Undiagnosed Hypertension and Associated Factors among Adult Dwellers in Hawela Tula Sub City, Hawassa, Southern Ethiopia: A Community Based Cross-sectional Study

DOI: https://doi.org/10.21203/rs.2.15583/v1

Abstract

Introduction Hypertension is a common public health problem and often goes unnoticed and can lead to a stroke or heart attack. It contributes to the high burden of cardiovascular disease, premature mortality, reduced quality of life and high costs to the health care system, especially in low and middle-income countries. Therefore, this study aimed to assess the prevalence of undiagnosed hypertension and influencing factors with health-seeking behaviour.Method A community-based cross-sectional study was conducted on 390 randomly selected adults in Hawela Tulla Sub-city, Hawassa, southern Ethiopia from February to June, 2019. Data was collected by pre-tested questionnaires and physical measurements of weight, height and blood pressure were collected through standardized procedures adapted from WHO STEPS survey tools. Data entry and analyzed for descriptive and logistic regression models by SPSS v.23. The result declared as statistically significant at p < 0.05.Result The prevalence of the undiagnosed hypertension among the respondents was 12.3%. The male [AOR= 3.70, 95% CI:1.64-8.32] than female contributing. Family history of hypertension had [AOR 3.69, 95% CI: 1.31-10.34], being physical inactive [AOR 3.21, 95% CI: 1.50- 6.84], salty food consumer [AOR 3.67, 95% CI:1.26-10.64], BMI 25 Kg/m2 and above [AOR 3.06, 95% CI:1.41-6.65] and not seek health care for some early hypertensive symptoms without serious illness [AOR 4.58, 95% CI: 1.85-11.32] when compared to their counterparts, were found to be determinant factors for undiagnosed hypertension.Conclusions and Recommendation The prevalence of undiagnosed hypertension found to be prevalent and calls for intervention. Health officials need to consider integrating the prevention and control of hypertension at the community level. The clinicians need to intervene on unhealthy lifestyles, by promoting healthy practices and health-seeking behavior to prevent undiagnosed hypertension.

Background

Hypertension already affects one billion people worldwide, leading to heart attacks and strokes [1]. It rarely manifests symptoms in the early stages and many people remain undiagnosed and invisible killer that rarely causes symptoms that may be late to successfully control their illness over the long term [2].

Elevated BP is the leading contributor to premature death, accounting for almost 10 million deaths in 2015, 4.9 million due to ischaemic heart disease and 3.5 million due to stroke [3]. The prevalence of hypertension in Africa 46% among WHO regions [4], 25% is the percentage of deaths under 60 that are attributable to hypertension in Africa [5]. The majority of African countries cannot afford the high costs of treatment with many other competing health priorities and limited resources [6].

Ethiopia as a developing country, there are economic development, industrialization, nutrition transition and globalization that lead to a rapid change in lifestyles that paramount the risk of hypertension [7]. However, WHO is working hard to achieve SDG target 3.4 to reduce by one- third premature mortality from NCDs through prevention and treatment at 2030 [8]. There was a high prevalence of hypertension probably indicating a hidden epidemic in this community [9]. The study reports of Ethiopia NCD STEPS, 2016 indicate that 76.6% of the total population never been measured for blood pressure per year. Some studies indicate there was a high prevalence of undiagnosed hypertension among working-age groups that were major health problem which requires urgent action [7, 10]. There is a gap in recording and reporting, no study reports show that undiagnosed hypertension in the study area. This study indicates there are hidden epidemics of undiagnosed hypertension, which associated with a sedentary lifestyle, dietary, and not seeking modern health care. This is important for researchers, clinicians, and health planners.

Methods

The source population was all resident households of 4 urban and 8 rural kebele city (the smallest administrative units in Ethiopia) dwellers in Hawela Tula sub-city. While all randomly selected adults from selected households in urban and rural kebele at Hawela Tula sub-city of Hawassa city administration during the study period was the study population. The study was conducted on 390 calculated by a single population proportion formula and 10% possible non-response rate. A multistage random sampling technique. In the first stage, five out of 12 kebeles were selected by simple random sampling technique. In the second stage, the sample size was proportionally allocated. In the last stage, only one random selected eligible person was interviewed. The age of 18 years or older adults and had no visit to any health facility in 12 last months for BP check before the study period was included. All adults who, are unable to be interviewed, apparently with the history of any major illness, known hypertensive, who are taking anti-hypertensive treatment, pregnant women were excluded from the study.

