Prevalence of Pre-Hypertension/Hypertension and Its Associated Factors Among Adults in the Wolaita Zone of Southern Ethiopia: A Cross-Sectional Study

Abstract

Preventing the development of high blood pressure and resulting complication requires estimating the prevalence of prehypertension/hypertension and identifying associated risk factors. Information about pre-hypertension/hypertension in Ethiopia, especially in the southern region, is scarce, and limited knowledge exists regarding the prevalence and risk factors associated with pre-hypertension/hypertension. Objective of this study was to assess prevalence of pre-hypertension/hypertension and its associated factors among adults in Wolaita Zone of Southern Ethiopia, 2023. This cross-sectional study was conducted among adults attending outpatient departments in governmental hospitals in South Ethiopia in 2023. Face-to-face interviews were used to gather information on sociodemographic data, dietary and behavioral patterns, and medical history. Digital weighing scales, Stadiometers, and digital sphygmomanometers were used to measure height, blood pressure, and weight, respectively. Epi-Data version 3.1 was used to enter the data before exporting it to SPSS version 25 for analysis. To find factors associated with prehypertension/hypertension, binary logistic regressions were conducted and odds ratios with 95% confidence intervals were computed. The overall prevalence of prehypertension/hypertension was 42.8% (95% confidence interval: 39.56, 49.47). Factors associated with prehypertension/hypertension in this study were older age, male gender, obesity, diabetes mellitus comorbidity, alcohol drinking, and family history of hypertension. Lifestyle modification is demanded for pre-hypertensive/hypertensive patients to prevent progression to severe complications, including premature death and permanent disabilities.

Keywords

prevalence of prehypertension/hypertension prehypertension hypertension factors associated with prehypertension/hypertension predictors associated factors

What do we already know about this topic?

Prehypertension/hypertension complications and its impacts.

How does your research contribute to the field?

Our research delivers information on the prevalence of prehypertension/hypertension and its associated factors for the responsible bodies to fill knowledge gap and take an appropriate intervention against the identified gap.

What are your research’s implications toward theory, practice, or policy?

The stated stakeholders should think about the appropriate intervention as the prevalence of prehypertension/hypertension and its associated factors revealed by this study alarming the incoming fatal complication including premature death and permanent disabilities among the patients.

Background

The global ramifications of non-communicable diseases (NCD) pose a significant governmental health challenge, adversely affecting social and economic development on a global scale.¹ Although NCD are prevalent in developed countries, Sub-Saharan Africa (SSA) grapples with an escalating epidemic marked by the prevalence of cardiovascular diseases (CVD), including blood pressure rise, oncologic conditions, and metabolic conditions like diabetes. Of which one of particular concern is high blood pressure.²

Hypertension stands out as one of the most prevalent health issues globally.³ It is linked to a heightened risk of morbidity and mortality related to CVD and stands as the foremost preventable cause of death in the human population. The conventional definition of hypertension, indicated by a blood pressure (BP) reading of 140/90 mm Hg, is based on the recognition that the risk of CVD substantially rises beyond this threshold. Nevertheless, recent findings indicate an elevated risk of CVD in individuals with BP readings as low as 115/70 mm Hg, with this risk steadily increasing as blood pressure rises.⁴

Prehypertension is characterized by a systolic blood pressure (SBP) ranging from 120 to 139 mm Hg or a diastolic blood pressure (DBP) between 80 and 89 mm Hg and Hypertension is defined as a systolic blood pressure (SBP) of 140 mm Hg or higher or a diastolic blood pressure (DBP) of 90 mm Hg or higher, based on the average of two or more properly measured, seated blood pressure readings on each of two or more office visits: as defined by the Seventh Joint National Committee (JNC7) on the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.⁵ Coined in 2003 by JNC7, the term “Prehypertension” introduced a new classification for elevated blood pressure, serving as an early warning for the potential development of hypertension and cardiovascular disease.⁶ Subsequent to the release of the JNC7 report, numerous studies have investigated the prevalence and significance of prehypertension, providing evidence supporting its status as a pre-hypertensive state.^7
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Prehypertension/hypertension have emerged as significant public health concerns for government bodies, given their robust correlation with an elevated risk of cardiovascular and cerebrovascular events.¹¹ Pre-hypertensive/hypertensive people had a 31% higher risk of coronary heart disease (CHD), a 49% higher risk of stroke, and a 44% higher risk of total cardiovascular events when compared to people with normal blood pressure.¹²

