Hypertension is one of the leading public health problems globally. About half of the deaths from cardiovascular diseases were attributed to hypertension in 2008. Reduction of blood pressure to normal range is one of the major challenges in preventing complications and future burden of cardiovascular diseases. Therefore, this study aims to determine prevalence, awareness, treatment and control of hypertension and its associated factors in Nepal.
This was a community based cross-sectional study conducted as a part of a community based intervention trial in Birendranagar Municipality of Surkhet district located at the Mid-western region of Nepal. We enrolled 1159 subjects aged 30 years and above. Out of 12 wards (administrative unit), four wards were selected randomly. Three hundred participants were recruited from each selected ward. Trained enumerator collected socio-demographic, anthropometric, and clinical data using standard STEPS questionnaires.
Out of all participants, women were 71% and mean age was 47±12.6 years. The overall prevalence of hypertension was 38.9% (95% CI: 36–41.7) while age and sex adjusted prevalence was 40.6%. The hypertension was present in 48.1% (95% CI: 45.2–50.9) of men and 35.2% (95% CI: 32.4–37.9)] of women. Male gender (OR = 1.49), older age (OR = 1.04 per year), Dalit caste (OR = 1.71), past history of cigarettes smoking (OR = 2.78), current alcohol consumption (OR = 1.75), and raised body mass index (OR = 1.17 per unit) were identified as significant factors associated with hypertension. Of total hypertensive respondents, 53.4% (95% CI: 48.7–58) were aware, 29% (95% CI: 24.8–33.1) were receiving treatment for high blood pressure, and 8.2% (95% CI: 5.6–10.7) had controlled blood pressure. The awareness, treatment, and control status were worse in younger participants.
The study revealed high prevalence with low awareness, treatment, and control of hypertension in Nepal. Gender, age, ethnicity, smoking, drinking alcohol, and body mass index were associated with hypertension. Immediate public health and individual measures are warranted to reduce future burden of cardiovascular diseases.
Citation: Khanal MK, Dhungana RR, Bhandari P, Gurung Y, Paudel KN (2017) Prevalence, associated factors, awareness, treatment, and control of hypertension: Findings from a cross sectional study conducted as a part of a community based intervention trial in Surkhet, Mid-western region of Nepal. PLoS ONE 12(10): e0185806. https://doi.org/10.1371/journal.pone.0185806
Editor: Stefan Kiechl, Medizinische Universitat Innsbruck, AUSTRIA
Received: July 19, 2017; Accepted: September 19, 2017; Published: October 5, 2017
Copyright: © 2017 Khanal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All raw data files are available from the Dryad depository database (doi:10.5061/dryad.1rb14).
Funding: The study was supported by a fund from Nepal Family Development Foundation, Kathmandu, Nepal. YG received the funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Hypertension is one of the major risk factors of cardiovascular diseases and one of the leading causes for global mortality . Cardiovascular diseases accounted for one third of the total deaths a year in 2008. Out of these, 9.4 million deaths every year throughout the world were attributed to hypertension . If left uncontrolled, hypertension is responsible for 45% deaths due to heart disease and 51% deaths due to stroke. In addition, the raised blood pressure can cause chronic kidney disease, heart failure, diabetes, and other diseases . Globally, about 22% of adults aged 18 years and above had been diagnosed with hypertension in 2014. Prevalence was higher in low income countries compared to high income countries (30% in low income countries vs. 18% in Americas). The WHO estimated proportion of adults with high blood pressure was approximately 25% in South East Asia Region (SEAR) .
Nepal is one of the low income countries where nationally representative sample revealed that 25.7% of population aged 15–69 years suffered from hypertension in 2013 . Similarly, the proportion of hypertension among different populations of Nepal were 12.3% in rural Sindhuli , 27.7% in Dhulikhel , 28% in Pokhara , 32.5% in Kathmandu  within last three years. Despite the high prevalence, control of hypertension was low in Nepal and ranged from 11.7%  to 24% .
