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• Volume 9, Issue 12
• Prevalence and associated risk factors of hypertension among persons aged 15–49 in India: a cross-sectional study
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• http://orcid.org/0000-0002-5077-0551 Soumitra Ghosh ,
• Manish Kumar
• School of Health Systems Studies , Tata Institute of Social Sciences , Mumbai , India
• Correspondence to Dr Soumitra Ghosh; soumitra{at}tiss.edu

Objectives This is the first attempt to provide estimates on the prevalence of hypertension at the national, state and district level, a prerequisite for designing effective interventions. Besides, the study aims to identify the risk factors of hypertension.

Design We analysed cross-sectional survey data from the fourth round (2015–2016) of National Family Health Survey (NFHS). NFHS was conducted between January 2015 and December 2016, gathering information on a range of indicators including blood pressure. The age adjusted prevalence of hypertension was calculated for state comparison, while multilevel logistic regression analysis was done to assess the correlates of hypertension.

Setting and participants India (2015–2016; n=811 917) aged 15–49.

Primary and secondary outcome measures The primary outcome is hypertension, which has been defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg.

Results The age-adjusted prevalence of hypertension in India was 11.3% (95% CI 11.16% to 11.43%) among persons aged between 15 and 49 and was four percentage points higher among males 13.8% (95% CI 13.46% to 14.19%) than among females 10.9% (95% CI 10.79% to 11.06%). Persons in the urban location (12.5%, 95% CI 12.25% to 12.80%) had a marginally higher prevalence than persons in rural location (10.6%, 95% CI 10.50% to 10.78%). The proportion of population suffering from hypertension varied greatly between states, with a prevalence of 8.2% (95% CI 7.58% to 8.85%) in Kerala to 20.3% (95% CI 18.81% to 21.77%) in Sikkim. Advancing age, obesity/overweight, male sex, socioeconomic status and consumption of alcohol were found to be the major predictors of hypertension.

Conclusions Hypertension prevalence is now becoming more concentrated among the poor. Policy measures should be taken to improve the hazardous working conditions and growing social pressures of survival responsible for ‘life-style’ changes such as consumption of high calorie food and alcohol.

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https://doi.org/10.1136/bmjopen-2019-029714

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Strengths and limitations of this study

First epidemiological study to provide estimates on prevalence of hypertension at national, state and district level.

Multivariate analysis identified the key drivers of hypertension.

The use of cross-sectional data that does not allow for exploration of causal pathways underlying the reported associations.

The role of behavioural risk factors such as low fruit and vegetable intake and physical inactivity could not be explored in this analysis.

Findings are limited to the persons aged between 15 and 49.

Introduction

Hypertension is the single largest contributor to the avoidable deaths and diseases in India. It is a leading risk factor for cardiovascular disease, which accounted for 23% of total deaths and 32% of adult deaths in 2010–2013. 1 India has committed to take an array of actions to meet the Sustainable Development Goals (SDG) target of reducing premature mortality from non-communicable diseases (NCDs) by one-third by 2030. However, much of the success in meeting this target hinges on its ability to check the rise of hypertension. The Global Burden of Hypertension study has highlighted that of the global burden of 212 million Disability-Adjusted Life Years (DALYs) related to hypertension, 18% occurred in India in 2015. 2 The burden of hypertension in India is expected to rise considerably in the coming years due to rapid environmental and ‘life-style’ changes that emanate from hazardous working conditions and growing social pressures of survival. 3 4

Monitoring and evaluation for SDG

It is, therefore, imperative that blood pressure trends are monitored to evaluate the progress that the country makes vis-à-vis the SDG goal of reduction in NCD mortality. To do that, data on hypertension are needed so that stakeholders can design appropriate interventions and evaluate national programmes aimed at effectively addressing hypertension and associated NCDs. But there was a paucity of reliable information on the status of hypertension in India. As a result, to assess the magnitude of this problem, policy makers had to rely on community studies or surveys that provided self-reported data on hypertension. 5–8 Further, data from small studies were extrapolated to obtain national level estimate on hypertension. 9 Although these studies were helpful and used as a key resource in the arsenal of health policy makers, in the absence of active surveillance or data from population based surveys, policy makers are unable to determine the true burden of hypertension in India.

The recent health surveys have measured blood pressure, providing an opportunity to explore the trends in prevalence of hypertension both at the national, sub-national (state) and district level. Given the heterogeneity in the demographic and socioeconomic conditions across states in India, it is very likely that there would be considerable inter-state variations in hypertension prevalence. 9 Moreover, the socioeconomic disparities are widespread even within the state. Hence, estimates at the state and district levels are required for policy formulation, setting intervention priorities and to evaluate national programmes. This study is the first in India to provide estimates on the prevalence of hypertension at the national level and for each state, district, and by rural and urban areas and individual characteristics such as age, sex and economic status using the most recent large-scale survey data. Aside from providing estimates on hypertension prevalence, an attempt was also made to identify the correlates of hypertension.

This study is based on the data from the fourth wave of National Family Health Survey (NFHS), which is the Indian version of Demographic and Health Survey carried out periodically in over 90 countries across the globe. NFHS 4 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOH&FW) and led by International Institute for Population Sciences. The survey was a collaborative effort of 14 research organisations, including three Population Research Centres (under MOH&FW). ICF International provided technical assistance at all stages of NFHS project. NFHS 4 began on 20 January 2015 and ended on 4 December 2016. The survey was conducted across all 29 states and 7 union territories (UTs) in India. The survey is representative not only at the national and state level but also at the district level.

NFHS adopted a 2-stage stratified random sampling approach by selecting primary sampling units (PSUs) (villages in rural areas and census enumeration blocks in urban areas) with probability proportional to population size at the first stage and subsequently, picking the same number of households from each of selected PSUs through systematic random sampling. Both male and female interviewers were recruited by field agencies to interview respondents of the same sex. The data collection team made up to three visits in case no body was present in the chosen household or any eligible member was not available at the time of the household visit.

The household-level questionnaire of NFHS covered the details on possession of 33 assets and access to certain utilities. The information on assets and utilisation of utilities were used for constructing wealth index, which reflects the standard of living of households. The wealth index categorises households into five wealth quintiles: ‘poorest’, ‘poor’, ‘middle’, ‘rich’ and richest. In NFHS, the Biomarker Questionnaire collected details on height, weight and haemoglobin for children, and measurements of height, weight, haemoglobin, blood pressure and random blood glucose for women aged 15–49 and men aged 15–54. The different age ranges for men and women were chosen, considering the average spousal age gap of 5 years in India. The survey used same questionnaires, field procedures and procedures for biomarker measurements across the country to ensure comparability across states and to ensure the highest possible data quality. The response rate for BP measurements was 97% among women and 92% among men. Apart from taking BP measurements, all participants irrespective of their BP were asked, ‘Were you told on two or more different occasions by a doctor or other health professional that you had hypertension or high blood pressure?’ If they responded in the affirmative, they faced a follow-on question, ‘To lower your blood pressure, are you taking a prescribed medicine?’

The analysis was restricted to women and men aged 15–49, after excluding men aged 49–54 (n=8618) to ensure an equal age range among women and men. Missing values (n=32 268) were also excluded from the analysis. Data were weighted prior to analysis.

Ethics approval

The study is based on an anonymous publicly available data set with no identifiable information on the survey participants; therefore, no ethics statement is required for this work.

Statistical analysis

Hypertension was considered as the outcome variable of this study. Three blood pressure readings were taken in NFHS. The first measurement was discarded and then, based on the average of second and third readings of blood pressure, it was decided whether a participant was hypertensive or not. Hypertension was defined as systolic blood pressure of at least 140 mm Hg or diastolic blood pressure of at least 90 mm Hg. The definition was based on the criteria given by WHO and American Heart Association. 10 In addition, an individual is classified as having hypertension if she/he is currently taking antihypertensive medication to lower his or her blood pressure. To make the prevalence of hypertension comparable, age adjusted prevalence rates were calculated for all states, UTs and districts using the direct standardisation method. The national population, as per 2011 Census, was used as a reference population for carrying out the standardisation technique. To understand how hypertension prevalence varies by socioeconomic status (SES), the wealth index was converted into a dichotomous variable; where the bottom 60% that is, ‘poorest’, ‘poor’ and ‘middle’ were combined into one group (low SES), the remaining two categories were clubbed into the other category (high SES). Besides conducting bivariate analyses, multilevel (first level: individual; second level: district; third level: state) logistic regression model with random intercepts and fixed slopes was employed to calculate multilevel ORs with corresponding 95% CI.

Dependent variable

Hypertension for persons aged between 15 and 49. The dichotomous variable, hypertension, was defined as 1=hypertensive, else=0.

Explanatory variables

Predictors were selected based on their effects on hypertension.

Sociodemographic variables

Age, sex, marital status, caste (Indian society is mainly divided into four castes within the framework of the Hindu caste system. The castes used to be classified according to occupation. Historically, many sub-castes have faced discrimination, deprivation and social exclusion on account of their assigned ‘low-status’. Recognising the marginalisation of certain communities and socioeconomic differences among different population groups, the constitution of India categorised the Indian population into four major groups: scheduled tribe (ST), scheduled caste (SC), other backward class (OBC) and General. ST is the most socio-economically disadvantaged group, followed by the SC and OBC and together they comprise 69% of India’s population, with SC at 19.7%, ST at 8.5% and OBC at 41.1%), education, place of residence, wealth status. Besides sociodemographic variables, we included body mass index, tobacco use and alcohol consumption as proxy for behavioural risk factors. The education categories are defined based on number of years of education completed by an individual: 0 year as ‘no education’; 1–5 years as ‘primary education’; 6–12 years as ‘secondary education’; and more than 12 years of educational attainment categorised as ‘higher studies’.

