban residence: Patients who had town identification card.

Results

Characteristic of hypertensive patients

A total of 352 individuals were invited to participate in the study; out of them only 341 (96.88%) were fully responded. The mean age of the participants was 54.35 ± 12.48 years with range of 26 to 89 years. One hundred seventy-seven (51.9%) respondents were males. One hundred eighty-six (54.5%) were Muslim by religion and Oromo account 200 (58.7%). One hundred forty-nine (43.7%) were Illiterate. Married respondents account 279 (81.8%) and 182 (53.4%) live in Urban. One hundred twenty-two of respondents had estimated monthly income of 501–1500 Ethiopian birr (ETB). About 52% of respondents had medium social support. Two hundred thirty-seven (69.5%) of the participants were diagnosed to have hypertension before 3 years. Fifty-five (16.1%) of patients had diabetes as comorbid disease. Two hundred fifteen (63%) have normal weight whereas about 53 (15.5%) respondents self-rated their health as very good. Poor self-efficacy to manage hypertension accounts 70% of respondents (Table 1).
Table 1

Characteristic of hypertensive patients at Jimma University Specialized Hospital (n = 341)

Variables

Frequency (%)

Variables

Frequency (%)

Age

Ethnicity

19–39 years

42 (12.3)

Oromo

200 (58.7)

40–64 years

222 (65.1)

Amhara

51 (15)

65–89 years

77 (22.6)

Tigre

18 (5.3)

Gender

Guragie

26 (7.6)

Male

177 (51.9)

Dawuro

17 (5)

female

164 (48.1)

Kafa

17 (5)

Education

Yem

4 (1.2)

Tanbaro

3 (0.9)

Sulte

5 (1.5)

Illiterate

149 (43.7)

Average monthly income (ETB)

Read and write

35 (10.3)

< 500

61 (17.9)

Primary

80 (23.5)

501–1500

122 (35.8)

Secondary

43 (12.6)

1501–2500

82 (24)

College/above

34 (10)

2501–3500

38 (11.1)

Religion

> 3501

38 (11.1)

Muslim

186 (54.5)

Live alone

Orthodox

99 (29)

Yes

24 (7)

Protestant

55 (16.1)

No

317 (93)

Wakefata

1 (0.3)

Social support

Occupation

Low

114 (33.4)

House wife

82 (24)

Medium

177 (51.9)

Farmer

122 (35.8)

Greater

50 (14.7)

merchant

38 (11.1)

Marital status

Employed

47 (13.8)

Married

279 (81.8)

Retired

32 (9.4)

Single

2 (.6)

Daily laborer

7 (2)

Widow

46 (13.5)

House servant

9 (2.6)

Students

4 (1.2)

Place of residence

Divorced

14 (4.1)

Rural

159 (46.6)

BMI

Urban

182 (53.4)

16.3–18.499

22 (6.5)

Time since diagnosis of hypertension

18.5–24.99

215 (63)

< 3 years

104 (30.5)

25–29.9

92 (27)

≥ 3 years

237 (69.5)

≥ 30

12 (3.5)

self-reported Comorbidities

Self-rated health

Diabetes

55 (16.1)

Very good

53 (15.5)

Heart failure

20 (5.9)

Good

141 (41.3)

Kidney disease

26 (7.6)

Fair

113 (33.1)

Liver disease

2 (0.6)

Poor or very poor

34 (10)

Asthma

10 (2.9)

Self-efficacy

Retinopathy

5 (1.5)

Good

103 (30.2)

Neuropathy

3 (0.9)

Poor

238 (69.8)

Prevalence of self-care practices of hypertensive patients

Of the study participants; 61.9%, 30.5%, 44.9%, 93.5%, 88.3% and 56.9% were reported adherent to medication usage, low salt diet, physical activity, non-smoking, non-alcohol drinking and weight management practices respectively (Table 2).
Table 2