Furthermore, research findings revealed that prehypertension/hypertension was associated with atherosclerosis, angiogenesis, damage of micro vessels, hypertrophy of left ventricle, and arteriosclerosis of coronary artery.^13
-17 Recent WHO’s global sustainable development goal plans to reduce NCD, including elevated blood pressure by 33% by year 2030, through controlling and therapeutic measures.¹⁸ In addition, the Federal Democratic Republic of Ethiopia government developed initiatives in the plan of Health Sector Transformation, which focus on alleviating of high blood pressure. Identifying factors that can be altered or those that cannot be altered is crucial to minimize the likelihood of experiencing additional complications linked to CVD. However, associated risk factors for pre-hypertension/hypertension have not been well studied.

Therefore, researching the prevalence of prehypertension/hypertension and associated risk factors could help in preventing prehypertension, hypertension and serious associated multiple organ damage. No studies conducted on the prevalence of prehypertension/hypertension and its associated factors in Ethiopia. Therefore, this study aimed to determines the prevalence of pre-hypertension/hypertension and its associated factors among adults in Wolaita zone of Southern Ethiopia, 2023.

Methods

Study Design, Setting, and Period

This is hospital-based cross-sectional study done from January 24 to February 25, 2023 in governmental hospitals in Wolaita zone, South Ethiopia. There were 8 public hospitals (1 comprehensive specialized hospital and 7 primary hospitals) in the Wolaita zone.¹⁹

Wolaita Sodo university comprehensive hospital (WSUCH) is the only comprehensive teaching hospital located in Wolaita Sodo town. There are 7 primary hospitals in the zone during study period; Which are located in Bodity, Gasuba, Bitana, Bale, Humbo, Kindo didaye, and Bombe.

Sampling Procedure

Sample was estimated a single population proportion formula (prevalence [P] = 50%), because prevalence was not known. We used confidence interval (CI) = 95%, margin of error = 5%, non-response = 10%. Accordingly; the total sample size was 422. The total sample sizes were distributed among 5 adult OPDs in WSUCTH and respective adult OPD’s in the remaining hospitals. Sampling units were included in the study by using a systematic sampling technique. The first sampling units were selected by lottery method and the remaining study participants were included every consecutive patient until the required sample size was reached.

Data Collection Techniques

The 6 sections of the interviewer administered questionnaires concerned with sociodemographic information, lifestyle characteristics, physical activity, dietary practice, medical and genetic background and anthropometric measurements were utilized for data collection. The sociodemographic information includes information on age, gender, residency, marriage condition, profession, level of education, household income, and any history of hypertension in the family. On the other section of the questionnaire, information about lifestyle status, such as smoking and alcohol use, degree of physical activity, and food status, was requested. The last section consisted height, weight, and blood pressure.

Blood pressure (BP) measurement: As WHO recommendations, BP was measured.²⁰ Qualified healthcare professionals measured BP by utilizing a sphygmomanometer and an appropriately sized cuff for the respondent’s arm circumference. Resting 5 min in the inclined position, 2 separate BP readings were taken, with the mean of the readings being recorded. Before the assessment, subjects were instructed to abstain from using stimulant medications or using stimulant drinks like coffee or tea. On the basis of their arm circumference, BP was taken in the morning using the proper cuff. The analysis used the mean values of 2 measurement held on 5 min difference. Based on the JNC-7 criteria, hypertension (HT), prehypertensive (PRT), and normotensive (NT) were classified. Measurements of weight (in kg) and height (in cm) were part of the physical examination.