All statistical analyses were performed using STATA V.14.

Patient and public involvement

No patients or public were involved in the conception, design and planning of this study.

Sample characteristics

As seen in table 1 , of the total 779 649 persons who participated in the survey, a little more than half of them (51.3%) were aged between 15 and 29 years. It is worth noting that as per India’s census, the median age was 24 years in 2011. Nearly 13% of men and 27% of women never went to school. Further, 13% of both sexes attended school only up to primary level. Almost 64% of men and 73% of women were currently married. A third of the study population were urban residents and a quarter of them were either overweight or obese. Around 48% of men were users of some form of tobacco as compared with 10% of women. The gap between men’s and women’s tobacco use is not unusual. It is in consonance with results of other nationally representative household surveys. For instance, as per Global Adult Tobacco Survey (2016–2017), 19% of men and 2% of women smoke tobacco in India. 11 It may be pointed out that traditionally tobacco usage is significantly higher in males than in females in the Indian sub-continent. This could be attributed to cultural disapproval, prohibiting women from smoking in India. Under-reporting of tobacco use by women is also partly responsible.

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Characteristics of sample population by gender, National Family Health Survey, India, 2015–2016

Like tobacco use, a significantly greater proportion of men (nearly 31%) reported consuming alcohol either almost every day, about once a week or less than once a week as compared with 2.5% among women.

Prevalence of hypertension at national, state and district level

Table 2 shows crude and age-adjusted prevalence of hypertension among persons aged 15–49 for the year 2015–2016. The data reveal that the age-adjusted prevalence of hypertension in India was 11.3% and the prevalence was four percentage points higher in men (13.8%) than in women (10.9%). Hypertension prevalence was 12.5% in urban, compared with 10.6% in rural location.

Prevalence of hypertension in India, 2015–2016

The results indicate that the age-adjusted prevalence of hypertension varied greatly between states and UTs, with a prevalence of 8.2% in Kerala to a prevalence of 20.2% in Sikkim (See figure 1 and online supplementary figure S1 ). Quite intriguingly, the prevalence of hypertension was highest in the north-eastern (NE) states, namely Sikkim (20.2%), Nagaland (17.6%), Assam (17.6%), Arunachal Pradesh (16.6%) and Tripura (15.4%). Further, hypertension prevalence was very high in few non-NE states, namely Jammu and Kashmir (15.8%), Punjab (14.8%), Himachal Pradesh (14.8%) and Telangana (14.2%). On the other hand, proportion of population suffering from hypertension was relatively low in states such as Kerala (8.2%), Bihar (8.8%), Delhi (8.6%), Rajasthan (9.1%), Uttar Pradesh (9.6%) and Jharkhand (9.6%).

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Prevalence of hypertension across states, India, 2015–2016.

Figure 2 displays the inter-district variations in hypertension prevalence. The proportion of hypertensive population varied tremendously, ranging between 3.5% in district Mahoba, Uttar Pradesh and 34.7% in district Dibang Valley, Arunachal Pradesh. The majority of the districts across the country recorded a high hypertension burden, with more than one-tenth of the persons aged 15–49 hypertensive in 427 districts. Only 10 districts had hypertension levels below 5% and all of them except one were in the relatively less advanced states. Several districts with alarmingly high prevalence of hypertension were clustered across NE states. Five districts in Arunachal Pradesh, two districts in Punjab, one each in Sikkim, Assam and Andaman and Nicobar Islands were among the top ten districts with the highest levels of hypertension. The results revealed that at least one in every five persons aged between 15 and 49 were having hypertension in as many as 28 districts across India.

Prevalence of hypertension across districts, India, 2015–2016.

The findings highlighted that the prevalence of hypertension was higher in men than in women in most states and UTs, except in Delhi, West Bengal, Meghalaya and Jammu and Kashmir ( online supplementary figure S2 ). The sex difference in prevalence of hypertension was highest in Andaman and Nicobar Islands (12.4%), followed by Sikkim (8.4%), Himachal Pradesh (7.3%) and Manipur (7.2%). The results also suggest that, in general, the gender differentials were relatively smaller in low prevalence states than in high prevalence states. Figure 3 shows the prevalence of hypertension in rural and urban settings of all states. As shown in the earlier figure, the prevalence rate of hypertension was found to be higher in urban than in rural areas for most of the states. However, there were a few exceptions. The prevalence of hypertension was relatively higher among the rural folks than their urban counterparts in Punjab, Goa and Kerala. Another interesting pattern emerges while comparing the prevalence of hypertension between high and low SES categories within rural and urban areas of each of these states ( online supplementary figure S3 ). The results suggest hypertension is no longer a disease of the rich. In fact, the distribution of the condition is changing, disproportionately affecting the economically disadvantaged in urban areas of the more developed states such as Punjab, Haryana, Jammu and Kashmir and most of the NE states. Furthermore, the phenomenon of higher prevalence of hypertension among the poor appears to be not limited to only urban setting. In rural areas of Chhattisgarh, Kerala and Mizoram, the burden of hypertension was relatively higher among people from lower socioeconomic groups than those from higher socioeconomic groups. Furthermore, the differences in prevalence of hypertension by low versus high SES categories were generally insignificant in urban areas of most states (<2 percentage points).

Prevalence of hypertension by sector across selected states, 2015–2016.

The weak association between GDP per capita of states and hypertension prevalence ( online supplementary figure S4 ) is also the confirmation of the growing convergence of rich–poor difference in the prevalence of hypertension, particularly in the urban areas.

Sociodemographic differentials in prevalence

The bi-variate and multivariate analyses were carried out to understand the relative importance of socioeconomic and behavioural risk factors of hypertension. Since the bi-variate and multivariate analyses yielded very similar results, we are only presenting the findings of multivariate analysis here. Table 3 shows results for multilevel logistic regression of hypertension by its different covariates. Expectedly, age was found to be an important predictor of hypertension. The likelihood of being hypertensive increased significantly with age. ORs suggest that the risk of hypertension was 6.7 times higher in older age group (45–49 years) than in younger age group (15–19 years). The differences in prevalence probabilities between married, widowed and single were statistically significant. Those who were widowed, separated and divorced were more likely to have hypertension than their single counterparts (OR=1.19; p<0.001). Interestingly, married persons were also found to be at greater risk of hypertension than those who were never married or single (OR=1.08; p<0.001). Educational attainment seems to be inversely related with prevalence, though the effect of education was not significant among those who studied only up to primary level. But persons with secondary (OR=0.92; p<0.001) or higher education (OR=0.81; p<0.001) were less likely to be hypertensive as compared with those with no formal education.

Results of multilevel logistic regression on hypertension, India, 2015–2016

We tried to understand whether economic status affects hypertension risk in people. The ORs suggest a positive association between economic status and hypertension.

Compared with those in poorest quintile, people from richest quintile were having considerably higher likelihood of hypertension (0.21 percentage points). Place of residence was also found to be statistically significantly associated with hypertension. Those from rural areas (OR=0.96; p<0.01) were at a lower risk for hypertension. Caste differences in prevalence of hypertension were not much, except that persons belonging to OBC were less likely to have the condition (OR=0.96; p<0.001) as compared with those from others.

Overweight or obese persons were significantly more likely to suffer from hypertension (OR=2.02, p<0.001 and OR=3.22, p<0.001, respectively). Alcohol consumption was found to be positively related with hypertension; however, no statistically significant association was found between tobacco use and hypertension. Those who drank alcohol almost every day (OR=1.45; p<0.000), about once a week (OR=1.25; p<0.001) and less than once a week (OR=1.17; p<0.001) had a higher risk of hypertension than people without alcohol use habit.

We have explored the regional and sub-regional disparities in the prevalence of hypertension in India. Median odds ratio (MOR) indicates geographical heterogeneity in the prevalence of hypertension across India. Overall, the variation in the prevalence of hypertension was of greater magnitude at the district level (MOR=1.32; p<0.001) than at the state level (MOR=1.28; p<0.001). While the MOR was 1.28 and 1.32, ORs for most individual level characteristics were relatively higher, suggesting that unexplained between-district and between-state variations are not as relevant as individual level characteristics for understanding the prevalence of hypertension.

This article provides estimates on the prevalence of hypertension across different geographical areas in India and examines socioeconomic and life-style factors associated with this condition, by exploiting the latest data from the fourth round (2015–2016) of NFHS. Although some previous research has attempted to understand the burden of hypertension in India, 9 12 13 to the best of our knowledge, this study is the first comprehensive assessment of hypertension prevalence using high-quality survey data of each state and district of India.