Self-care practices of hypertensive patients at Jimma University specialized hospital (n = 341)

Prevalence of self-care practices

Variables

Frequency (%)

Medication usage

Adherent

211 (61.9)

Non-adherent

130 (38.1)

Physical activity

Adherent

153 (44.9)

Non-adherent

188 (55.1)

Weight management

Adherent

194 (56.9)

Non-adherent

147 (43.1)

Low salt diet

Adherent

104 (30.5)

Non-adherent

237 (69.5)

Non Smoking

Adherent

319 (93.5)

Non-adherent

22 (6.5)

Moderate alcohol usage

Adherent

301 (88.3)

Non-adherent

40 (11.7)

Predictors of self-care practices

In bivariate logistic regression variables like younger age, female sex, normal weight, hypertension knowledge, self-efficacy, education, time since hypertension diagnosis and marital status were significantly associated with SCPs.

In multivariate logistic regression, normal weight patients were 1.82 times more likely to adhere medication usage practice than over weight respondents (AOR = 1.822, 95% CI 1.073–3.093). However, participants of poor self-efficacy (AOR = 0.407, 95% CI 0.227–0.730) were less likely to adhere medication usage than participants of good self-efficacy.

Participants who get greater social support were 2.81 times (AOR = 2.811, 95% CI 1.209–6.534) more likely adherent to low salt diet than their counterparts.

Female were 3.63 time more likely to non-smoking than male (AOR = 3.626, 95% CI 1.211–10.851).

Respondents having adequate knowledge of hypertension were 2.58 times more likely (AOR = 2.585, 95% CI 1.125–5.940) to adhere practicing physical activity. However, female (AOR = 0.517, 95% CI 0.301–0.887) respondents were less likely to adhere physical activity than male.

Normal weight respondents were 2.22 times more likely (AOR = 2.219, 95% CI 1.218–4.043) to practice weight management. Besides, having good self-efficacy were 2.60 times more likely (AOR = 2.584, 95% CI 1.411–4.731) to maintain their weight than poor self-efficacy (Table 3).
Table 3

Predictors of Self-care practices among hypertensive patients at Jimma University specialized Hospital

Variables

Medication usage

Univariate analysis

Multivariable analysis

Adherent

Non-adherent

P-value

COR (95% CI)

P-value

AOR (95% CI)

Age in years

19–39 years

32

10

0.022

2.667 (1.151–6.176)

0.064

2.455 (0.951–6.339)

40–64 years

137

85

0.270

1.343 (0.795–2.268)

0.380

1.300 (0.723–2.337)

≥ 65 years

42

35

1.0

1.0

1.0

1.0

Time of HTN diagnosis

< 3 years

74

30

0.020

1.800 (1.096–2.958)

0.092

1.605 (0.926–2.782)

≥ 3 years

137

100

1.0

1.0

1.0

1.0

BMI

16–18.49

14

8

0.360

1.559 (0.603–4.032)

0.098

2.396 (0.851–6.747)

18.5–24.9

142

73

0.024

1.733 (1.075–2.793)

0.026

1.822 (1.073–3.093)

≥ 25

55

49

1.0

1.0

1.0

1.0

Self-efficacy

Good

80

23

1.0

1.0

1.0

1.0

Poor

131

107

0.000

0.352 (0.207–0.598)

0.003

0.407 (0.227–0.730)

Variables

Low salt diet

Univariate analysis

Multivariable analysis

Adherent

Non–adherent

P–value

COR (95% CI)

P–value

AOR (95% CI)

Time of HTN diagnosis

< 3 years

40

64

0.035

1.689 (1.037–2.753)

0.050

1.752 (0.999–3.074)

≥ 3 years

64

173

1.0

1.0

1.0

1.0

Social support

Low

23

91

1.0

1.0

1.0

1.0

Medium

58

119

0.020

1.928 (1.107–3.358)

0.053

1.837 (0.992–3.401)