Anthropometric measures: Weight and height were assessed in accordance with the established protocols outlined by the World Health Organization (WHO).¹⁸ The respondents’ height was approximated to the nearest 0.1 cm, employing a standard stadiometer, with individuals standing upright and without any outerwear. Weight measurements were taken after removing heavy outer jackets and scarves. Weight measurements were recorded to the closest 0.1 kg. Body Mass Index (BMI) was calculated by dividing the weight (in kg) by the square of the height (in m²)²⁰ and subsequently categorized as follows: Under weight: BMI < 18.00 kg/m², Normal weight: BMI = 18-25.00 kg/m², Overweight: BMI ≥ 25.00 kg/m² and ≤29.99 kg/m, and Obese: BMI ≥ 30.00 kg/m² and ≤50.00 kg/m².¹⁹

In our study, we aimed to comprehensively assess participants’ dietary habits by utilizing a questionnaire that explored various aspects of their food consumption. Participants were asked about their regular consumption of fatty meat, intake of processed foods, inclusion of egg products in their diets, and the primary type of oil used for food preparation. Additionally, we inquired about the average number of servings of vegetables included in their diet per week. These questions were carefully crafted to capture a broad spectrum of dietary behaviors, providing valuable insights into participants’ food choices and nutritional patterns.²¹

In exploring the lifestyles and characteristics of our respondents, we employed a series of targeted questions to gather valuable information. Participants were queried about their smoking habits, including whether they are current smokers and, if so, the frequency of their smoking on a daily basis. Additionally, respondents were asked about their history of alcohol use, with those answering affirmatively prompted to specify the frequency of their alcohol consumption. Furthermore, participants provided insights into their sedentary behaviors by indicating the average number of hours spent sitting down during work on a typical day. These tailored inquiries were designed to capture a comprehensive picture of respondents’ lifestyles and behaviors, enriching our understanding of the factors influencing their health and well-being.^21,22

Level of Physical Activity: The assessment of physical activity level utilized the International Physical Activity Questionnaire (IPAQ) short version. The categorization of physical activity followed the guidelines provided in the IPAQ manual for reliability and validity.²³ The primary objective of the IPAQ instruments is to aggregate individual indicators into an overall measure of physical activity-related MET (Metabolic equivalent). The recommended MET estimates of IPAQ: Vigorous physical activity = 8 METs, moderate physical activity = 4 METs, walking on average = 3.3 METs. To calculate the overall METs of physical activity, each category was multiplied by its corresponding Special MET estimate value. Additionally, the recommended categorical score, comprising three levels of physical activity (low, moderate, and high) as proposed in the IPAQ Scoring Protocol (short form), was employed.^23,24

In examining the medical and genetic factors among our study participants, we addressed a range of pertinent health-related aspects. Participants were queried about their current stress levels, diabetes mellitus (DM) diagnosis, and any history of hypertension diagnosis. For those diagnosed with hypertension, additional information was gathered on their current treatment status. Participants were also asked about their use of hormonal contraceptives and whether there was a familial history of hypertension. These targeted inquiries aimed to elucidate the interplay of medical and genetic factors, contributing to a comprehensive understanding of the health profiles within our study participants.