Data collection method and instruments

Data were collected by pre- tested structured questionnaires and physical measurements of weight, height and blood pressure were collected through standardized procedures adapted from a modified WHO STEPwise approach to surveillance- Instrument v.3.1 [11]. The questionnaire was pretested on 5% of the study participants found outside of the study area and modifications were made based on the findings. Data collectors were five clinical nurses supervised by investigators. Training and practical demonstrations on interview techniques and measurement procedures were given to data collectors for two consecutive days assessed for competency.

Data entry, cleaning, and analysis were done by SPSS V. 23. All factors with a p-value <0.2 in the bivariate logistic regression analysis were a candidate to the multivariable model to control confounding effects. The Hosmer -Lemeshow goodness-of-fit statistic was used to assess whether the necessary assumptions for the application of multiple logistic regression are fulfilled. Odds ratios (OR) with 95% confidence intervals (CI) were calculated. Finally, p-value <0.05 declared a significant association.

Ethical clearance was obtained from Hawassa university college of medicine and health sciences ethical review committee, support letter was also requested from the SNNPR, Hawassa city & Hawela Tulla Sub-city health bureau. All participants informed well about purpose, risk and benefit, and confidentiality. Participation was fully voluntary and written informed consent (verbal consent for who cannot read and write respondent) was obtained from each participant.

Terms and definitions

Undiagnosed hypertension: was defined as SBP 140 mmHg and above, and/or DBP  90 mmHg and above, without previous history or anti-hypertensive treatment during survey diagnosis [12].

Physical inactivity– Who involved in combination of moderate and vigorous activities for less than 10 min/day, or 30 min and above of moderate dynamic exercise on 5–7 days per week [13].

BMI interpretation: overweight/obesity - a body mass index (BMI) 25.0 kg/m2 and above.

Harmful alcohol use: who had consumed alcohol consumption more than 14 units/week for men and more than 8 units/week for women in the last 12 months. Unit of alcohol = vol (in ml) X % alcohol/ 1000. For local alcoholic beverages: Tella (4%), Tej (10%) and arake (40-45%) alcohol content, (as Glass 250ml and bottle as 330ml) [12].

Cigarette smokers: who had used cigarette smokers form of tobacco in the last 30 days [14].

Low consumption of fruits and vegetables: Fewer than 5 servings of fruit and/or vegetables per day [7]. (1serving =one orange/apple/banana or three tablespoons of cooked vegetables).

Results

A total of 383 participants (aged 19-61 years, with the mean (±SD) age of 33.48 (±10.30) were interviewed yielding a response rate of 98.21%. Nearly half of the studied participants 196 (51.2%) were male and 191(49.9%) in the age category of 30–49 years old. The majority of 320 (83.6%) were married and 258 (67.4%) were rural resident. Regarding ot educational stus, 56 (14.6%) have no formal education and 177 (46.2%) had a primary school, while only 150 (39.2%) had high school and above education. The occupation of the participants 137 (35.8%) were farmer and 144 (37.6%) were employed. The monthly income of the households, 182 (47.5%) earned between 450 - 1920 ETB, and 201 (52.5%) earned more than 1920 ETB (Table 1).

Behavioral related characteristics

From the total study participants, 27 (7.0%) were use any tobacco products, among this 14 (3.7%) were current cigarette smokers. The prevalence of Khat chewing was 48 (12.5%), among this 16 (33.3%) were chew daily. Regarding to alcohol consumption, 71 (18.5%) were ever drunk alcohol, 63 (16.4%) were currently drinking alcohol (last 30 days). Their favourate alcohol was maily locally prepared and reported as, 25 (39.7%) drink Tejji, 21 (33.3%) drink Beer, 9 (14.3%) Areke and other local drinks and 8 (12.7%) Wine. The prevalence of harmful alcohol consumption was calculated as 37 (9.7%) among adults (Fig 1).

Physical Activities

The vigorous activities ≥10 minute/day, 115 (30.0%) sawing hardwood, 177 (46.2) ploughing, 26 (6.8%) playing football and 10 (2.6%) weight lifting >20kg as daily physical activities. The study participants involved in moderate activities atleast 10 minute/day were mainly 72 (18.8%) washing clothes by hand, 126 (32.9%) drawing (Fetching) water and 281 (73.4%) walking. The prevalence of sedentary life style or physically inactive was 148 (38.6%) (Table 2).