Greater

23

27

0.001

3.370 (1.640–6.925)

0.016

2.811 (1.209–6.534)

HTN knowledge

Poor

28

94

1.0

1.0

1.0

1.0

Average

55

127

0.164

1.454 (0.858–2.464)

0.313

1.345 (0.756–2.391)

Adequate

21

16

0.000

4.406 (2.029–9.567)

0.003

3.789 (1.575–9.114)

Self-efficacy

Good

49

54

0.001

3.019 (1.849–4.930)

0.001

2.584 (1.477–4.521)

Poor

55

183

1.0

1.0

1.0

1.0

Variables

Physical activity

Univariate analysis

Multivariable analysis

Adherent

Non-adherent

P-value

COR (95% CI)

P-value

AOR (95% CI)

Age in years

19–39 years

24

18

0.043

2.207 (1.026–4.745)

0.164

1.864 (0.775–4.480)

40–64 years

100

122

0.261

1.357 (0.797–2.308)

0.345

1.346 (0.726–2.495)

≥ 65 years

29

48

1.0

1.0

1.0

1.0

Sex

Male

93

84

1.0

1.0

1.0

1.0

Female

60

104

0.003

0.521 (0.338–0.804)

0.017

0.517 (0.301–0.887)

Education

Illiterate

47

102

1.0

1.0

1.0

1.0

Read and write

12

23

0.755

1.132 (0.520–2.467)

0.929

0.963 (0.422–2.200)

Primary

43

37

0.001

2.522 (1.442–4.411)

0.077

1.728 (0.942–3.170)

Secondary

29

14

0.000

4.495 (2.176–9.286)

0.002

3.301 (1.529–7.126)

College/above

22

12

0.001

3.979 (1.817–8.711)

0.172

1.912 (0.754–4.846)

Marital status

Married

135

144

1.0

1.0

1.0

1.0

Others

18

44

0.006

0.436 (0.240–0.792)

0.627

0.842 (0.420–1.686)

HTN knowledge

Poor

45

77

1.0

1.0

1.0

1.0

Average

84

98

0.110

1.467 (0.917–2.345)

0.288

1.320 (0.791–2.204)

Adequate

24

13

0.003

3.159 (1.465–6.813)

0.025

2.585 (1.125–5.940)

Self-efficacy

Good

60

43

0.001

2.176 (1.359–3.482)

0.097

1.567 (0.922–2.664)

Poor

93

145

1.0

1.0

1.0

1.0

Variables

Non-smoking

Univariate analysis

Multivariable analysis

Adherent

Non-adherent

P-value

COR (95% CI)

P-value

AOR (95% CI)

Sex

Male

160

17

1.0

1.0

1.0

1.0

Female

159

5

0.019

3.376 (1.217–9.379)

0.021

3.626 (1.21–10.851)

Self-rated health

Good-very good

190

4

0.001

6.628 (2.193–20.036)

0.012

4.482 (1.39–14.45)

Fair to poor

129

18

1.0

1.0

1.0

1.0

Social support

Low

103

13

1.0

1.0

1.0

1.0

Medium

170

7

0.019

3.126 (1.207–8.093)

0.148

2.246 (0.749–6.732)

Greater

48

2

0.148

3.089 (0.670–14.235)

0.524

1.730 (0.320–9.337)

Self-efficacy

Good

102

1

0.026

9.87 (1.310–74.399)

0.052

9.541 (0.98–92.752)

Poor

217

21

1.0

1.0

1.0

1.0

Variables

Non-alcohol usage

Univariate analysis

Multivariable analysis

Adherent

Non-adherent

P-value

COR (95% CI)

P-value

AOR (95% CI)

Education

Illiterate

131

18

1.0

1.0

1.0

1.0

Read and write

29

6

0.426

0.664 (0.242–1.819)

0.732

0.817 (0.267–2.250)

Primary

76

4

0.093

2.611 (0.852–7.999)