Operational Definitions

According to JNC 7 blood pressure is categorized as follows⁵:

Normal BP is defined as SBP < 120 and DBP < 80 mm Hg

Pre-hypertension: systolic BP 120–139 mm Hg or DBP 80–89 mm Hg

Stage 1 hypertension: SBP of 140–159 mm Hg or DBP 90–99 mm Hg

Stage 2 hypertension: SBP of 160–179 mm Hg or DBP 100–109 mm Hg

High blood pressure is defined as pre-hypertensive or hypertensive (SBP ≥ 120 or DBP ≥ 80)^25,26

Data Quality Assurance

Prior to data collection, questioner was translated from English to Amharic then back to English by language experts. The questioner was examined for content validity and pretest was conducted on 10% of sample size in Arbaminch general hospital, which is different from the study area. Training was given to data collectors and supervisors for 2 consecutive days before actual data collection mainly on the appropriate utilization of the weight, height and BP measurement tools. Data quality was controlled by designing the proper data collection materials, through continues supervision. The collected data was reviewed and checked for completeness before data entry and analysis.

Following the daily data collection, a review session was conducted to assess the thoroughness of questionnaire responses, ensuring that all questions were appropriately addressed. The principal investigator oversaw the corrections. Prior to each day’s fieldwork, an evaluation of the measuring scale and a functionality check of the blood pressure monitoring device were performed.

In this study the level of physical activity was assessed using the standard International Physical Activity Questionnaire (IPAQ) short version.^23,24,27 We conducted reliability testing to assess the consistency and precision of our other assessment tools. Test-retest reliability was assessed by administering the same assessment tool to 20% of total participants (83 individuals) on 2 separate occasions. The correlation coefficient between the scores on the 2 occasions was found to be excellent (r = 0.90), indicating a high level of consistency. Additionally, internal consistency was assessed using Cronbach’s alpha, resulting in an excellent value of α = 0.92, suggesting strong internal consistency among the items within the assessment tool.

Data Analysis

The acquired data underwent input into Epi-Data Manager version 3.1, where it was subjected to scrutiny, coding, and subsequently exported to Statistical Package for the Social Sciences (SPSS) version 25. Summary statistics, including frequencies, percentages, means, standard deviations, and crosstabs, were employed for data summarization.

In addressing potential confounding factors, our analysis included rigorous assessments to ensure the reliability of the fitted multivariate model. The Parallel Line Test results (P-value = 0.074) affirmed the consistent interpretation of the effects of independent variables across different levels, indicating a well-fitted model for multivariate analysis. Furthermore, a thorough Multicollinearity Test revealed no significant multicollinearity concerns among candidate variables, as indicated by variance inflation factors (VIF) consistently below 10. These measures collectively support the robustness of our model, enhancing confidence in the examination of associations while minimizing confounding influences.

Binary logistic regression was utilized to examine the relationship between each independent variable and the dependent variable. Variables with a significance level below 0.25 were included in a multivariable logistic regression analysis, employing a stepwise backward method.²⁸ Significance was established at a P-value of 0.05 with a 95% confidence interval (CI). The strength of association was interpreted using an adjusted odds ratio.

Results

Socio-Demographic Status of the Participants

A total sample of 417 adults was participated in this study and which gives the response rate of 98.8%. Out of 417 participants, 299 (71.7%) were males and majority of respondents were married (52.3%) (Table 1).

Table 1.

Socio-Demographic and Economic Characteristics of the Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia, January 24 to February 25, 2023 (n = 417).

Variables	Frequency		Prehypertension/hypertension
Variables	n	%	Yes	No
Age in years
25-34 years	25	6.0	26	15
35-44 years	111	26.6	21	52
45-54 years	143	34.3	64	79
≥55 years	138	33.1	68	92
Gender
Male	299	71.7	129	137
Female	118	28.3	50	101
Residence
Urban	309	74.1	118	120
Rural	108	25.9	61	118
Marital status
Single	74	17.7	44	74
Married	218	52.3	45	167
Divorced	76	18.2	22	74
Separated	49	11.8	68	42
Education status
Unable to read and write	57	13.7	39	57
Able to read and write	53	12.7	15	60
Primary education	88	21.1	31	67
Secondary education	109	26.1	24	98
Diploma and above	110	26.4	70	95
Occupation
Government employee	72	17.3	47	57
NGO employee	132	31.7	34	46
Merchant	102	24.5	31	62
Farmer	51	12.2	21	35
Other	60	14.3	54	38
Monthly income in Ethiopian Birr
<1000	45	10.6	15	37
1001-2500	206	49.4	77	117
>2500	166	40.0	87	84

Note. Others—Daily laborer, drivers, security, cleaners.