Evidence shows that lowering and controlling blood pressure has health benefits. For instance, 10 mm Hg reduction of systolic blood pressure is associated with 22% and 41% reduction in coronary heart disease and stroke, respectively . In the same way, prevention of different risk factors of hypertension contributed to 41–46% of the reduction in cardiometabolic mortality . Population data on prevalence, awareness, risk factors, treatment, and control are necessary for establishing the gap, planning, and implementation of strategies related to hypertension prevention and control in communities. However, on one side, a very few studies have been conducted, on the other side, these studies were carried out only in the central and eastern part of Nepal [7,10] and scarce information is available in the Mid-western region. Therefore, this study was conducted to determine prevalence, associated factors, awareness, treatment and control of hypertension in Mid-western region of Nepal.
Study design, setting, and study population
This was a cross-sectional study conducted as a part of a community based health education intervention trial (trial registration no: NCT02981251) in Birendranagar Municipality of Surkhet District of Nepal from January to December 2016. The city is an administrative and geographic centre of the Mid-western part of Nepal, about 600 kilometers west of the capital where 52,137 population are residing in poor urban planning setup . The city is inhabited by multicultural, multiethnic indigenous, and migrated population. This mixed population would be related to internal mobility (17% out of total migration of the region) of the Mid Western region . These heterogeneous people are residing in each ward of the municipality . Agriculture is the main source of income among the study population, followed by self-owned business and employment.
Men and women aged 30 years and above were included in the study. However, pregnant women and individuals who were bed-ridden, blind or deaf, diagnosed with kidney disease, cancer, heart disease, and mental illness were excluded from the study. As this study was the part of preventive health education program, we included the participants with essential hypertension and without complications.
Sample size and sampling technique
Based on 36.8% prevalence of hypertension among the population of 30 years and above  with the precision of 5% and the design effect of 1.5, we calculated unadjusted sample size as 530. We used design effect to address the limitation (loss of power of the study) while applying clustered sampling compared to simple random sampling .The obtained sample size was doubled to incorporate two strata of men and women. After adjustment for a 10% non response rate, the final estimated sample size was 1179. We used multistage clustered sampling technique where wards (smallest administrative unit) were considered as clusters. Out of 12 wards, four wards were selected randomly. Initially, we randomly selected the first household from the left-hand side of the main road. Data collector, then, visited the consecutive households to enroll 300 participants, who met the inclusion criteria, from the single ward. We repeated the same sample selection strategy in each ward.
We recruited 20 health professionals and trained them about the study tools and methods of data collection. Principle and co-investigators organized three days training session for the data collector followed by pre-testing to conform their understanding. Training sessions covered study objectives, methods, inclusion and exclusion criteria, process of inform consent, accurate application of data collection tools, and techniques. Data enumerator interviewed face-to-face and observed anthropometric and blood pressure measurements of the study participants to collect the data. We utilized WHO STEPS questionnaires  to collect information related to age, sex, socio-economic status, tobacco use, alcohol consumption, fruit and vegetable intake, salt intake, and physical activities. The data collector asked participants to provide the information regarding total teaspoons of salt consumed during last two days. In addition, we asked whether they had ever been told by health worker that they have raised blood pressure or hypertension and whether they were receiving treatment for hypertension in the previous two weeks before the data collection. Similarly, other questions were related to information of the history of known diabetes mellitus and the family history of hypertension. Questionnaires were pre-tested among 20 participants before final implementation.
Blood pressure measurements.
Trained data collectors measured the blood pressure using aneroid sphygmomanometer on the left arm. Appropriate cuff size was utilized based on upper arm circumference of the respondent. First reading was taken at least after 15 minutes of rest in uncrossed leg. Second measurement was obtained after the subject has rested for at least three minutes of the first measurement. If two readings were different, mean of two readings was used for final analysis [17,18].
Demographic and socio-economic variables.