Dietary Practice and BMI of respondents

The two-third 298 (77.8%) of the participants eat foods containing oil and fat, regularly, whereas, 360 (94.0%) were consume vegetables. The majority of 366 (95.6%) were consume <5 servings of fruit and/or vegetables on average/day. The prevalence of overweight/obesity was 84 (21.9%).

Health seeking behaviour

The majority, 357 (93.2%) were ever had BP measurement. Regarding to risk of hypertension, 106 (27.7%) consuming high salt, and 40 (10.4%) alcoholism and fat were mainly identfied as a risk for getting hypertension. The study participants who did not know about hypertension, 152 (39.7%) symptoms, 123 (32.1%) prevention options and 160 (41.8%) complication of hypertension. Only 108 (28.2%) had agree to seek health care for some hypertensive symptoms without serious illness. The main reasons for not seeking health, 103 (35.8%) due to shortage of money and 126 (43.8%) illness was not severe.

Prevalence of Undiagnosed Hypertension

The prevalence of undiagnosed hypertension was 47 (12.3%) at 95% CI (9.3, 15.8). out of this 24 (51.1%) were only systolic and 23 (48.9%) were both systolic & diastolic hypertension (Fig 2).

Associated Factors for Undiagnosed Hypertension

In the multivariate analysis sex of respondent, occupation, family history of hypertension, physical inactive, consume high salty food, BMI (Kg/m2) and health seeking behaviour were remains as determinant for prevalence of undiagnosed hypertension. Regarding to the modifiyable risk factors, the study participants who were physical inactive was approximtely 3 times more likely exposed to had undiagnosed hypertension with [AOR 3.21, 95% CI: 1.50, 6.84] than compared with more physical active. More salty food consumer [AOR 3.67, 95% CI:1.26, 10.64], BMI 25 Kg/m2 and above or over weight/obesity had about 3 times more exposed to develop undiagnosed hypertension with [AOR 3.06, 95% CI: 1.41, 6.65] when compared to their counterparts. The prevalence of undiagnosed hypertension was high among who are not seek health care for some early hypertensive symptoms without serious illness with [AOR 4.58, 95% CI: 1.85, 11.32] when compared to who seek earlier (Table 3).

Discussion

This population-based cross-sectional study revealed that, the prevalence of undiagnosed hypertension was 12.3%, [95% CI: 9.3-15.8] among study population. This study result was consistent with the study findings in Gulele sub-city, Addis Ababa city, Ethiopia reported (13.25%)  [15] and in Gondar city, North-West Ethiopia (10.47%)  [9]. Another study from Vietnam reported (14.1%) [16], India (10.1%) [7], 10.0% in North Indian state of Punjab [17].  

This study result slightly lower when compared with the study conducted in Bedele Town, Southwest Ethiopia (16.9% ) [18], and in Aksum town, northern Ethiopia (16.5% ) [19] and in Addis Ababa, Ethiopia (25%) [20]. Onother hand, it was higher from Gilgel Gibe (7.5%) [21] and Durame Town, Southern Ethiopia (8.96%) [22]. This discrepancy may due to this study is considered majorly urban setting whereas the former studies not included urban and rural settings and other difference on study population in socio demographic difference like: the age difference in the study population more than 18 included on this study while other studies included adult population aged above 30 year.

The male participants were more likely to had undiagnosed hypertension than female contributing. Which was similar with study conducted in North India [17] and  Durame Town [22]. This may due to related with ability to afford fatty food, sugar, cigarette smoking, alcohol and being physical inactivity due to utilization of vehcle. The prevalence of undiagnosed hypertension was high among adults who had family history of hypertension. This result inline with study report from Jigjiga city of eastern Ethiopia [23], and Gondar, Northwest Ethiopia [9]. This may due to variability in blood pressure might explained by genetic factors. Physical inactive study participants were more likely exposed to had undiagnosed hypertension. This was consistent with study findings from Gondar city in Ethiopia [24], Addis Ababa Ethiopia [25] and Kerala, India [26]. This may due to rapid growth of urbanization, in urban areas using taxis, motor cycles to move from place to place may affect the mobilization of dwellers.