One of our key findings is that more than 11% of the population aged 15–49 in India are hypertensive. However, our estimate on the age-adjusted hypertension prevalence differs considerably from the reported crude prevalence (25%) in Geldsetzer et al ’s (2018) study on hypertension. This discrepancy is arising mainly because our estimates of prevalence pertain to those aged 15–49 while the said study provided estimates for adults aged 18 or older. Besides the differences in age composition between two samples, several states and UTs were not covered in annual health survey (AHS) and district-level household survey (DLHS), which were used for assessing hypertension prevalence in Geldsetzer et al ’s study. Furthermore, while the clinical and anthropometric data for AHS were collected in 2014 (Although AHS was conducted during 2013–2014, the biomarker component, ie, Clinical, anthropometric and biological (CAB) data were collected only from a sub-sample of AHS in the year 2014. For details, see http://www.censusindia.gov.in/2011census/hh-series/HH-2/CAB-Introduction.pdf . In contrast, in DLHS, CAB tests were carried out in all selected households), DLHS was carried out between 2012 and 2013. As a result, the pooled data may not provide true estimates of hypertension at the national level owing to inconsistencies between two surveys in terms of survey design, period of data collection (time gap) and non-inclusion of many states and UTs.

Hypertension was found to be more prevalent in men than in women. Although the prevalence of hypertension was relatively higher in urban than in rural areas at the national level, the rural–urban differences were small, implying that hypertension epidemic is spreading very fast even in the rural population. This has serious implications for the rural people. The public health system through primary health centres in rural areas is still focusing on infectious diseases, reproductive and child health and thus, has become too limited. So, people would have to rely on the private sector for the management of hypertension and its associated diseases, which would substantially add to their financial strain.

Considerable inter-state and inter-district differences were found in the prevalence of hypertension. It was more common in NE states, Jammu and Kashmir, Himachal Pradesh, Punjab, and Telengana than in Kerala and less advanced states. The inter-state differentials might have been caused by the differences in risk exposure such as rising affluence, urbanisation, sedentary life style, changing dietary habits, obesity prevalence, social stress and possibly, genetic factors. The finding of relatively lower hypertension prevalence in poorer states is consistent with evidence from the latest burden of disease study that classified these states as having low epidemiological transition level. 14 But surprisingly, Kerala, where epidemiologic transition is most advanced among all states, had recorded the lowest prevalence of hypertension. This may be due to the non-inclusion of older persons in NFHS. It should be noted that Kerala has the highest proportion of elderly population (13%) in India. However, more research is needed to pinpoint the reasons for low prevalence in Kerala. Interestingly, in NE states, despite their low per capita income, the prevalence was way higher than in states with much higher level of socioeconomic development. The higher burden of hypertension among the population of NE could be attributed to ethnicity and food habits. 15 It may be noted that NE Indians belong to Mongoloid, whereas North Indians and South Indians are part of Indo-Aryan and Dravidian ethnic groups. Hypertension has emerged as a major epidemic in many districts. Examples include two districts of Arunachal Pradesh (part of NE India), where every third person was hypertensive and more than a fifth of the population had the condition in as many as 28 districts.

In majority of the states, hypertension prevalence was higher in urban than in rural areas, though the difference was not large and at times, insignificant. Further, in Goa, Punjab, Kerala and Nagaland, the prevalence of hypertension was observed to be higher in rural than in urban communities. Such narrowing differentials may be the result of the factors mentioned in a recent study conducted in Punjab. Tripathy and others (2016) reported that there was no rural–urban differential in terms of dietary practices and prevalence of overweight and obesity barring the fact that a markedly higher proportion of individuals from rural areas always/often add salt before/when eating as compared with those from urban areas. 16

Another major finding was the weak link between economic growth (GDP per capita) and hypertension. Our study reveals that hypertension is affecting the people in more advanced and less advanced states alike. Furthermore, hypertension is not only affecting the affluent but is also widespread among the poor within states. Another salient finding is the increased proportion of poor suffering from hypertension in many states, particularly in the urban areas. This actually confirms the trend seen in studies on NCD. 17 More importantly, these findings paint a disturbing pattern, indicating that it is just a matter of time when the less affluent segment of the population in other states would also face a disproportionately higher burden of hypertension. The situation might have arisen due to factors such as the diffusion and adoption of ‘modern’ lifestyles (the changing dietary behaviour: smoking, drinking, unhealthy diets) across population groups (which is a result of urbanisation, aggressive push of junk food through advertising and marketing and related shifts in sociocultural practice), physical inactivity and high levels of depression and stress (linked to poverty and lack of equal opportunities). 18 19 Our study corroborates the earlier observations as the evidence point to urban residence, obesity, and alcohol use as some of the key drivers of the hypertension epidemic in India. These were also supported by previous research on hypertension in India. 13 16 20 Surprisingly, use of tobacco was not found to increase the risk of hypertension. While it is difficult to explain why use of tobacco did not display statistically significant association with hypertension, one plausible reason could be the young population of our sample. According to a recent study which examined the life-course impact of smoking on hypertension, no statistically significant relationship was found between smoking and the risk of hypertension in the age group younger than 35, though smoking was found to be significantly associated with hypertension in the later ages. 6

Our study has several notable strengths. This is the first study that used the recently released NFHS data, which is based on a sample of households that is representative at the national, state and district levels, thereby, allowing us to provide estimates of the prevalence of hypertension across various geographical levels. Further, multivariate analysis identified the key drivers of hypertension in India.

Aside from the above mentioned strengths, the study has a few limitations, which merit discussion. The findings of this study are limited to the persons aged between 15 and 49 in India. Further, NFHS provides cross-sectional data. This prevents exploration of causal pathways underlying the reported associations. We could not investigate the role of behavioural risk factors such as low fruit and vegetable intake and physical inactivity in this analysis due to the non-availability of such information in the data set.

To conclude, hypertension epidemic is spreading alarmingly in India across rural and urban populations. Disturbingly, the hypertension prevalence is now becoming more concentrated among the poor in both urban and rural areas. This phenomenon of rising hypertension prevalence among the least resourceful people has serious social and economic implications for the country and warrants immediate policy interventions to prevent the catastrophe. 21 22 The district wise estimates on this condition should be used to plan for localised interventions so that the prevalence could be brought down significantly, which would help achieve the national target of 25% relative reduction in the prevalence of hypertension by 2025. 23 We recommend universal blood pressure screening for high prevalence districts to track the progress of interventions. However, when it comes to interventions, the emphasis should be on primary prevention of hypertension. Policy measures should be taken to improve hazardous working conditions of the poor and growing social pressures of survival responsible for ‘life-style’ changes such as consumption of high calorie food and alcohol. On the other hand, a diet rich in fruits and vegetables, regular physical activity and weight control should be promoted.

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Contributors While SG conceptualised the paper, partly analysed the data and wrote the manuscript, MK carried out the analysis of the data. SG edited the paper. The authors discussed the results and approved the revision of the final manuscript.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

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Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement Data are available in a public, open access repository.

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Prevalence of Hypertension and Cardiovascular Risk According to Blood Pressure Thresholds Used for Diagnosis

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Characteristics of Individuals Classified as Hypertensive Under Newly Recommended BP Thresholds

End Points in SPRINT and ACCORD-BP

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Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study

• Henok Asresahegn 1   na1 ,
• Frew Tadesse 1   na1 &
• Ermias Beyene 2  

BMC Research Notes volume  10 , Article number:  629 ( 2017 ) Cite this article

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Hypertension is a growing public health problem in many developing countries including Ethiopia. It is a silent killer and most patients are detected to have it incidentally when they are admitted to hospital for unrelated disease or subjected to pre-employment or preoperative medical checkups. Information on the prevalence of hypertension and its associated factors is to be considered vital to focus and improve prevention and control of cardiovascular diseases. The study design was a cross-sectional survey. The study population consisted of adults aged 25–65 years who lived in Jigjiga city of eastern Ethiopia for at least 6 months. Data were collected using a pretested structured questionnaire, and blood pressure was measured using standardized instruments by trained clinical nurses. Hypertension was defined as having Systolic BP ≥ 140 mmHg or Diastolic BP ≥ 90 mmHg or reported use of regular anti-hypertensive medications prescribed by professionals for raised BP. Data were entered into a computer using Epi Info Version 3.5.1 and exported to SPSS version 16.0 for analysis. Multiple logistic regressions were fitted and Odds ratios with 95% confidence intervals were calculated to identify independently associated factors.

The prevalence of hypertension was 28.3%. Family history of Hypertension [Adjusted OR 5.7; 95% CI (2.9, 10.9)], having high level of income [Adjusted OR 3.1; 95% CI (1.5, 6.3)], being male [Adjusted OR 2.4; 95% CI (1.3, 4.3)], being above grade 12 [Adjusted OR 2.2; 95% CI (1.2, 3.9)], and having BMI ≥ 25 [Adjusted OR 2.0; 95% CI (1.1, 3.5)] were significantly associated with hypertension.

Consistent with the literatures, the prevalence of hypertension was high and may show a hidden epidemic in this population. If established with more robust and nationally representative studies, the finding calls for efficient health screening and regular checkups as well as interventions promoting healthy lifestyles. Accordingly, health promotion regarding hypertension should be provided in the population as means of primary prevention.

Hypertension is a state of elevated systemic blood pressure which is commonly asymptomatic. It is a major cardiovascular risk factor that is closely associated with lethal complications like coronary artery disease, cerebro-vascular accidents, heart and renal failure [ 1 ]. Hypertension is an overwhelming global challenge, which ranks third as a means of reduction in disability-adjusted life-years [ 2 ]. Besides, it is the leading cause of mortality [ 3 ]. Globally, nearly one billion people have hypertension; of these, two-thirds are in developing countries [ 4 ]. The burden of chronic non-communicable diseases (NCDs) in developing countries has risen sharply in recent years. The new epidemic of hypertension and cardio-vascular diseases is not only an important public health problem, but it will also have a big economic impact as a significant proportion of the productive population becomes chronically ill or die, leaving their families in poverty [ 5 ].