Age was recorded in completed years and re-grouped into ten years interval. Divorced, widow or widowers were regarded as single besides married and unmarried condition for marital status. Ethnicity was categorized into Brahman, Kshetri, Shahi or Thakuri, Dalit, and Janajati based on caste. Education was categorized into no formal education (illiterate/informal education), primary (grade 1–5), secondary (grade 6–10), and higher (grade >11) level. Occupation was classified as employed (involved in job or running own business), household work, agriculture or construction worker, and unemployed. Poor economic status was defined as any participant whose family income per person per year was less than Rupees 16, 355 (US$: 16.3) .
Hypertension awareness, treatment, and control variables.
Hypertension was defined as average systolic blood pressure (SBP) ≥ 140 mm Hg and/or average diastolic blood pressure (DBP) ≥ 90 mm Hg and/or history of taking antihypertensive medication in the last two weeks . Awareness of hypertension was defined as self reported condition of hypertension that had been diagnosed by a doctor or other health worker prior to the data collection . Treatment of hypertension was defined as self reported use of any antihypertensive medication in last two weeks before the interview. Control of blood pressure was defined as SBP < 140 mm Hg and DBP < 90 mm Hg among hypertensive participants .
Variables related to behavior.
Questions related to smoking use were asked to identify current, past use along with the number of cigarettes they were smoking per day. Current smoker was defined as those who were smoking cigarettes and those who quit less than one month before the interview. Similarly, those who were chewing tobacco in last 30 days were defined as current tobacco users . Any respondent who drank alcohol within last 30 days of data collection was defined as current alcohol user. Total amount of alcohol intake was calculated in number of standard drinks (10 grams of pure ethanol). Number of servings of fruit and vegetable intake in a week was calculated with the help of pictogram. Sufficient intake of fruit and vegetable was considered if the participant consumed at least 400 grams or at least five servings per day . Salt intake was estimated by dividing total teaspoons of salt by total family members who shared food in last two days. The average teaspoon was multiplied by 5.69 grams to get the total amount of salt intake. Dietary salt intake of >5 grams was considered as high amount of salt .Amount of physical activities was calculated in metabolic equivalents of task (MET) per minutes per week. They were categorized into light (<3 MET), moderate (3–6 MET) and vigorous (>6 MET) with the local context and questions were asked to record for each subject. Physical activities equivalent to less than 600 MET-minutes per week was defined as inadequate level (physically less active) .
Height and weight were measured by portable stadiometer and weighing machine. Waist circumference (WC) was measured in a separate room in standing position, at the end of a normal expiration, holding the arms relaxed at the sides, and at midpoint between the lower margin of the last palpable rib and the top of the iliac crest (hip bone).Weight was read in nearest kilogram (Kg) while height and waist circumference were measured in centimeter (cm). All measurements were undertaken in light clothes and without the shoes. Weight was divided by square of height (in meters) to calculate body mass index (BMI) of participants. The BMI was classified as underweight (<18.5 Kg/m2), normal (18.5–24.9 Kg/m2), overweight (≥25 Kg/m2), and obese (≥30 Kg/m2) . Central obesity was defined as increased waist circumference more than 88 cm in women and more than 102 cm in men .
Data management and analysis
Data were compiled and edited to maintain consistency before entering into Epidata V 3.1. Duplications were removed and exported to SPSS V.20.0 for further analysis. Simple descriptive statistics were used to describe socio-demographic characteristics of study participants. Data were presented as the frequency with percentage (%) for categorical variables and the mean with standard deviation (SD) for normally distributed continuous variables. Median with interquartile range was used to present non-normally distributed continuous data. The overall prevalence of hypertension was described for the total study population with 95% confidence intervals (CI). Initially, univariate analysis was used to identify factors associated with hypertension. Prevalence of hypertension and factors associated with hypertension were adjusted by age and sex using standard Asian population distribution of 2013 for both male and female . Then all the associated factors were entered into simple and multiple logistic regression models to determine crude and adjusted odds ratios, respectively. Awareness, treatment, and control of hypertension were presented in proportion with 95% confidence interval for sex, age group, and socio-economic status among all hypertensive participants. Chi-square and independent t-test were conducted to compare proportions of categorical variables and means of continuous variables, respectively. Mann-Whitney U test used to test for medians of non-normally distributed numerical variables. All tests were two tailed and p value of < 0.05 was considered to be statistically significant.