Life Styles Among Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia

From a total of 417 respondents, only 89 (21.3%) of the respondents were current smokers. Majority of respondents (75.1%) never consumed alcohol at least once, while 104 (24.9%) had consumed alcohol at least once. Of respondents who had consumed alcohol at least once, 34 (33%) consumed alcohol less than once a month (Table 2).

Table 2.

Lifestyles of Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia, January 24 to February 25, 2023 (n = 417).

Variables	Category	Frequency (percentage)	Prehypertension/hypertension
Variables	Category	Frequency (percentage)	Yes	No
Current smoker	Yes	89 (21.3)	73	15
	No	328 (78.7)	105	223
Daily smoker (n = 40)	Yes	12 (23.0)	10	11
	No	52 (77.0)	15	4
Ever used alcohol	Yes	104 (24.9)	72	105
	No	313 (75.1)	107	133
Frequency of alcohol use (n = 72)	Daily	5 (4.8)	5	0
	5-6 days/week	11 (10.5)	11	4
	1-4 days/week	19 (18.2)	3	18
	1-3 days/week	35 (33.5)	5	7
	<once/month	34 (33.0)	6	3
Sitting down during work	>3 h	218 (52.2)	50	103
	<3 h	199 (47.8)	129	135
Physical activity	High	99 (23.7)	16	68
	Moderate	150 (35.9)	58	90
	Low	168 (40.4)	105	80

Dietary Factors Among Respondents Attending OPD of Governmental Hospitals in Wolaita Zones of Southern Ethiopia

Regarding dietary characteristics of respondents, 308 (73.9%) of respondents didn’t consume fatty meat while almost half (44.5%) of respondents consume vegetables up to twice a week (Table 3).

Table 3.

Dietary Factors Among Study Subjects Attending OPD of Governmental Hospitals in Wolaita Zone of South Ethiopia, January 24 to February 25, 2023 (n = 417).

Variables	Category	Frequency (percentage)	Prehypertension/hypertension
Variables	Category	Frequency (percentage)	Yes	No
Fatty meat consumption	Yes	109 (26.1)	79	106
Fatty meat consumption	No	308 (73.9)	100	132
Processed food consumption	Yes	198 (47.4)	105	115
Processed food consumption	No	219 (52.6)	74	123
Egg product consumption	Yes	393 (94.2)	141	223
Egg product consumption	No	24 (5.8)	38	15
Oil used for food preparation	Vegetable oil	239 (57.3)	100	136
Oil used for food preparation	Saturated oil	178 (42.7)	79	102
Vegetable use/week	0-2	185 (44.5)	34	104
	3-4	163 (39.0)	134	80
	5-7	69 (16.5)	11	54

Medical and Genetic Factors Among Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia

Regarding medical conditions, from all 417 participants in this study 136 (32.4%) had reported diabetes mellitus. Similarly, 120 (28.8%) reported that they had family history of hypertension. Majority of respondents (73%) reported that they experienced stress (Table 4).

Table 4.

Medical and Genetic Factors Among Study Subjects Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia, January 24 to February 25, 2023 (n = 417).