Hypertension is a silent killer and most patients are detected to have it incidentally when they are admitted to hospital for unrelated disease or subjected to pre-employment or preoperative medical checkups. The exact causes of high blood pressure are not known, but several factors and conditions may play a role in its development [ 1 ]. Few studies indicate that the disease has become significant public health problem especially in the major cities of Ethiopia. According to the studies conducted in Addis Ababa and Gondar the prevalence of hypertension was high probably indicating a hidden epidemic in those communities [ 6 , 7 ]. To our knowledge, there have not been any published studies in this regard in Somali region of Ethiopia. Hence, we tried to find the prevalence and associated factors of high blood pressure among adults in the region. The findings of this study will be useful to raise awareness among policy makers and the public at large, about the magnitude of high blood pressure and related risk factors of cardiovascular diseases, and thereby, contribute to the design and implementation of appropriate interventions.

Study population

A cross-sectional study was conducted among randomly selected adults aged 25–65 years in Jigjiga city of Somali Regional State in Ethiopia from October to November 2014. The Study participants were permanent residents of Jigjiga city who have been living there at least for 6 months. Subjects with obvious physical deformity, pregnant women and known psychiatric patients who were taking medication were excluded from the study. Single population proportion formula was applied to calculate the sample size by using hypertension prevalence rate of 28.3% [ 6 ], with 5% precision at 95% confidence level, 5% non-response rate, and design effect of 1.5 which as a result give a total sample size of 492.

This study was conducted in accordance with the STEP-wise approach of the World Health Organization (WHO) for NCD surveillance in developing countries [ 8 ]. The approach has three levels: (1) questionnaire to gather demographic and behavioral information, (2) simple physical measurements, and (3) biochemical tests. The present study used the first two steps; questionnaire survey, and anthropometric and blood pressure measurement. Consumption patterns of the participants for various food groups were studied using a Food Frequency Questionnaire.

Data collection and variable specification

Participants were interviewed by trained interviewers using the WHO STEPS-structured questionnaire. In accordance with the STEPS manual, questions related to alcohol and substance use were tailored to reflect the local context of Ethiopia. The questionnaire was first written in English, translated into local languages ( Amharic and Somaligna) by experts and translated back into English by a panel of professionals who speak both languages. The questionnaire was pretested before the initiation of the study and contained information regarding socio-demographic characteristics, tobacco and alcohol use, and nutritional status. A 3-days training of the contents of the STEPS questionnaire, data collection techniques, and ethical conduct of human research was provided to research interviewers prior to the commencement of the study.

Blood pressure (BP) was measured using a digital measuring device with participants sitting after resting for at least 5 min. Two BP measurements were taken with at least 3 min intervals between consecutive measurements. The mean systolic and diastolic BP from the first and second measurement was analyzed. The measurement was taken with each subject sitting on a chair and supported hand. The measurement was taken early in the morning from 7 a.m. to 10 a.m. and in the afternoon after 4 p.m. in a calm environment. Hypertension was defined as mean systolic blood pressure (SBP) ≥ 140 mmHg or mean diastolic blood pressure (DBP) ≥ 90 mmHg. The study protocol was approved by the research and publication technology transfer office of Jigjiga University.

Statistical analysis

Data were entered into EPI INFO (Version 3.5.1), and exported to SPSS (Version 16.0) for statistical analysis. We first explored frequency distributions of socio demographical and behavioral characteristics of subjects and descriptive statistics was used to summarize and present the information in the form of mean, median, percentages and tables with 95% confidence intervals for prevalence estimates. A binary logistic regression model was used to examine factors associated with Hypertension among adults (0 = Non-Hypertensive, 1 = Hypertensive). Variables which showed association with dependent variable in the bivariate analyses at 0.2 were entered into multivariate logistic regression model. Multiple binary logistic regression analysis was used to examine the association between variables and hypertension adjusting for other potential confounders. A p value of less than 0.05 was used to define statistical significance. Both crude and adjusted odds ratio are presented with a 95% confidence interval. The Hosmer–Lemeshow goodness-of-fit and Omnibus tests of model coefficients tests with enter procedure were used to test for model fitness. The explanatory variables were tested for multi-collinearity before entering them into the multivariable model, using the variance inflation factor (VIF) test, the Tolerance test, and values of the standard error. Body mass index (BMI) was computed using weight (Kg) per height (m) 2 . Concerning to income, those with monthly income of < 1970 birr, 1970–2999 birr, and ≥ 3000 birr were labeled as low level, medium level and high level of income respectively.

Physical activity was classified according to the STEPS manual [ 8 ] as follows;

Vigorous-intensity activity on at least 3 days achieving a minimum total physical activity of at least 1500 min/week OR

7 or more days of any combination of walking, moderate-intensity or vigorous intensity activities achieving a minimum Total physical activity of at least 3000 min/week [ 28 ]

3 or more days of vigorous-intensity activity of at least 20 min per day OR

5 or more days of moderate-intensity activity and/or walking of at least 30 min per day OR

5 or more days of any combination of walking, moderate-intensity or vigorous intensity activities achieving a minimum total physical activity of at least 600 min/week.

Low is the lowest level of physical activity. Those individuals who do not meet the criteria for moderate and high are considered.

Smoking status was defined as follows;

Someone who has smoked greater than 100 cigarettes in their life time and has smoked in the last 28 days.

Someone who has smoked greater than 100 cigarettes in their life time but hasn’t smoked in the last 28 days.

Someone who hasn’t smoked greater than 100 cigarettes in their life time and doesn’t currently smoke.

Study demographics

A total of 487 adults provided data for analysis. The mean and median ages of the study participants were 35 and 32 years old respectively (Table  1 ). Regarding the self or family history of any chronic disease; 50 (10.3%), and 16 (3.3%) of the total study participants were known hypertensive, and diabetes mellitus (DM) patients respectively, while 82 (16.8%) and 64 (13.1%) have family history of hypertension and DM respectively. On the other hand, 182 (37.4%) and 131 (26.9%) of the total respondents were Chat chewer and smoker respectively (Table  1 ).

Prevalence of hypertension

Blood pressure measurements were done to all the study subjects to check for hypertension. The mean systolic and diastolic BP results were 125.7 mmHg (± 16 SD) and 79.7 mmHg (± 9.2 SD).The overall prevalence of hypertension was 28.3% (95% CI 24.5, 32.5). Among all hypertensive people identified, 88 (63.8%) did not know they have had hypertension (newly screened). Of the 50 hypertensive people who reported using anti-hypertensive medications during data collection period, 34.0% had normal BP on measurement (Table  2 ).

Factors associated with hypertension

Having family history of hypertension, having high level of income, being male, being below grade 12, and having BMI ≥ 25 were significantly associated with hypertension for the overall study participants (Table  3 ). Among all, those who have family history of Hypertension were nearly six times more likely to be hypertensive when compared to those who haven’t [Adjusted OR 5.7; 95% CI (2.9, 10.9)], those who had high level of income were three times more likely to be hypertensive when compared to those who had low level of income [Adjusted OR 3.1; 95% CI (1.5, 6.3)], those who are male were 2.4 times more likely to be hypertensive when compared to those female participants[Adjusted OR 2.4; 95% CI (1.3, 4.3)], those who were below grade 12 were two times more likely to be hypertensive when compared to those who are above grade 12 [Adjusted OR 2.2; 95% CI (1.2, 3.9)], and those who had BMI ≥ 25 were two times more likely to be hypertensive when compared to those who had BMI < 25 [Adjusted OR 2.0; 95% CI (1.1, 3.5)]. The other variables were not significantly associated with hypertension after adjusting for confounders (Table  3 ).

Dietary habits of respondents

About 49% of the study subjects eat meat and eggs at least two to four times a week. While 39% of the respondents eat oil and fats at least two to four times a week. Regarding the frequency of consumption of sugars and sweets; 89 (18.3%) eat two to four times per week, and only 43 (9%) eat at least once a day. Majority of the respondents 92.4, 98.2, and 85.2% eat breakfast, lunch, and dinner on daily basis respectively. Concerning to the frequency of eating of deep fries; 327 (67.1%) eat sometimes, 130 (26.7%) had never eaten deep fries, and 30 (6.2%) eat daily. Two hundred forty one (49.5%) had never eaten any visible fat in a meat, while 234 (48.0%) eat any visible fat in a meat sometimes, and the rest 12 (2.5%) eat daily.

Physical activity

Among the 455 study participants who respond about their physical activity, 264 (58.0%) had low level of physical activity, 124 (27.3%) had moderate level of physical activity, and 67 (14.7%) had high level of physical activity. Thirty two (6.6%) didn’t respond to the physical activity variable.

Anthropometric measurements

The mean and median heights of the study participants were 1.65 m whereas; the mean and median weights of the study participants were 65.2 and 63 kg respectively. Hence, the mean and median BMI of the study participants were 23.9 and 23.3 kg/m 2 old respectively. Furthermore, the mean and median waist circumferences of the study participants were 82.1 and 80 cm respectively, while the mean and median hip circumferences of the study participants were 90.6 and 91 cm respectively. Therefore, the mean and median waist-to-hip ratio (WHR) of the study participants was 0.92, and 0.90 respectively. Regarding the centrally obesity of the study participants, 335 (68.8%) were centrally obese.