The prevalence of undiagnosed hypertension was high among more salty food consumer than their counterpart. This study result inline with North India [17] and in Jigjiga city of eastern Ethiopia [23]. This agreement may due to high salt containing foods increase high absorption of water and increase blood volume that responsible for high blood pressure. Being over weight/obesity was more likely exposed to develop undiagnosed hypertension when compared to their counterparts. This was agree with study findings from Gondar city in Ethiopia [24], Durame Town, Southern Ethiopia [22], Addis Ababa Ethiopia [27] and Kerala, India [26]. The prevalence of undiagnosed hypertension was high among not seek health care for some early hypertensive symptoms. This was consistent with study findings from south India [28] and Nairobi Kenya [29] states failure to seeking health services increase prevalence of undiagnosed hypertension. This may due to seek health care for some hypertensive symptoms without serious illness not common due to lack of money, health related information about prevention, early symptoms and health benefits of early modern health care seeking benefit.

Despite to other study findings, there was no another socio demographic and other behaviour al factors had statistically significant association with undiagnosed hypertension on this study. This may be due to the minimum prevalence of these factors in the community studied.

This study result shows there was high prevalence of undetected hypertension among adults in selected house hold at Hawela Tulla Sub-city. Which related to occurred irrespective of the income status and due to low level of health seeking behaviour of the study participants. This study findings suggest for we need more attention on different strategies to address early detection for better prevention, evaluation, and management of high blood pressure in adults.

This study has potential limitations as the study is cross-sectional in design; it neither represents seasonal variation of nutritional outcomes nor establishes causal relationship. There was no pregnancy test for to female participants and early pregnancy that can not be noticed by participants and data collectors was difficult to differentiate. For harmful alcohol consumption calculation majority reports maily locally prepared alcohol and which was hard to estimate the concentration.

Conclusions

This study result shows there was high prevalence of undiagnosed hypertension when compared with other studies and indicates there is hidden epidemic in this population. Being male, having family history of hypertension, being physically inactive, high salty food consumption, and over weight/obesity and not seeking modern health care for some hypertensive symptoms without serious illness were associated with undiagnosed hypertension and statistically significant when compared to their counterparts.

Abbreviations

DBP= Diastolic Blood Pressure, ETB= Ethiopian Birr, FDRE= Federal Democratic Republic of Ethiopia, mmHg= Millimeters of Mercury, NCDs= Non-Communicable Diseases, SBP= Systolic Blood Pressure, SNNP= Southern Nations, Nationalities, and People, SPSS= Statistical Package for Social Science, WHO= World Health Organization

Declarations

Consent for publication

Not applicable.

Availability of data and materials

There is no remaining data and materials, all information is clearly presented in the main manuscript.

Competing interests

The authors declare that they have no conflict of interests.

Funding

No funding was obtained.

Authors’ contributions

DW wrote the proposal, participated in data collection, analyzed the data and drafted the paper. EM and DG approved the proposal with some revisions, participated in data collection, analysis and manuscript writing. authors read and approved the final manuscript. 

Acknowledgements

The authors would like to thank Hawassa University, College of Medicine and Health Science for ethical approival. We would like to thanks to Hawassa city administration health bureau and Hawela Tula sub city for their cooperation on providing, material support, information and support letter. The authors are also grateful to the all data collectors and study participants for their valuable contribution.

References

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Tables

Table 1: Socio-demographic characteristics of the study participants among adults in Hawela Tulla Sub-city, Hawassa, southern Ethiopia, 2019.

 

Category

No.

(%)

Sex

 

Male

187

(48.8)

Female

196

(51.2)

Age

 

18–29 years

155

(40.5)

30–49 years

191

(49.9)

≥ 50 years

37

(9.7)

Marital status

 

Married

320

(83.6)

Single

44

(11.5)

Divorce

14

(3.7)

Widow

5

(1.3)

Address

 

Urban

125

(32.6)

Rural

258

(67.4)

Educational level

 

No formal education

57

(14.9)

primary school

178

(46.5)

High school and above

148

(38.6)

Occupation

 

Farmer

137

(35.8)

Non-employed

102

(26.6)

Employed

144

(37.6)

Household income in Ethiopian Birr

 

450 - 1920

182

(47.5)

> 1920

201

(52.5)

NB: Employed (government, NGO, Private), Income: based on (HCE, 2016) Exchange rate 1 USD to 29.3673ETB

 

Table 2: Daily physical activities among adults in selected house hold at Hawela Tulla Sub-city, Hawassa, southern Ethiopia, 2019.

 

 

Activities

No

≤ 10 min

> 10 min

No.

(%)

No.

(%)

No.