The study protocol was approved by the Ethical Review Committee of Nepal Health Research Council. Written informed consent was obtained from every participant along with thumb impression, if participants were unable to write. The study objectives, data collection procedures, benefit, risk, and confidentiality were explained to each respondent before obtaining consent.
Socio-demographic characteristics of the study participants
Total number of participants included for the study was 1159 after excluding 21 with incomplete and inappropriate information. Of these, 71% were female. Mean age was 47±12.6 years and about one third of the participants were from 30–39 years. The majority of the enrolled residents were married. Out of total respondents, Brahman (29.3%) and Dalit (21.4%) were more compared to Janajati (18%). Majority of participants were not able to read and write (54%) and women (62.5%) were more uneducated than men (33.1%). More than half (56.8%) of the participants were working in household work while one third (26.3%) were employed. About one third (27.3%) were living in poor economic status (Table 1).
Prevalence of hypertension
Mean systolic blood pressure (SBP) was 123.1±20.6 mm Hg. The mean SBP was higher among men than women (128.6±19.9 vs. 120.8±19.8 mm Hg). Similarly, the overall mean diastolic blood pressure (DBP) was 80.8±12.4 mm Hg. The women (79.6±12 mm Hg) had lower mean blood pressure than that of men (83.6±12.8 mm Hg) [Table 1 and Fig 1]. After age and sex adjustment, overall mean systolic blood pressure was 123.6±20.1 mm Hg and mean diastolic blood pressure was 80.9±12.5 mm Hg. Men had significantly higher systolic and diastolic blood pressure compared to women (p<0.001).The overall prevalence of hypertension was 38.9% (95% CI: 36–41.7).With the age and sex adjustment hypertension prevalence was 40.6%. The prevalence of hypertension was significantly higher among men [48.1% (95% CI: 45.2–50.9)] compared to women [35.2% (95% CI: 32.4–37.9)]. After adjusting for age and sex, 48.6% of men and 37.1% of women were hypertensive. When stratified with the age group, the lowest prevalence was observed among 30–39 years of age (21.7%).The highest prevalence was 59.3% among participants above 60 years of age. The prevalence was almost similar among both men and women, if compared among last two age groups (Fig 2). Presence of hypertension was significantly different between men and women (p<0.001) and among age groups (p<0.001) with and without adjusting for age and sex (Table 2).
Socio-economic characteristics and hypertension
Hypertension was highest among the widow or widower (59%). Dalit (50%) and Janajati (41%) participants had high blood pressure in comparison to upper caste groups like Brahman and Kshetri. The proportion of hypertension was highest among uneducated participants (46.3%). Respondents without any job were more likely to be hypertensive. Prevalence was higher among those who had poor economic status (44%) compared to participants who were in above poverty line. Hypertension varied significantly with level of education (p = <0.001), marital status (p = <0.001), ethnicity (p = 0.001), occupation (p = 0.026), and economic status (p = 0.03) in univariate analysis. Moreover, ethnicity (p = 0.001), level of education (p = 0.001) and marital status (p<0.001), occupation (p = 0.02), and economic status (p = 0.012) were significantly associated with hypertension when adjusted for age and sex (Table 2).
Behavioral and anthropometric factors associated with hypertension
Overall, 18% and 15.5% of participants were the current and past smoker, respectively. Higher proportion of males (35%) than females (11%) were smoking cigarettes at the time of data collection. Among current smokers, 64.4% had high blood pressure. Mean number of cigarettes smoked was about 7 per week in both hypertensive and normotensive participants. Hypertension was observed among one third of past smokers. Smoking status (p<0.001) was significantly associated with hypertension with and without age and sex adjustment. Twelve percent of participants were chewing tobacco, among them; about half of the participants had hypertension. Current tobacco use (non smoking tobacco) was significantly (p = 0.01) associated with hypertension with and without hypertension (Tables 1 and 3).