0.398

1.701 (0.496–5.835)

Secondary

38

5

0.936

1.044 (0.364–2.998)

0.900

1.081 (0.321–3.644)

College/above

27

7

0.198

0.530 (0.202–1.393)

0.036

0.239 (0.063–0.908)

Presence of DM

Yes

43

12

0.014

0.389 (0.184–0.823)

0.282

0.615 (0.254–1.491)

No

258

28

1.0

1.0

1.0

1.0

BMI

16–18.49

19

3

0.675

1.326 (0.354–4.959)

0.581

1.537 (0.334–7.061)

18.5–24.9

196

19

0.029

2.159 (1.080–4.316)

0.084

2.036 (0.909–4.561)

≥ 25

86

18

1.0

1.0

1.0

1.0

Self-rated health

Good-very good

178

16

0.024

2.171 (1.107–4.255)

0.198

1.638 (0.773–3.470)

Fair to poor

123

24

1.0

1.0

1.0

1.0

Variables

Weight management

Univariate analysis

Multivariable analysis

Adherent

Non-adherent

P-value

COR (95% CI)

P-value

AOR (95% CI)

Education

Illiterate

63

86

1.0

1.0

1.0

1.0

Read and write

21

14

0.061

2.048 (0.967–4.336)

0.095

2.099 (0.879–5.015)

Primary

49

31

0.007

2.158 (1.239–3.758)

0.258

1.467 (0.755–2.849)

Secondary

32

11

0.000

3.971 (1.860–8.476)

0.002

4.146 (1.65–10.405)

College/above

29

5

0.000

7.917 (2.903–21.591)

0.017

4.241 (1.289–13.96)

BMI

16–18.49

13

9

0.273

1.685 (0.663–4.285)

0.058

2.903 (0.964–8.742)

18.5–24.9

133

82

0.008

1.892 (1.178–3.039)

0.009

2.219 (1.218–4.043)

≥ 25

48

56

1.0

1.0

1.0

1.0

Social support

Low

38

76

1.0

1.0

1.0

1.0

Medium

118

59

0.000

4.000 (2.428–6.590)

0.000

4.050 (2.279–7.196)

Greater

38

12

0.000

6.333 (2.971–13.500)

0.000

6.694 (2.733–16.39)

HTN knowledge

Poor

60

62

1.0

1.0

1.0

1.0

Average

106

76

0.120

1.441 (0.909–2.286)

0.303

1.334 (0.771–2.305)

Adequate

28

9

0.006

3.215 (1.401–7.378)

0.011

3.524 (1.331–9.328)

Self-efficacy

Good

78

25

0.000

3.215 (1.956–5.504)

0.002

2.584 (1.411–4.731)

Poor

116

122

1.0

1.0

1.0

1.0

Discussion

Trials showed using SCPs in patients with hypertension have shown reduction in BP, cardiovascular events and total mortality [20].

In this study, the prevalence of SCPs of medication usage was 61.9%, which is similar to studies done in China in which 61.3% of the participants reported taking antihypertensive medications as prescribed [21]. However, this study result is lower than a study done in Tikur Anbessa; Ethiopia in which 69.2% were adherent to medication [22]. This difference might be due to educational variation as some of study participants were illiterate. However, our current result is higher than study done in Nigeria [23]. Normal weight patients adhere to medication use as compared to overweight patients, which is in line with a study done in metropolitan Charlotte area [24].

Importantly in this result, we found the prevalence of SCP of adherence to low salt diet was 30.5%, which is much lower than the study done in China [21]. This might be the daily consumption of salt per person is high in Ethiopia and most countries [25]. Participants who are less than 3 years since diagnosis to have hypertension were found to be independent predictor of low salt diet practice, which is not consistent with research done in china [21]. The possible reason might be patients unable to go through with diet regimen for long period, which is different from the other family members. In addition, participants with greater social support are independent predictor of self-care practice of low salt diet similar to a study done by Hu et al. [26]. Respondents who have adequate knowledge of hypertension adhere to low salt diet and this is in line with a study done in India [27].