This study provides information regarding the prevalence and associated factors of hypertension among adults in living in the Semi-pastoralist community of eastern Ethiopia. It has demonstrated a 28.3% prevalence of hypertension. The present study depicts that having family history of Hypertension, having high level of income, being male, being above grade 12, and having BMI ≥ 25 were significantly associated with hypertension.

The prevalence of hypertension by self-report and physical measurement was 10.3 and 24.9%, respectively. More than twofold difference between the two measures indicates that a significant number of the population was not aware of their hypertension status which calls for appropriate and timely intervention. It is known that most individuals with high blood pressure do not have symptoms until complication arises to result in sudden death from heart attack or sudden intracranial bleeding or developed severe disability such as stroke as well as heart failure.

The overall prevalence of hypertension in our study was 28.3% which is consistent with the most recent community-based studies in Ethiopia and Zambia (28.3% in Gondar city, and 30% in Addis Ababa, and 31.8% in Zambia ) [ 6 , 7 , 9 ]. However it is significantly higher than the findings of the study done in south west Ethiopia (13.2%), and slightly higher than that of Jimma, Ethiopia (21.3%), Uganda (22%) and Tanzania 23.7% [ 10 , 11 , 12 , 13 ]. This could partly be due to the fact that, this study was conducted only in an urban setting, whereas the study conducted in south west Ethiopia was conducted in both urban and rural settings as well as the age difference in the study populations, and that of Uganda and Tanzania were conducted in rural settings.

In our study, individuals with positive family history of hypertension were more likely to be hypertensive. In agreement with this, many other previous studies [ 14 , 15 , 16 ] reported that family history of hypertension was significantly associated with being hypertensive in this study. This could be explained by the fact that genetic factors account for one-third to one-half of the risk of hypertension. Blood relatives tend to have many of the same genes that can predispose a person to high blood pressure, heart disease, or stroke [ 17 , 18 ]. Moreover, the tendency of individuals to follow risky life styles of their family could have also played a role for this association.

This study showed highest risk of hypertension among subjects who have high level of income. Some studies showed that the income distributions and hypertension were nonlinear indicating elevated levels in low income as well as in high income groups [ 19 , 20 , 21 ]. In the present study, being male was more likely to be hypertensive. This finding is in line with previous research reports [ 7 , 22 , 23 , 24 ]. Participants who were below grade 12 were more likely to be hypertensive in this study. However, this study tried to see educational status by re-categorizing to above grade 4 and below 4 or above grade 8 and below grade 8, but there was no association at all. This finding is consistent with the results from previous studies [ 25 , 26 , 27 ] that reported the positive relationship between hypertension and low education. Such association may be due to lack of awareness of risk factors of hypertension [ 28 ] as a result of the low educational status.

Participants with a BMI ≥ 24.9 were more likely to be hypertensive compared to those with a BMI of 24.9 or lower, which is consistent with multiple previous studies that have reported a strong association between hypertension and BMI [ 6 , 22 , 29 , 30 , 31 ]. Obesity is a well-established risk factor for hypertension [ 32 , 33 , 34 , 35 ]. Frequently used measures of obesity are BMI, skin fold thickness, estimation of per cent body fat and body weight and hip-waist ratio [ 36 ]. Obesity has been recognized as the most important risk factor for developing hypertension. Several epidemiological studies from different populations have reported a significant association between obesity and hypertension [ 23 , 37 , 38 , 39 , 40 , 41 ]. The link between obesity and hypertension is through neuro-endocrine mechanisms and most recently, factors derived from adipose tissue are thought to play a major role.

The study has a number of strengths including being a community based study which can truly describe the general population in contrast to the many reports that have emanated from hospital based studies. The main limitation of this study is that it is a simple cross-sectional, and didn’t include variables such as psychological stress and biochemical measurements. Hence other analytic studies that incorporate biochemical measurements should be carried out in order to assure the temporal relationship between hypertension and the explanatory variables. Moreover, there is a need to carry out research on the reasons for difference in prevalence of hypertension among male and female.

Conclusions

Findings of this study indicate that hypertension has become an important public health problem among adults in jigjiga city, with a huge discrepancy in the proportion of those who were newly screened and those who are known hypertensive subjects. This may indicate a hidden epidemic that underscores the need for comprehensive evaluation of prevalence of hypertension and other cardiovascular diseases in this population. If established with more robust and nationally representative studies, the finding calls for efficient health screening and regular checkups as well as interventions promoting healthy lifestyles. Certain factors like family history of hypertension, having high level of income, being male, being above grade 12, and having BMI ≥ 25 were found to be associated with high BP. Therefore, community based screening programs for Hypertension and its risk factors need to be carried out. Especially there is a need for routine screening for hypertension for those overweight or obese, low level educational status, those with positive family history of hypertension and high level of income, as they have an increased likelihood of developing hypertension.

Abbreviations

body mass index

blood pressure

coronary heart disease

diastolic blood pressure

diabetes mellitus

non-communicable diseases

systolic blood pressure

simple random sampling

World Health Organization

waist-to-hip ratio

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Authors’ contributions

FT and HA were involved in proposal writing, designed the study and participated in coordination, supervision and the overall implementation of the project, analyzed the data, drafted and finalized the manuscript. EB participated in designing the study, supervision and revision of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Our heartfelt thanks go to the Jigjiga University for funding this research without which it would not have been materialized. We would also like to thank Somali Health Bureau and all the Kebele administrative of Jigjiga for allowing us to carry out this study. Above all, we are grateful to the data collectors, supervisors and study participants for their full cooperation during data collection. This thesis would have not been possible without their involvement.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its Additional files 1 , 2 .

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Not applicable.

Ethics approval and consent to participate

The study protocol was reviewed and approved by the research and publication technology transfer committee of Jigjiga University which had the authority to approve ethics for scientific study. Written informed consent was obtained from each participant and confidentiality was maintained. Lastly, those with high blood pressure were advised and referred to the nearby health facility for further diagnosis and treatment by giving a referral note.

This work was funded by Jigjiga University. The sponsors of this study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to the data in the study and had full responsibility for the decision to submit.

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Henok Asresahegn and Frew Tadesse had the same role throughout the study

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School of Public Health, College of Health Sciences and Medicine, Jigjiga University, Jigjiga, Ethiopia

Henok Asresahegn & Frew Tadesse

School of Medicine, College of Health Sciences and Medicine, Jigjiga University, Jigjiga, Ethiopia

Ermias Beyene

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Corresponding author

Correspondence to Frew Tadesse .

Additional files

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Additional file 1. Hypertension data set. SPSS data set for the research entitled “Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study”.

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Additional file 2. Questionnaire hypertension BMC RN. Study tool for the research entitled “Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study”.

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Asresahegn, H., Tadesse, F. & Beyene, E. Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study. BMC Res Notes 10 , 629 (2017). https://doi.org/10.1186/s13104-017-2966-1

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Received : 03 September 2016

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Published : 28 November 2017

DOI : https://doi.org/10.1186/s13104-017-2966-1

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Prevalence and predictors of hypertension: Evidence from a study of rural India

Affiliation.

• 1 Department of Community Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
• PMID: 35495805
• PMCID: PMC9051678
• DOI: 10.4103/jfmpc.jfmpc_967_21

Background: Raised blood pressure (BP) is the leading global risk factor for cardiovascular diseases and a major cause of premature death. Worldwide, one in four men and one in five women are hypertensive. For effective preventive strategy, understanding of predictors of hypertension is necessary.

Objective: To assess prevalence and predictors of hypertension in the rural adult Indian population.

Material and methods: This cross-sectional study was carried out on 425 rural subjects (25-64 years) of the Varanasi district in India selected through multistage sampling. Blood pressure of each subject was measured using a standard technique. Sociodemographic data and predictors of hypertension were assessed by interviewing subjects with help of a predesigned and pretested proforma.

Results: Prevalence of hypertension was 31.5% (95% CI: 27.1-35.9). There existed a significant ( P < 0.05) association of BP with age, educational status, occupation, socioeconomic class, tobacco consumption, waist circumference, waist-hip ratio, and nutritional status. No significant association was found with gender, religion, caste, marital status, type and size of family, family without NCDs, awareness of screening camps for NCDs and national program for prevention and control of cancer, diabetes, cardiovascular diseases and stroke, and alcohol consumption. Significant association of education, nutritional, and occupational status obtained in univariate analysis got eliminated in the logistic model. Risk of hypertension was higher in the 45-64 years age group (AOR: 3.06; 95% CI: 1.75-5.35) and in socioeconomic class IV and V (AOR: 2.24; 95% CI: 1.17-4.31).

Conclusion: Prevalence of hypertension in the rural population was high and most of the observed predictors were modifiable.

Keywords: BMI; cardiovascular diseases and stroke; diabetes; hypertension; national program for prevention and control of cancer; noncommunicable diseases; waist circumference; waist-hip ratio.

Copyright: © 2022 Journal of Family Medicine and Primary Care.

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There are no conflicts of interest.

Distribution of family history of…

Distribution of family history of NCDs and self-reported NCDs

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• v.4(3); 2021 Sep

Prevalence of and risk factors for hypertension in Ethiopia: A systematic review and meta‐analysis

Endalamaw tesfa.