Proportion of participants who consumed alcohol currently was 15.3% where more than one third of males (38.5%) and 6% of females were drinking (Table 1). Majority of study subjects who drank alcohol (56.5%) had hypertension. Current alcohol consumption was associated with hypertension without (p<0.001) and with (p = 0.001) age and sex adjustment. The mean number of standard drinks per day was significantly (p = 0.032) higher among hypertensive respondents (3.6 vs. 3) (Table 3).
Fruit and vegetable intake.
Almost all participants (96.8%) were not eating fruit and vegetable in sufficient amount and 38.7% of these individuals had hypertension. Median intake of fruit and vegetable servings was significantly different (p = 0.039) in both hypertensive and normotensive subjects (Tables 1 and 3).
Overall, one fifth of the total participants were consuming more than or equal to five grams of salt. Higher proportion of males (22.1%) was taking high amount of salt compared with females (19.7%). Of those participants who consumed high amount of salt, 37.3% had high blood pressure. However, salt intake was not significantly different between respondents with and without hypertension (Tables 1 and 3).
Out of all, 35.8% of participants were physically less active. Less physical activity was higher among males (41.5%) than females (35.8%) (Table 1). Among these less active individuals, 46% were suffering from hypertension. Median level of physical activities was 1060 METs-minutes per week among hypertensive while it was 1590 METs-minutes per week among normal participants (p = 0.036). The low level of physical activities was associated with hypertension with (p<0.001) and without (p<0.001) age and sex adjustment (Table 3).
Overweight and obesity.
Proportions of total participants who were overweight and obese were 36% and 7.5%, respectively. Women were more overweight and obese (39% and 8.7%) compared to men (29% and 4.5%) (Table 1). Proportion of hypertension was significantly different (p<0.001) between respondents with and without overweight and obesity. The mean BMI (p<0.001) and waist circumference (p<0.001) were significantly different in between hypertensive and normotensive participants. The findings were significantly (p<0.001) different between hypertensive and normotensive participants even after adjustment with age and sex (Tables 1 and 3).
Diabetes mellitus and family history of hypertension.
Seven percent participants stated that one of their first degree relatives had hypertension. Out of these, the proportion of hypertension was 46.5% among participants having positive family history and this family history of hypertension was significantly associated with hypertension with (p = 0.037) and without (p = 0.02) age sex adjustment. Overall, proportion of self reported diabetic participants were about 7%. It was significantly associated with hypertension without (p<0.001) and with (p = 0.001) age and sex adjustment (Table 3).
Factors associated with hypertension
Univariate and multivariate logistic regression model were used to identify the factors associated with hypertension. Age, gender, marital status, ethnicity, level of education, occupation, economic status, smoking, alcohol consumption, level of physical activities, history of diabetes, family history of hypertension, and BMI were significantly associated with hypertension in univariate logistic regression. However, fruit and vegetable intake and consumption of high amount of salt were not significantly associated. When all of these variables were entered in a multivariate logistic model, only gender, age, ethnicity, smoking, current alcohol use, and BMI were identified as significant factors associated with hypertension. One year increase in age shifted the likelihood of having hypertension up by 4% (adjusted OR = 1.04, 95% CI: 1.03–1.06) after adjusting all other factors. The chance of having hypertension in males was 1.49 (95% CI: 1.00–2.22) times as compared with females. Odds of having hypertension in Dalits as compared to Bramhan was 1.71 (95% CI: 1.41–2.56). Similarly, among past smokers, the odds of having hypertension had increased by 2.78 (95% CI: 1.87–4.14) compared to non smoker. In the same way, current alcohol user had 75% (adjusted OR = 1.75, 95% CI: 1.13–2.71) more chance of having high blood pressure compared to non alcohol drinker. With every unit gain in BMI, the risk of having hypertension was increased by 17% (adjusted OR = 1.17, 95% CI: 1.13–1.21) even after all other factors were adjusted (Table 4).