Variables	Category	Frequency (percentage)	Prehypertension/hypertension
Variables	Category	Frequency (percentage)	Yes	No
Stress	Yes	308 (95.4)	148	223
Stress	No	109 (4.6)	31	15
DM (self-reported)	Yes	135 (32.4)	164	61
DM (self-reported)	No	282 (67.6)	15	177
History of hypertension	Yes	57 (13.6)	75	32
History of hypertension	No	360 (86.4)	104	206
On treatment for hypertension (n = 75)	Yes	16 (28)	32	8
On treatment for hypertension (n = 75)	No	41 (72)	28	7
Hormonal contraceptive utilization (n = 118)	Yes	37 (31.3)	37	30
Hormonal contraceptive utilization (n = 118)	No	81 (68.7)	23	28
Family history of hypertension	Yes	120 (28.8)	137	32
	No	297 (71.2)	42	206

BMI Status Among Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia

Regarding body mass index among respondents, 42 (10%) were categorized as underweight and 104 (25%) of them were categorized as obese. The remaining 217 (52%) and 54 (13%) of respondents were categorized as normal weight and overweight respectively (Figure 1).

Figure 1.

BMI classification among respondents attending OPD of governmental hospitals in Southern Ethiopia, January 24 to February 25, 2023 (n = 417).

The Prevalence of Prehypertension/Hypertension Among Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia

The findings of this study showed that the overall prevalence of prehypertension/hypertension was 42.8% (95% CI: 39.56, 49.47). The majority of respondents (57.2%) have blood pressure measurements with in normal limit. The mean systolic and diastolic blood pressure measurement results were 104.36 (SD ±16.96) and 71.37 (SD ±9.34) mmHg respectively (Figure 2).

Figure 2.

Blood pressure classification among respondents attending OPD of governmental hospitals in Wolaita zones in Southern Ethiopia, January 24 to February 25 2023 (n = 417).

Factors Associated with Prehypertension/Hypertension Aamong Respondents Attending OPD of Governmental Hospitals in Wolaita Zone of Southern Ethiopia

All predictor variables that have a P-value less than 0.25 in bivariable analyses were considered candidate variables for the multivariable analysis. Factors associated with prehypertension/hypertension in this study were older age (AOR: 2.8 [CI: 1.76, 4.37]), male gender (AOR: 2.69 [CI: 1.54, 3.74]), obesity (AOR: 3.63 [CI: 2.74, 5.64]), diabetes mellitus comorbidity (AOR: 4.53 [CI: 2.68, 6.89]) alcohol drinking (AOR: 1.5 [CI: 1.15, 5.63]) and family history of hypertension (AOR: 2.7 [CI: 1.76, 7.54]) (Table 5).

Table 5.

Factors Associated With Prehypertension/Hypertension Among Patients Attending OPD in Governmental Hospitals in Wolaita Zone of Southern Ethiopia, 2023 (n = 473).

Variables	Prehypertension/hypertension		COR (95% CI)	AOR (95% CI)	P-value
Variables	Yes	No	COR (95% CI)	AOR (95% CI)	P-value
Age in years
25-34 years	26	15	1	1
35-44 years	21	52	2.45 (1.56, 4.21)	3.46 (2.96, 7.64)	0.87
45-54 years	64	79	5.28 (4.97, 9.28)	1.34 (0.611, 2.948)	0.59
55≥ years	68	92	3.45 (2.36, 4.87)	2.8 (1.76, 4.37)	0.02*
Marital status
Single	44	74	1	1
Married	45	167	2.54 (0.37, 4.76)	1.62(0.58, 2.56)	0.54
Divorced	22	74	0.72 (0.56, 3.53)	1.08 (0.76, 5.23)	0.65
Separated	68	42	3.79 (2.57, 7.41)	2.37 (0.74, 7.87)	0.64
Gender
Female	50	101	1	1
Male	129	137	2.18 (1.87, 1.45)	2.69 (1.54, 3.74)	0.035*
Fatty meat consumption
No	79	132	1	1
Yes	100	106	3.38 (2.63, 7.49)	0.67 (0.17, 3.62)	0.58
Vegetable use/week
0-2	34	104	8.36 (6.61, 12.65)	5.19 (0.83, 12.34)	0.72
3-4	134	80	1.54 (1.78, 6.87)	0.74 (0.12, 4,76)	0.87
5-7	11	54	1	1
Ever used alcohol
No	72	133	1	1
Yes	107	105	4.54 (3.67, 8.87)	1.5 (1.15, 5.63)*	0.036*
BMI
Normal	56	52	1	1
Underweight	19	62	3.83 (2.78, 8.75)	6.42 (0.61, 10.43)	0.93
Overweight	84	58	5.96 (4.76, 12.45)	1.65 (0.38, 7.74)	0.65
Obese	20	66	6.62 (4.76, 9.76)	3.63 (2.74, 5.64)*	0.025*
Self-reported DM
No	164	177	1	1
Yes	15	61	4.72 (3.87,13.73)	4.53 (2.68, 6.89)	0.042*
Hormonal contraceptive use
No	37	28	1	1
Yes	23	30	0.67 (0.91,4.26)	0.75 (0.54, 0.84)	0.83
Family history of hypertension
Yes	137	51	4.67 (3.76,7.23)	2.7 (1.76, 7.54)	0.027*
No	42	206	1	1