In this study, the prevalence of SCP of adherence to physical activity was 44.9%, which is lower than study done in china were 51.9% of participants engage in physical exercise [21]. The main barriers in practicing physical activity were lack of desire and not convinced of the benefits [28]. Zinat Motlagh et al. [29] found 24.5% of hypertensive patients do physical activity, which is lower than our study. However, this study result is in line with a study done in Black Lion, Ethiopia [30]. Respondents who have secondary education practiced physical activity as compared to illiterate since they learnt benefit of physical activity at school. Female patients were less likely to involve in physical activities than males. This is not in line with the study done in China and Iran [21, 29]. In areas like ours, females are culturally made busy at home activities and they are responsible in making foods for their family.

Non-smoking practice was the most widely practiced SCP among hypertensive patients studied, which accounted for 93.5% respondents. This finding was found to be higher compared to a study done in China and India [21, 27]. This might be due to low prevalence of smoking habit in Ethiopia [31] and females were more likely to adhere to non-smoking practice in our study which is in line with a study done in China [21] and different from a study done in Iran [29]. Women are much less likely than men to report using smoking [32].

Non-alcohol use practice was the second most widely practiced SCP, which account for 88.3% of respondents that is higher than study done in china and India [21, 27]. The possible discrepancy may be low alcohol drinking prevalence and difficulty to afford daily expenditure of alcohol. However, this study is lower than study done in Iran because alcoholic drinks are banned in Iran. However, this finding is in line with a study done in Brazil were 88.7% of respondents adherent to non-alcohol drink [33].

More than half of respondents in this study, 56.9% were adherent to SCP of weight management which is higher than study done by Warren-Findlow and Seymour [17]. In addition, this study result is higher than a study done in Iran were 39.2% managed their weight [29]. Having good self-efficacy encouraged practicing weight management similar to a study done by Warren Findlow et al. [24].

Conclusion

Self-care practices of low salt diet (30.5%), physical activity (44.9%), medication usage (61.9%) and weight management (56.9%) were low whereas self-care practices of non-alcohol use and non-smoking were good. Self-efficacy was independent predictor of SCPs of low salt diet and weight management. Females were independent predictor of non-smoking.

Limitation

Recall bias may influence the result this study because data was gathered through a self-report questionnaire. It was difficult to assess the amount of salt intake of the patients.

Notes

Authors’ contributions

BGL was the principal investigator who conceived and designed the study; extracted, analyzed and interpreted the data and drafted the manuscript. FBD, MBA and GFM supervised the whole research, guided the conception and design of the study and assisted with interpretation of data and manuscript preparation. All authors read and approved the final manuscript.

Acknowledgements

We were thankful for the co-operation of all hypertensive patients who participated in this study for their sincere response and precious time. We would also like to thanks all data collectors.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethical clearance was obtained from the Institutional Review Board of Jimma University and JUSH clinical director in 2016. At hospital, patients were informed about the objective of study. Written approval consent was obtained from literate participants and oral approval was considered in case of illiterate participants. All patients were informed the right to out of the research. The data was handled with strong confidentiality.