(%)

Vigorous activities

 

Sawing hardwood

205

(53.5)

63

(16.4)

115

(30.0)

Ploughing

206

(53.8)

0

(.0)

177

(46.2)

Playing football

357

(93.2)

0

(.0)

26

(6.8)

Weight lifting(>20kg)

324

(84.6)

49

(12.8)

10

(2.6)

Moderate activities

 

Gardening

296

(77.3)

67

(17.5)

20

(5.2)

Washing clothes by hand,

281

(73.4)

30

(7.8)

72

(18.8)

Drawing (Fetching) water

241

(62.9)

16

(4.2)

126

(32.9)

Walking

0

(.0)

102

(26.6)

281

(73.4)

Riding pedal bicycle

305

(79.6)

27

(7.0)

51

(13.3)

 

Table 3: Bivariable and multivariable logistic regression analysis for prevalence of undiagnosed hypertension among adults in Hawela Tulla Sub-city, Hawassa, south Ethiopia, 2019.

 

Undiagnosed Hypertension

 

 

 

Yes

No

 

 

 

No. (%]

No. (%)

COR (95% CI]

AOR (95% CI]

P-Value

Sex

 

Female

17

(8.6)

180

(91.4)

1

1

 

Male

30

(16.1)

156

(83.9)

2.04(1.08, 3.83)

3.70(1.64, 8.32)

0.002*

Age in years

 

18–29

12

(7.7)

143

(92.3)

1

1

 

30–49

28

(14.7)

163

(85.3)

2.05(1.00, 4.174)

2.04(0.89, 4.70)

0.093

50 and above

7

(18.9)

30

(81.1)

2.78(1.01, 7.65)

2.66(0.82, 8.64)

0.105

Educational level

 

No formal education

12

(21.1)

45

(78.9)

2.55(1.10, 5.92)

2.50(0.76, 8.29)

0.133

primary school

21

(11.8)

157

(88.2)

1.28(0.63, 2.62)

1.16(0.44, 3.03)

0.766

High school & above

14

(9.5)

134

(90.5)

1

1

 

Occupation

 

Farmer

12

(8.8)

125

(91.2)

1

1

 

Non-employed

11

(10.8)

91

(89.2)

1.26(0.53, 2.98)

1.18(0.41, 3.37)

0.760

Employed

24

(16.7)

120

(83.3)

2.08(1.00, 4.35)

1.76(0.60, 5.20)

0.305

Family history of Hypertension

 

No

36

(10.5)

306

(89.5)

1

1

 

Yes

11

(26.8)

30

(73.2)

3.12(1.44, 6.75)

3.69(1.31, 10.34)

0.014*

Current cigarette smokers

 

No

43

(11.7)

326

(88.3)

1

1

 

Yes

4

(28.6)

10

(71.4)

3.03(0.91, 10.09)

2.19(0.49, 9.89)

0.308

Harmful alcohol use

 

No

35

(10.1)

311

(89.9)

1

1

 

Yes

12

(32.4)

25

(67.6)

4.27(1.97, 9.23)

2.62(0.95, 7.21)

0.062

Physical inactive

 

No

18

(7.7)

217

(92.3)

1

1

 

Yes

29

(19.6)

119

(80.4)

2.94(1.57, 5.51)

3.21(1.50, 6.84)

0.003*

Less than five servings of fruit and/or vegetables on average per day

 

No

42

(11.5)

324

(88.5)

1

1

 

Yes

5

(29.4)

12

(70.6)

3.21(1.08, 9.58)

2.58(0.61, 10.86)

0.197

Consume more salty food

 

No

5

(5.3)

90

(94.7)

1

1

 

Yes

42

(14.6)

246

(85.4)

3.07(1.18, 8.01)

3.67(1.26, 10.64)

0.017*

BMI (Kg/m2)

 

< 25

27

(9.0)

272

(91.0)

1

1

 

25 and above

20

(23.8)

64

(76.2)

3.15(1.66, 5.97)

3.06(1.41, 6.65)

0.005*

Seek health care for early symptoms

 

Yes

11

(7.6)

133

(92.4)

1

1

 

 

No

36

(15.1)

203

(84.9)

2.14(1.05, 4.36)

4.58(1.85, 11.32)

0.001*

NB: * statistically significant on multivariate analysis p-value (<0.05), COR: crude odds ratio, AOR: adjusted odds ratio, CI: confidence interval, 1: reference, Un-employed (Self-employed, Merchant, Unemployed (Un/able to work).