1 Department of Biochemistry, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar Ethiopia

2 Biotechnology Research Institute, Bahir Dar University, Bahir Dar Ethiopia

Dessalegn Demeke

3 Department of Physiology, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar Ethiopia

Associated Data

All data pertaining to this study are contained and presented in this document and in the supplementary files.

A number of epidemiological studies were performed to know the prevalence of and the risk factors for hypertension. However, these studies reported inconsistent results. As a result, this systematic review and meta‐analysis were planned to generate representative data on the prevalence of and risk factors for hypertension among the Ethiopian adult population.

Five electronic databases, namely, PubMed, Science Direct, Google Scholar, Hinari, and African Journals Online, were searched for studies published in English from 1 January 2010 to 31 August 2020. Joanna Briggs Institute Meta‐Analysis of Statistics Assessment and Review Instrument and Newcastle‐Ottawa scale were used for data extraction and quality assessment for this review. Stata version 14 statistical software was used for the analysis, and due to high heterogeneity a random effects model was used for meta‐analysis at 95% confidence interval (CI).

In this review, 35 observational studies were included. The pooled prevalence of hypertension in Ethiopia was 20.63% (95% CI [18.70, 22.55]) with the I 2 value of 96.1%. Older age (≥40 years) (adjusted odds ratio [AOR]: 3.46 [95% CI: 2.67, 4.49]), urban residence (AOR: 1.47 [95% CI: 1.28, 1.70]), educational status less than grade 12 (AOR: 1.67 [95% CI: 1.38, 2.01]), family history of hypertension (AOR: 4.33 [95% CI: 2.95, 6.34]), diabetes mellitus (DM) (AOR: 5.18 [95% CI: 3.01, 8.88]), body mass index (BMI) ≥25 (AOR: 3.79 [95% CI: 2.61, 5.50]), central obesity (AOR: 1.91 [95% CI: 1.09, 3.36]), and alcohol consumption (AOR: 1.72 [95% CI: 1.26, 2.34]) were the identified risk factors for hypertension.

The pooled prevalence of hypertension is relatively higher as compared to the previous reports in Ethiopia. Older age, urban residence, lower educational coverage, family history of hypertension, DM, BMI ≥25, alcohol consumption, and central obesity were the risk factors for hypertension. The governments and stakeholders should design an appropriate strategy to prevent and control the disease in the Ethiopian population.

Abbreviations

1. introduction.

Hypertension is the leading preventable causes of cardiovascular disease, premature death and disability worldwide. The incidence of hypertension is increased globally, particularly in low‐ and middle‐income countries. 1 The prevalence of hypertension is widely variable and it ranges from 13% to 41% due to the difference of risk factors. 2 In 2010, about 1.39 billion people became hypertensive worldwide. 1 , 3 Based on the systematic review, including studies from 90 countries, the prevalence of hypertension was 31.1% and high prevalence of hypertension was observed in low‐ and middle‐income countries as compared to high‐income countries (31.5% and 28.5%, respectively). 3

Hypertension is a multifactorial disease, and it is believed that the interaction of an individual's genetic makeup and different environmental factors involved in the pathogenesis of the disease. 4 Advanced age, 5 being overweight or body mass index (BMI) ≥25, 5 , 6 , 7 diabetes mellitus (DM), being physically inactive or following sedentary life style, 8 cigarette smoking, alcohol consumption, 5 , 9 stress, 10 positive family history or presence of susceptible genes, 7 consumption of saturated fats, consumption of excess salt, and lack of fruits and vegetables 11 were the known risk factors for hypertension.

In Ethiopia, nationwide cohort studies that showed the incidence of and risk factors for hypertension among the adult population were not conducted. Although, different epidemiological studies were performed and reported wider variation in the prevalence of hypertension ranging from 7.7% 12 to 41.9% in the adult population ,13 conducting this review is necessary to generate summarized information on the prevalence of and risk factors for hypertension. Kibret and his colleagues conducting a systematic review and meta‐analysis and reported the prevalence of hypertension in Ethiopia is about 19.6% 14 which is lower than the global report of hypertension prevalence (24.1%). 15

The previous review includes nine cross‐sectional studies, which do not represent the whole region of the country. To the best of our knowledge, there is no up‐to‐date published systematic review and meta‐analysis study that shows the risk factors and the prevalence of hypertension in the Ethiopian adult population. Therefore, the current review was planned to generate updated information on the prevalence of and risk factors for hypertension in Ethiopia by including more articles published from 1 January 2010 to 31 August 2020.

2. METHODS AND MATERIALS

2.1. protocol and registration.

This review protocol is registered at the National Institute for Health Research; PROSPERO international prospective register of systematic reviews with registration number CRD42020203758 at https://www.crd.york.ac.uk/prospero/#recordDetails .

2.2. Study design and search strategy

A systematic review and meta‐analysis of published studies were conducted to assess the prevalence of and risk factors for hypertension in Ethiopia. We searched the following databases: PubMed, ScienceDirect, Hinari, African Journals Online (AJOL), and Google Scholar. The search was performed by using Medical Subject Heading (MeSH) terms such as “Prevalence, risk factors, hypertension and Ethiopia ” and free terms such as high blood pressure, associated factors, and determinants separately or in combination (Appendix S1 ). All published articles from 1 January 2010 to 31 August 2020 were retrieved and assessed for their eligibility for their inclusion in this review. The preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guideline was utilized to conduct this systematic review and meta‐analysis.

2.3. Eligibility criteria

Inclusion and exclusion criteria are given as follows;

• Studies conducted on the adult population in Ethiopia were included.
• Articles reporting the prevalence of or risk factors for hypertension were included.
• Articles published in English from 1 January 2010 to 31 August 2020 were included.
• Community‐based and health institution‐based cross‐sectional studies were included.
• Conference papers, editorials, reviews, case‐control, cohort, and randomized trial studies were excluded from this review.

2.4. Study selection and screening

All citations identified by our search strategy were exported to EndNote X9 and duplicate articles were removed. And then the titles and abstracts of the identified articles were screened by two independent reviewers, and eligible studies were included for further review. The full texts of selected articles were retrieved and read thoroughly to ascertain the suitability prior to data extraction. In case of disagreement between the two reviewers, discussion was held to reach consensus. The search process was presented in the PRISMA flowchart that clearly shows the studies that were included and excluded with reasons of exclusion (Figure  1 ). 16

Flow diagram showing the eligibility of studies included in the review of prevalence of and risk factors for hypertension

2.5. Definition of outcome interest

The primary outcome of this study was to assess the prevalence of hypertension in Ethiopia.

• Hypertension: Systolic blood pressure ≥140 mm Hg and/or diastolic ≥90 mm Hg that is measured at least two times within 4‐hour interval. 17

The secondary outcomes of the current review were to assess the risk factors for hypertension such as age, sex, residence, educational status, family history of hypertension, DM, BMI, central obesity, alcohol consumption, physical inactivity, cigarette smoking, salt intake, and khat chewing in the Ethiopian population.

2.6. Quality assessment

We used the modified version Newcastle‐Ottawa scale (NOS) to assess the quality of the included studies for inclusion. 18 The NOS included three categorical criteria with a maximum score of 9 points. The quality of each study was rated using the following scoring algorithms: ≥7 points was considered “Good”‐quality study, 4 to 6 points was considered “Fair”‐quality study, and ≤3 points was considered “Poor”‐quality study. Accordingly, in order to improve the validity of this systematic review result, we only included primary studies with fair to good quality. 18

2.7. Data extraction process

The data extraction was performed using a tool developed by the 2014 Joanna Briggs Institute Reviewers' Manual data extraction form. 19 The abstract and full‐text were reviewed by the two independent reviewers. Author's name, publication year, study location, study design, sample size, age, sex, residence, educational status, family history of hypertension, DM, BMI, central obesity, alcohol consumption, physical inactivity, cigarette smoking, salt intake, and khat chewing were extracted for the assessment of risk factors and prevalence of hypertension in Ethiopia.

2.8. Data analysis

The data were entered into a Microsoft Excel sheet, and the meta‐analysis was performed using Stata 14 software. The forest plot of effect size and odds ratio were used to assess the prevalence of and risk factors for hypertension in Ethiopia at 95% CI. Standard error of prevalence (SEP) was calculated using the formula SEP = pq / n . Subgroup analysis was performed based on region and year of study. Variables such as age, sex, residence, educational status, family history of hypertension, DM, BMI, central obesity, alcohol consumption, physical inactivity, cigarette smoking, salt intake and khat chewing were assessed to know their association with hypertension.

2.9. Heterogeneity and Publication bias

Statistical heterogeneity was estimated through Cochrane Q, I 2 statistic and P‐value. If I 2 statistic value is <25%, 25%‐50%, and ≥50%, it represents low, medium, and high heterogeneity, respectively. In this review, a random effects model (REM) was used for analysis due to high heterogeneity. To know the cause heterogeneity subgroup analysis and sensitivity test were performed and presented in the supporting files (Apendix S2 ). In addition, publication bias was assessed through the funnel plot and Egger test (Appendix S3 ).