Awareness, treatment, and control of hypertension
Of total participants, 241 were aware of their hypertension, 131 were on treatment, and 37 had controlled blood pressure (Fig 3). The proportion of awareness among those who had hypertension was 53.4% (95% CI: 48.7–58). The awareness level was 55.9% (95% CI: 51.3–60.4) in males and 52.1% (95% CI: 47.4–56.7) in females. Older age groups had higher awareness of hypertension in both sexes compared to younger age groups. However, males more than 60 years were less aware than those of 40–60 years. Among those who had hypertension, 29% (95% CI: 24.8–33.1) were receiving prescribed antihypertensive medications. The proportion of men who were receiving treatment was 27.3% (95% CI: 23.1–31.4) and that of women was 30% (95% CI: 25.7–34.2) among hypertensive individuals. This treatment proportion was lower in younger age groups among all hypertensive participants. Only 8.2% (95% CI: 5.6–10.7) of all hypertensive participants had achieved blood pressure control (140/90 mm Hg). This achievement of blood pressure control was 7.5% (95% CI: 5–9.9) in males and 8.6% (95% CI: 6–11.1) in females. Blood pressure control was worse in younger individuals. Awareness (p = 0.003), treatment (p<0.001), and control (p = 0.039) were significantly different among the different age groups. However, the awareness, treatment and control among hypertensive participants were not significantly different by gender, ethnicity, level of education, occupation, and economic status (Table 5).
The current study revealed that about two-fifths of the participants had hypertension in suburban Municipality of Surkhet district of the Mid-western region of Nepal. Age, sex, ethnicity, smoking status, use of alcohol, and BMI were significantly associated with hypertension. Despite the high burden of hypertension, only half of them were aware of their condition, only one third were receiving the treatment, and one tenth had controlled blood pressure.
The prevalence of hypertension in the current study (38.9% and 40.6% without and with age/sex adjustment) was comparable with STEPS survey 2013 conducted in Nepal (36.8%) for respective age of 30 years and above . The hypertensive patients were higher in the current study population as compared to other different population of Nepal such as the Eastern region (34%), the capital (32.5%),western region (28%), Dhulikhel (27.7%), and rural Sindhuli (12.3%) [6–9,25]. These disparities in findings may be due to an inclusion of younger participants (even up to 15 years) in other studies. The higher prevalence of hypertension observed among older age group in our study was consistent with other studies conducted in Nepal [25–27]. Our findings were also comparable to studies of India for instance the prevalence of raised blood pressure including those of antihypertensive drug user was almost same as that of Kerala (40%) state of India .
Age was significantly associated with hypertension and its prevalence was highest among participants aged more than or equal to 60 years (59.3%). One study conducted in Kathmandu Nepal revealed that 56.1% were hypertensive among the same age group . Similarly, 45% of respondents aged more than 50 years had hypertension . Arterial, arteriolar stiffness, increased sodium retention is related to rise of blood pressure with age .
Hypertension was significantly higher among men (48%) compared to women (35%) (OR:1.49) in our study. Age and sex adjusted prevalence of hypertension was 48.6% and 37.1% among men and women. The finding was consistent with latest STEPS survey which reported that odds ratio was 1.16 in males compared to females . Similar findings were reported in the study conducted at Kathmandu (38.4% in males vs. 28.4% in females) , at that central development region (32.3% vs. 15.3%)  and at the rural Nepal (30.6% vs. 13.8%) . Data synthesized from 46 population based studies of different countries found higher prevalence of hypertension in men than women . One explanation for men to be more hypertensive may be related to the health behavior such as smoking, use of alcohol, and physical inactivity, which were consistently higher in male participants as noted from our study.
Ethnicity was another factor contributing to hypertension. Our results explored that Janajati had the highest burden of hypertension, which was followed by Dalit. Most of the studies conducted in Nepal found that hypertension was higher among the Janajati population. The higher exposure to unhealthy behaviors like smoking, use of alcohol among Dalits and Janajati population as observed in current and previous studies might be the contributing factors to hypertension [7,9,27]. However, more studies are needed to explain the effect of race/ethnicity on hypertension prevalence in Nepal.