Funding

There is no funding for this research. Busha Gamachu covered cost of data collection. Busha Gamachu designed the study, analysed data, interpreted data and involved in writing the manuscript.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.
    WHO. A Global brief on Hypertension. Silent killer, global public health crisis. 2013.Google Scholar
  2. 2.
    National Heart Foundation of Australia. Guideline for the diagnosis and management of hypertension in adults—2016. Melbourne: National Heart Foundation of Australia; 2016.Google Scholar
  3. 3.
    Weber MA, Schiffrin EL, White WB, Mann S, Lindholm LH, Kenerson JG, et al. Clinical practice guidelines for the management of hypertension in the community. A statement by the american society of hypertension and the international society of hypertension. J Clin Hypertens. 2013;16:1–13.Google Scholar
  4. 4.
    Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365:217–23.CrossRefGoogle Scholar
  5. 5.
    Michael Y, Gudina EK, Assegid S. Prevalence of hypertension and its risk factors in southwest Ethiopia: a hospital-based cross-sectional survey. Integr Blood Press Control. 2013;6:111–7.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Awoke A, Awoke T, Alemu S, Megabiaw B. Prevalence and associated factors of hypertension among adults in Gondar, Northwest Ethiopia: a community based cross-sectional study. BMC Cardiovasc Disord. 2012;12(113):2–7.Google Scholar
  7. 7.
    US Department of Health and Human Services. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. National Institutes of Health; 2004. (NIH Publication No. 04-5230).Google Scholar
  8. 8.
    Gohar F, Greenfield SM, Beevers DG, Lip GY, Jolly K. Self-care and adherence to medication: a survey in the hypertension outpatient clinic. BMC Complement Altern Med. 2008;8(4):1–9.Google Scholar
  9. 9.
    Han H-R, Lee H, Commodore-Mensah Y, Kim M. Development and validation of the hypertension self-care profile: a practical tool to measure hypertension self-care. J Cardiovasc Nurs. 2014;29(3):11–20.Google Scholar
  10. 10.
    Thayer C, Cohen A, Brock P, Dozois D, Haugen S, Mayfield R, et al. Hypertension diagnosis and treatment guideline. 2014. 1–19Google Scholar
  11. 11.
    Huang N, Duggan K, Harman J. Lifestyle management of hypertension. Aust Prescr. 2008;31:150–3.CrossRefGoogle Scholar
  12. 12.
    Seedat YK, Rayner BL, Veriava Y. South African hypertension practice guideline 2014. Cardiovasc J Afr. 2014;25(6):288–94.CrossRefGoogle Scholar
  13. 13.
    Azadbakht L, Mirmiran P, Esmaillzadeh A, Azizi F. Better dietary adherence and weight maintenance achieved by a long-term moderate fat diet. Br J Nutr. 2007;97:399–404.CrossRefGoogle Scholar
  14. 14.
    WHO. Global Recommendations on physical activity for health. Geneva: WHO; 2011.Google Scholar
  15. 15.
    Cornelissen VA, Buys R, Smart NA. Endurance exercise beneficially affects ambulatory blood pressure: a systematic review and meta-analysis. J Hypertens. 2013;31:639–48.CrossRefGoogle Scholar
  16. 16.
    Lee J, Han H, Song H, Kim J, Kim KB, Ryu JP, et al. Correlates of self-care behaviors for managing hypertension among Korean Americans: a questionnaire survey. Int J Nurs Stud. 2010;47(4):411–7.CrossRefGoogle Scholar
  17. 17.
    Warren-Findlow J, Seymour B. Prevalence rates of hypertension self-care activities among African Americans. J Natl Med Assoc. 2011;103(6):503–12.CrossRefGoogle Scholar
  18. 18.
    Ali MA, Bekele ML, Teklay G. Antihypertensive medication non-adherence and its determinants among patients on follow up in public hospitals in Northern Ethiopia. Int J Clin Trials. 2014;1(3):95–104.CrossRefGoogle Scholar
  19. 19.