3.1. Study selection

A total of 2836 articles were retrieved through electronic search by using different search terms of which 1584 articles were eligible for title and abstract assessment after the removal of 1252 duplicate records. Of 1584 articles screened for eligibility, 1508 records were excluded based on their title and abstract assessment. A total of 76 articles underwent full‐ text assessment for their eligibility, 41 studies were excluded due to different reasons (24 studies did not fulfill the inclusion criteria, 13 articles did not report the outcome variable, and two articles were repeated publication and the other two were review articles).

3.2. Study characteristics

In this review a total of 35 cross‐sectional studies were included. 12 , 13 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 Ten studies were conducted in the Amhara region, nine studies were performed in Southern Nations Nationalities and Peoples' Region (SNNPR), seven studies were conducted in Addis Ababa, three studies were conducted in the Tigray region, two studies were conducted in the Oromia region, and the other four studies were conducted in Somalia region, Harari region, and Dire Dawa, and as a national level. In this review, a total of 39 860 study participants were included (Table  1 ).

Characteristics of research articles included in the systematic review and meta‐analysis (N = 35)

Abbreviations: AA, Addis Ababa; HTN, Hypertension; SE, standard error; SNNPR, Southern Nations, Nationalities, and People's Region.

3.3. Prevalence of hypertension in Ethiopia

A wider difference in the prevalence of hypertension was observed in the studies included in this systematic review and meta‐analysis. A lower prevalence (7.7%) of hypertension was reported in the study conducted in the Amhara region, 12 and a higher prevalence (41.9%) of hypertension was observed in the Harari region. 13 The overall pooled prevalence of hypertension in Ethiopia was 20.63% (95% CI: [18.70%, 22.55%]). In this review, 35 articles were included to estimate the pooled prevalence of hypertension in Ethiopia (Figure  2 ).

Forest plot of pooled prevalence of hypertension in Ethiopia. Note : Weights are from random effects analysis

3.4. Subgroup analysis of hypertension prevalence in Ethiopia

The subgroup analysis of hypertension prevalence by region showed the highest pooled prevalence of 22.81 (9.90, 35.72) at 95% CI in the Oromia region followed by the SNNP region (22.11) (19.07, 25.15) at 95% CI. The lowest prevalence of hypertension was observed in the Tigray region (16.68) (15.32, 18.05) at 95% CI. The subgroup analysis of hypertension by the year of study had shown the highest pooled prevalence of 23.84 (19.76, 27.92) at 95% CI in the studies conducted from 2019 to 2020. This indicates that the current trend of hypertension has increased compared with the studies conducted from 2013 to 2015 ( Table  2 ).

Subgroup analysis of hypertension prevalence in Ethiopia

3.5. Risk factors for hypertension in Ethiopia

In this systematic review and meta‐ analysis different risk factors such as age, sex, residence, educational status, family history of hypertension, DM, BMI, central obesity, alcohol consumption, physical inactivity, cigarette smoking, salt intake and khat chewing were evaluated for their association with hypertension.

3.5.1. Association between age and hypertension

In this subcategorical analysis, 20 studies were included for the assessment of age as a risk factor for hypertension. 20 , 22 , 24 , 25 , 26 , 27 , 28 , 30 , 31 , 32 , 33 , 37 , 38 , 42 , 43 , 44 , 49 , 50 , 51 , 52 Nineteen of the included studies showed a statistically significant association between older age (≥40 years) and hypertension. 20 , 24 , 25 , 26 , 27 , 28 , 30 , 31 , 32 , 33 , 37 , 38 , 42 , 43 , 44 , 49 , 50 , 51 , 52 However, one study showed nonsignificant association between older age (≥40 years) and hypertension. 22 The pooled meta‐regression analysis showed that there is a statistically significant association between older age (≥40 years) and hypertension, with the odds of 3.46 (95% CI: 2.67, 4.49) (Figure  3 ).

Forest plot of odds ratio for the association of age ≥40 years with hypertension. Note : Weights are from random effects analysis

3.5.2. Association between sex and hypertension

In this subcategorical analysis, 17 studies were included for the assessment of sex as a risk factor for hypertension. 12 , 21 , 22 , 25 , 26 , 28 , 29 , 30 , 31 , 32 , 33 , 35 , 40 , 42 , 44 , 45 , 52 Six of the included studies showed a statistically significant association between male sex and hypertension, 12 , 28 , 29 , 30 , 31 , 45 whereas three studies 32 , 35 , 44 showed a lower risk of hypertension in male sex and eight studies 21 , 22 , 25 , 26 , 33 , 40 , 42 , 52 showed non‐ significant association between male sex and hypertension. The pooled meta‐regression analysis showed nonsignificant association between male sex and hypertension, with the odds of 1.18 (95% CI: 0.86, 1.62) ( Figure  4 ).

Forest plot of odds ratio for the association of male sex with hypertension. Note : Weights are from random effects analysis

3.5.3. Association between residence, educational status, and salt intake and hypertension

In this subcategorical analysis, 15 studies were included for the assessment of residence, educational status and salt intake as risk factors for hypertension. 21 , 22 , 26 , 27 , 28 , 30 , 32 , 33 , 42 , 43 , 44 , 45 , 50 , 52 The pooled meta‐regression analysis showed that there is a statistically significant association between urban residence and low education status (<Grade 12) with hypertension, with the odds of 1.47 and 1.67 (95% CI: 1.28, 1.70 vs 1.38, 2.01), respectively (Figure  5 ). However, the pooled meta‐regression analysis of salt intake showed nonsignificant association between salt intake and hypertension, with the odds of 2.70 (95% CI: 0.68, 10.73).

Forest plot of odds ratio for the association of residence, educational status, and salt intake with hypertension

3.5.4. Association between BMI and hypertension

In this subcategorical analysis, 19 studies were included for the assessment of BMI as a risk factor for hypertension. 12 , 13 , 20 , 24 , 26 , 27 , 28 , 29 , 30 , 33 , 35 , 37 , 40 , 42 , 43 , 44 , 49 , 50 , 52 Seventeen of the included studies showed a statistically significant association of BMI ≥25 with hypertension. 12 , 13 , 20 , 24 , 26 , 27 , 28 , 30 , 33 , 35 , 37 , 40 , 42 , 43 , 44 , 49 , 50 However, one study 29 showed lower risk and another study 52 showed nonsignificant association between BMI ≥25 and hypertension. The pooled meta‐regression analysis showed that there is a statistically significant association between BMI ≥25 and hypertension, with the odds of 3.79 (95% CI: 2.61, 5.50) ( Figure  6 ).

Forest plot of odds ratio for the association of BMI ≥25 with hypertension. Note : Weights are from random effects analysis

3.5.5. Association between physical inactivity and hypertension

In this subcategorical analysis, 12 studies were included for the assessment of physical inactivity as a risk factor for hypertension. 13 , 20 , 21 , 25 , 26 , 30 , 32 , 33 , 35 , 37 , 49 , 51 Eight of the included studies showed a statistically significant association among physical inactivity and hypertension, 13 , 20 , 21 , 30 , 32 , 33 , 35 , 49 whereas three studies 25 , 37 , 51 showed lower risk of hypertension and one study 26 showed nonsignificant association among physical inactivity and hypertension. The pooled meta‐regression analysis did not show a statistically significant association between physical inactivity and hypertension, with the odds of 1.24 (95% CI: 0.82, 1.88) (Figure  7 ).

Forest plot of odds ratio for the association of physical inactivity with hypertension. Note : Weights are from random effects analysis

3.5.6. Association between alcohol drinking and hypertension

In this subcategorical analysis, 13 studies were included for the assessment of alcohol drinking as the risk factor for hypertension. 20 , 21 , 24 , 28 , 29 , 30 , 31 , 32 , 33 , 35 , 44 , 49 , 51 Eight of the included studies showed a statistically significant association between alcohol drinking and hypertension, 20 , 24 , 28 , 29 , 30 , 31 , 35 , 44 whereas one study 51 showed a lower risk of hypertension among and four studies 21 , 32 , 33 , 49 showed non‐ significant association among alcohol drinking and hypertension. The pooled meta‐regression analysis showed that there is a statistically significant association between alcohol drinking and hypertension, with the odds of 1.72 (95% CI: 1.26, 2.34) (Figure  8 ).

Forest plot of odds ratio for the association of alcohol drinking with hypertension. Note : Weights are from random effects analysis

3.5.7. Association between family history of hypertension and hypertension

In this subcategorical analysis, 11 studies were included for the assessment of family history of hypertension as a risk factor for hypertension. 13 , 20 , 24 , 26 , 27 , 37 , 40 , 42 , 44 , 50 , 52 Ten of the included studies showed a statistically significant association between family history and hypertension. 13 , 20 , 24 , 26 , 27 , 37 , 40 , 42 , 44 , 50 However, one study 52 showed non‐ significant association with hypertension. The pooled meta‐regression analysis showed that there is a statistically significant association between family history of hypertension and occurrence of hypertension, with the odds of 4.33 (95% CI: 2.95, 6.34) (Figure  9 ).

Forest plot of odds ratio for the association of family history of hypertension with hypertension. Note : Weights are from random effects analysis

3.5.8. Association between DM and central obesity with hypertension

For the assessment of DM and central obesity as a risk factor of hypertension 14 studies were included. 20 , 24 , 26 , 27 , 28 , 31 , 32 , 33 , 40 , 49 , 52 Seven of the included studies showed a statistically significant association between DM and hypertension. 20 , 24 , 26 , 27 , 28 , 40 , 49 For central obesity, four studies 28 , 32 , 33 , 49 showed significant association, whereas three studies 26 , 31 , 52 showed nonsignificant association between central obesity and hypertension. The pooled meta‐regression analysis showed that there is a statistically significant association between DM and central obesity with hypertension, with the odds of 5.18 and 1.91(95% CI: 3.02, 8.88 vs 1.09, 3.36), respectively (Figure  10 ).