Statistically significant at P < .05.

Discussion

This study assessed the prevalence and associated factors of pre-hypertension/hypertension among adults attending the OPD of the governmental hospitals in Wolaita zone of Southern Ethiopia. The overall prevalence of prehypertension/hypertension was 42.8% among patients attending OPD in governmental hospitals in Wolaita zone of Southern Ethiopia, which is consistent with the study conducted in Iran, and Zare et al.²⁹ and lower than prevalence of pre-hypertension/hypertension study conducted in China, Jamaica, Thailand, Dubai, and Ghana.^30
-34 This discrepancy might be attributed to socio demographic differences. In contrary to the above studies, a finding of this study depicts slightly higher prevalence of pre-hypertension/hypertension than the findings of Peru, Indonesia, Vietnam, and Democratic Republic of Congo.^25,26,35,36 These higher prevalence rates in our study compared to previous research may be attributed to differences in population demographics, lifestyle factors, and regional health trends impacting prehypertension/hypertension rates.

Multivariate logistic regression model analysis found that gender, alcohol drinking, higher body mass index and family history of hypertension were factors which are significantly related to pre-hypertension/hypertension.

The prevalence of pre-hypertension/hypertension was 68% of the population already in the age group of 55 and above years. Older ages (55 years and above) were at 2.8 times increased risk of pre-hypertension/hypertension when compared to young groups. This finding is in contrast to study conducted in China, in which there is no significant difference in the prevalence of prehypertension/hypertension among different age groups.¹¹ However this finding is supported by the studies conducted in Algeria,³⁷ and Malaysia.³⁸

Higher prevalence of pre-hypertension/hypertension was found in male (98%) as compared to female (12%) subjects. Males were at 2.7 times increased risk of having pre-hypertension compared to females. This finding is in line with the study conducted in China,¹¹ Algeria,³⁷ Israel,³⁹ and Malaysia.³⁸ The molecular pathways underlying vascular, nervous system, and kidney functioning that resulted in hypertension could account for the gender discrepancies.⁴⁰ Furthermore, the reason for this result might be the protective effect of estradiol in females, which prevents them from risk of increased BP and cardiovascular disease while they are in the child bearing period. While several research from sub-Saharan Africa^41
-43 revealed that females were at higher risk than men to experience pre hypertension/hypertension, which might be attributed to postmenopausal period of women in which protective hormonal activity declines.