    Girma F, Emishaw S, Alemseged F, Mekonnen A. Compliance with anti-hypertensive treatment and associated factors among hypertensive patients on follow-up in Jimma University Specialized Hospital, Jimma, South West Ethiopia: a quantitative cross-sectional study. J Hypertens. 2014;3(5):174.  https://doi.org/10.4172/2167-1095.1000174.CrossRefGoogle Scholar
  20. 20.
    Eriksson MK, Franks PW, Eliasson M. A 3-year randomized trial of lifestyle intervention for cardiovascular risk reduction in the primary care setting: the Swedish Bjorknas study. PLoS ONE. 2009;4(4):1–15.CrossRefGoogle Scholar
  21. 21.
    Hu H, Li G, Arao T. Prevalence rates of self-care behaviors and related factors in a rural hypertension population: a questionnaire survey. Int J Hypertens. 2013;2013:1–8.CrossRefGoogle Scholar
  22. 22.
    Hareri HA, Abebe M. Assessments of adherence to hypertension medications and associated factors among patients attending Tikur Anbessa Specialized Hospital Renal Unit, Addis Ababa, Ethiopia 2012. Int J Nurs Sci. 2013;3(1):1–6.Google Scholar
  23. 23.
    Ajayi EA, Adeoti AO, Ajayi IA, Ajayi AO, Adeyeye VO. Adherence to antihypertensive medications and some of its clinical implications in patients seen at a tertiary hospital in Nigeria. IOSR J Dent Med Sci. 2013;8(4):36–40.CrossRefGoogle Scholar
  24. 24.
    Warren-findlow J, Huber LRB, Seymour RB. The association between self-efficacy and hypertension self care activities among African American Adults. J Community Heal. 2012;37(1):15–24.CrossRefGoogle Scholar
  25. 25.
    WHO. Sodium intakes around the world. Geneva: World Health Organization; 2007.Google Scholar
  26. 26.
    Hu HH, Li G, Arao T. The association of family social support, depression, anxiety and self-efficacy with specific hypertension self-care behaviours in Chinese local community. J Hum Hypertens. 2015;29:198–203.CrossRefGoogle Scholar
  27. 27.
    Durai V, Muthuthandavan AR. Knowledge and practice on lifestyle modifications among males with hypertension. Indian J Comm Heal. 2015;27(1):143–9.Google Scholar
  28. 28.
    Alsairafi M, Alshamali K, Al-rashed A. Effect of physical activity on controlling blood pressure among hypertensive patients from Mishref Area of Kuwait. Eur J Gen Med. 2010;7(4):377–84.CrossRefGoogle Scholar
  29. 29.
    Zinat Motlagh SF, Chaman R, Sadeghi E, Eslami AA. Self-care behaviors and related factors in hypertensive patients. Iran Red Crescent Med J. 2016;18(6):1–10.CrossRefGoogle Scholar
  30. 30.
    Hareri HA, Abebe M, Asefaw T. Assessment of adherence to hypertesion managements and its influencing factors among hypertensive patients attending Black lion hospital chronic follow up unit, Addis Ababa, Ethiopia—a cross-sectional study. Int J Pharm Sci Res. 2013;4(3):1086–95.Google Scholar
  31. 31.
    Central Statistical Agency [Ethiopia] and ICF International. Ethiopia demographic and health survey 2011. Addis Ababa: Central Statistical Agency and ICF International; 2012.Google Scholar
  32. 32.
    Ansara, Donna L., Fred Arnold, Sunita Kishor, Jason Hsia, and Rachel Kaufmann. 2013. Tobacco Use by Men and Women in 49 Countries with Demographic and Health Surveys. DHS Comparative Reports No. 31. Calverton, Maryland, USA: ICF International.Google Scholar
  33. 33.
    Mendes C, Souza T, Felipe G, Lima F, Miranda M. Self-care comparison of hypertensive patients in primary and secondary health care services. Acta Paul Enferm. 2015;28(6):580–6.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Busha Gamachu Labata
    • 1
    Email author
  • Muktar Beshir Ahmed
    • 2
  • Ginenus Fekadu Mekonen
    • 1
  • Fekede Bekele Daba
    • 3
  1. 1.Pharmacy DepartmentWollega UniversityNekemteEthiopia
  2. 2.Department of EpidemiologyJimma UniversityJimmaEthiopia
  3. 3.Pharmacy DepartmentJimma UniversityJimmaEthiopia

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