Forest plot of odds ratio for the association of DM and central obesity with hypertension

3.5.9. Association between cigarette smoking and khat chewing and hypertension

In this subcategorical analysis, 14 studies were included for the assessment of cigarette smoking and khat chewing as the risk factors for hypertension. 20 , 21 , 24 , 28 , 32 , 33 , 40 , 43 , 49 The pooled meta‐regression analysis showed nonsignificant association between cigarette smoking and khat chewing with hypertension, with the odds of 1.16 and 1.12 (95% CI: 0.62, 2.16 vs 0.46, 2.73), respectively ( Figure  11 ).

Forest plot of odds ratio for the association of cigarette smoking and khat chewing with hypertension

3.6. Sensitivity analysis and publication bias

A sensitivity test was performed by omitting one study at a time to assess the stability of the results. There was no significant change in the pooled prevalence of hypertension after excluding one of the included studies at 95% CI (Appendix S2 ). This means there is no individual study that excessively influences the pooled prevalence of hypertension. The funnel plot did not show evidence of publication bias (Appendix S3 ).

4. DISCUSSION

This review was conducted to determine the pooled prevalence of and risk factors for hypertension in Ethiopia. In this meta‐ analysis the pooled prevalence of hypertension was 20.63% at 95% CI. This is almost similar to the previous meta‐analysis reported by Kibret and his colleagues which was 19.60% (95% CI: 13.7%, 25.50%). 14 Similar finding was also reported in the coos‐sectional study conducted in Cameron (19.8%). 53 However, the prevalence of the current review was lower than that of the studies conducted in Sudan and the global age standardized hypertension prevalence report were 40.8% and 24.1%, respectively. 15 , 54 The difference might be due to the reason that an older age of the study participants involved in the Sudanese study as compared to our review.

In the current review, a number of risk factors were assessed to know their association with hypertension in the Ethiopian adult population. Age is an important risk factor for hypertension and is assessed for its association with hypertension by classifying age ≥40 and <40 years. Hence, in our study older age (age ≥40 years) was significantly associated with hypertension as compared to younger age (age <40 years) with the odds of developing hypertension 3.46 times more. Supporting evidences were reported in the studies conducted in Eastern Sudan and China. 7 , 54 The incidence of high blood pressure or hypertension is increased as the age of an individual increased due to structural changes in the arteries and decreased its elasticity because of age‐related gene expression. 55

In this study, residence and educational status were significantly associated with hypertension in the Ethiopian adult population. Urban residence and low educational status (<Grade 12) significantly increased the risk of developing hypertension as compared to rural dwellers and high educational status (≥Grade 12) with the odds of 1.47 and 1.67, respectively. Supporting evidences were reported in the studies conducted in China and Korea. 5 , 7 This might be due to the difference in the level of understating in living style and eating healthy diet among urban and rural dwellers and also in low and high educational status. In the current study, the sex of the study participants did not show statistically significant association between male sex and hypertension. However, in the studies conducted in Sudan and India showed that females less likely become hypertensive than males this might be due to the protective effects of estrogen until menopause. 56 , 57

Dyslipidemia and obesity are important risk factors for hypertension, DM and cardiovascular diseases. In this study, central obesity and BMI ≥25 showed statistically significant association with hypertension as compared to non‐central obese and BMI <25 with the odds of 1.91 and 3.79 times, respectively. Similar results were obtained in the studies conducted in South Asia, Eastern Sudan and China. 54 , 58 , 59 , 60 Elevated levels of total cholesterol, low‐density lipoprotein cholesterol (LDL‐c), and non‐high‐density lipoprotein cholesterol (non‐HDL‐c) increased the risks of hypertension due to structural and functional changes in the blood vessel property and atherosclerosis. 61 Evidence from the meta‐analysis study showed that obesity increased the risk of hypertension 3.82 times. 6

Hypertension and DM are closely associated, even though the causal effect relationship between the two is not as such clear. In the study conducted in Korea, hypertension was reported as a significant risk factor for type 2 DM. 62 High blood glucose level increased the risk of hypertension through decreasing blood vessel elasticity, increasing the circulating fluid by impairing kidney function and by increasing insulin resistance. 63 In our study, DM is significantly associated with hypertension as compared to patients without DM with the odds of 5.18 at 95 CI. Similar levels of evidences were reported in the studies conducted in Kenya and Ethiopia. 27 , 64

In the current review, alcohol drinking showed a statistically significant association with hypertension as compared to nondrinkers with the odds ratio of 1.72 times at 95 CI. Similar levels of evidences were obtained in the longitudinal cohort studies conducted in Brazil and China. 9 , 65 The mechanisms of alcohol consumption raises pressure remains unclear, but the genetic variant in alcohol metabolizing enzymes and environmental factors play a major role in hypertension. 66 Factors such as activation of the sympathetic nervous system, impairment of the baroreceptors, increased vascular stimulation of the endothelium and loss of relaxation due to oxidative stress of the endothelium involved in the pathogenesis of hypertension. 6

Hypertension is a complex multifactorial disorder resulted from an interaction between an individual's genetic makeup and environmental factors. The genetic influence of hypertension in a given individual reaches about 30%‐60%. 67 Genome‐wide association studies were identified a list of common genetic variants associated with blood pressure regulation and hypertension. 68 In this review, family history of hypertension significantly associated with hypertension as compared to patients without positive family history of hypertension with the odds of 4.33 at 95% CI. Supporting levels of evidence were reported in the study conducted in China. 69 A study conducted in India, showed that angiotensinogen gene variants and their haplotypes were positively associated with the causation of hypertension. 70

Physical inactivity, is an important risk factor for noncommunicable diseases such as obesity, DM, hypertension, cardiovascular disease, and metabolic syndrome. In the current study, cigarette smoking, physical inactivity, salt intake, and khat chewing did not show statistically significant association with hypertension. However, the studies conducted in Sudan and Ethiopia showed a significant association between physical inactivity and hypertension. 27 , 57 This might be due to the problems related to the lack of operationalization about physical exercise or physical inactivity in the studies included in our review. In this review, salt intake increased the risks of developing hypertension by 2.4‐fold as compared to the person not taking salt, but the association is not statistically significant. This might be due to a small study effect; few studies were included for assessing this factor.

5. LIMITATION

This systematic review and meta‐analysis showed the current pooled prevalence of and the risk factors for hypertension in Ethiopia. In addition, it provides updated baseline information on the prevalence of and risk factors for hypertension in the Ethiopian adult population for the scientific community. Moreover, this review includes 35 cross sectional studies which are high in number gives a representative data of the national prevalence but the search strategy may miss unpublished articles; publication bias likely occurs. The search strategy may miss unpublished articles; publication bias likely occurs. In addition, high statistical heterogeneity observed might be due to publication bias. The included studies lack consistency to include more articles for a particular variable of risk factor that may lead to a small study effect. These together reduce the quality of the generated evidence.

6. CONCLUSION

The pooled prevalence of hypertension was slightly higher as compared to the previous report of hypertension in Ethiopia. In the subgroup analysis, the highest prevalence of hypertension was observed in studies conducted in the Oromia region and in the studies conducted between 2018 and 2020. Age ≥ 40 years, urban residence, lower educational status (<Grade 12), family history of hypertension, DM, BMI ≥25, central obesity, and alcohol consumption were identified as the risk factors for hypertension. Cigarette smoking, physical inactivity, khat chewing, salt intake, and sex did not show any statistically significant association with hypertension in the Ethiopian adult population. The governments and stakeholders should design a strategy to reduce the prevalence of hypertension in Ethiopia. In addition, large‐scale prospective cohort studies should be needed to identify risk factors for hypertension in Ethiopia.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest regarding this research.

AUTHOR CONTRIBUTIONS

Conceptualization: Endalamaw Tesfa

Data Curation: Endalamaw Tesfa and Dessalegn Demeke

Investigation: Endalamaw Tesfa, and Dessalegn Demeke

Methodology: Endalamaw Tesfa

Supervision: Dessalegn Demeke

Visualization: Endalamaw Tesfa and Dessalegn Demeke

Writing Original Draft Preparation: Endalamaw Tesfa and Dessalegn Demeke

Writing Review and Editing the Final Manuscript: Endalamaw Tesfa, and Dessalegn Demeke

All authors have read and approved the final version of the manuscript.

AVAILABILITY OF DATA AND MATERIALS

Ethics statement.

Ethical approval was not required for this study.

Supporting information

Appendix S1. Search strategy of the review.

Appendix S2. Sensitivity test of the review.

Appendix S3. Funnel plot of the review.

ACKNOWLEDGMENT

Not applicable.

Tesfa E, Demeke D. Prevalence of and risk factors for hypertension in Ethiopia: A systematic review and meta‐analysis . Health Sci Rep . 2021; 4 :e372. doi: 10.1002/hsr2.372 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Funding information No fund was received for this study.

Prevalence of hypertension in Ethiopia: A systematic meta-analysis

• December 2015
• Public Health Reviews 36(1)

• Deakin University

• The University of Newcastle, Australia

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