The odd of being pre-hypertension/hypertension was 3.6 times higher with obesity when compared to normal weight participants. Higher body mass index was associated with pre-hypertension/hypertension in studies conducted in China,¹¹ Algeria,³³ Malaysia,³⁸ Bangeladish,⁴⁴ and Ghana.⁴⁵ Improved living conditions and reduced physical activity lead to weight gain, which increases blood flow to numerous important organs and tissues in response to their higher metabolic demands. As a result, there will be greater pressure on the artery walls.⁴⁶ But research from Tanzania and Uganda showed that people with central obesity and a high BMI had a low prevalence of hypertension.²

Alcohol consumption increase risk of having pre-hypertension/hypertension more than 1.5 times compared to non-alcohol consumers. This finding is supported with the finding of the study conducted to assess association of alcohol consumption with prehypertension.⁴⁷ Other similar studies conducted to assess risk factor of pre-hypertension/hypertension revealed that alcohol consumption was significantly associated with pre-hypertension/hypertension.^48,49

The odd of being pre-hypertension/hypertension is 2.7 times higher in those with family history of hypertension compared to those who don’t have family history of hypertension. This is due to genetical involvement in the pathogenesis of increased blood pressure. Studies revealed that current increment in BP is strongly associated with family history of hypertension.^50
-52

There was no significant association between the proportion of pre-hypertension/hypertension and marital status, education, income, or occupation. These socioeconomic and demographic factors were widely viewed as contributing to the onset of hypertension.^53
-55

Conclusion and Recommendation

In this study, the prevalence of pre-hypertension/hypertension was high. Older age, male gender, alcohol consumption, family history of hypertension and obesity are significant associated factors that lead to pre-hypertension/hypertension. According to our finding we strongly recommend lifestyle modification for pre-hypertensive/hypertensive patients to prevent progression to hypertension and resulting complications. We suggest researchers to conduct prospective studies in order to determine the role of pharmacotherapy in pre-hypertension/hypertension in future studies.

Limitation of the Study

Recall and social desirability bias could be one of the limitations of the study. In addition, resource constraints this study didn’t assessed CVD risk factors such as lipid profile, blood sugar level, and HbA1c tests were not performed in this study.

Supplemental Material

sj-docx-1-inq-10.1177_00469580241246968 – Supplemental material for Prevalence of Pre-Hypertension/Hypertension and Its Associated Factors Among Adults in the Wolaita Zone of Southern Ethiopia: A Cross-Sectional Study

Supplemental material, sj-docx-1-inq-10.1177_00469580241246968 for Prevalence of Pre-Hypertension/Hypertension and Its Associated Factors Among Adults in the Wolaita Zone of Southern Ethiopia: A Cross-Sectional Study by Eshetu Elfios Endrias, Teketel Tesfaye Mamito, Temesgen Geta Hardido and Bizuayehu Atinafu Ataro in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

The authors extend their sincere thanksgiving to God at the first place for giving its hand on successful completion of this research. The authors deliver their acknowledgement to Wolaita Sodo University, and the supervisors for their guidance and friendly mentorship Last but not the least, the authors hail the management and staff of the health institutions participated on this study for their contribution to this study.

Author’s Contribution

EEE conceptualized the study, analyzed the data and interpreted the data and wrote the first draft of the manuscript; EEE, TTM, TGH, and BAA reviewed and substantively revised the manuscript. All authors read and approved the final manuscript. We authors read and confirmed to submit the journal and gave the final approval of version to be published, and agreed to be accountable for all aspect of the work.

Availability of Data and Material

The data sets used and/or analyzed during this study are available from the corresponding author.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Approval

Ethical approval was obtained from Wolaita Sodo University Institutional Review Board (IRB-WSU), college of health sciences research committee with the ethics approval number of WSUCTH/ERC/123/2023. Written informed consent was obtained from the subjects prior to study initiation. Following the approval by IRB, an official letter of co-operation was written to the study area. The study was conducted after permission from concerned management bodies was taken. All the necessary measures have been taken to secure the confidentiality. Data have been treated confidentially as subjects identified by number only, and all methods were carried out in accordance with relevant guidelines and Helsinki regulations.

ORCID iDs

Eshetu Elfios Endrias

Temesgen Geta Hardido

Bizuayehu Atinafu Ataro

Supplemental Material

Supplemental material for this article is available online.

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