In our study, current smoking and past smoking were associated with hypertension in univariate analysis. However, only past smoking became the significant predictor of hypertension when other variables were adjusted. Despite the well established fact that cigarette smoking increases the risk of hypertension [32,33], some cross-sectional epidemiological studies  like ours observed that habitual smokers generally have lower blood pressures than non smokers. This may be due to the fact that many patients stop smoking once they were diagnosed with hypertension.
Current alcohol consumption was also associated with hypertension. Recent epidemiological studies have demonstrated that alcohol intake was positively and significantly associated with risk of hypertension [35,36]. According to the global burden of disease in 2003, about 16% of all hypertensive diseases were attributed to alcohol consumption . Different studies in Nepal also observed an association of alcohol consumption to hypertension [6,9]. However, some studies found protective effect of alcohol intake on blood pressure [38,39] and this effect was demonstrated in women with light and moderate alcohol consumption [35,36]. Our study found that mean standard drink was higher among hypertensive participants, which was consistent with a meta-analysis of 15 randomized controlled trials  that demonstrated a dose-response relationship between alcohol consumption and blood pressure .
Our study observed a positive association between body mass index and blood pressure, which was consistent with the findings from other studies conducted in similar settings in Nepal [6, 9]. Higher BMI means greater fat stores, insulin resistance, increased salt retention, [42,43] and decreased physical activity ; all these contribute to rise in blood pressure level.
Current study found that about half (53.4%) of all hypertensive participants were aware of their condition. The level of awareness in our study was higher when compared with other studies of Nepal and abroad. The proportion of aware participants ranged from 41% to 46% in Nepal [7,8,45]. Moreover, one cross-sectional study of 628 communities of high, middle and low income countries observed that 46.5% were aware of hypertension . Our study also found that hypertension awareness was comparatively higher among elderly groups. It could be because of frequent visit to health care facilities by elderly groups. Similarly, one third (29%) of total hypertensive participants were receiving antihypertensive medicine in current study. This proportion was consistent with other studies of Nepal (31–33%) [7,8] and abroad (32.5%) . However, the proportion of untreated hypertensive participants was less compared with a study in municipalities of Kathmandu  and then national STEPS survey of Nepal (88.3%) . Current study contrast the finding of other studies which reported different awareness and treatment proportion among males and females [7,10]. As suggested by Devkota et. al., such a low treatment status could be because of poor socio-economic status, poor health literacy and ingrained misconception on antihypertensive treatment among participants . In the same way, only 8.2% of all hypertensive participants had controlled blood pressure in current study which was lower than that reported in recent studies of Kathmandu (13%) , Dhulikhel (11%) , and Pokhara (15%)  of Nepal. When compared with the findings of developed countries, there was high disparity in awareness, treatment, and control of hypertension in Nepal [20,46]. Our results also showed hypertension control status significantly varied with age groups as observed in other studies [7,10]. From the above findings, it can be inferred that there is a huge gap in hypertension awareness, treatment and control in the study population inviting urgent public health intervention particularly targeting the population at risk, including younger population.
Our study had several limitations. The study was conducted in one municipality of the Mid-western region of Nepal with a total population of about 52, 000. High numbers of female were participated in the study because of the fact that many males were out of the community or country for earning livelihood. Though we had adjusted the sample size for non response rate, we did not record the formal participation rate. We have measured blood pressure twice at three-minutes interval in a single visit and average of these two were used for analysis. Over-estimation of hypertension status may result in due to the use of a single visit measurement. Moreover, bilateral measurement could rule out sublcavian steal syndrome. As we did not include the person having known heart disease and kidney disease in the study, findings could be less accurate in estimating population parameter. Despite the use of standardized questionnaire with rigorous training to the enumerator, error might have happened in self reported behavior. Over-estimation of level of physical activities and under-estimation of salt intake might have been observed in our study. It would have been better to use a log book or other direct method to ascertain physical activities  and 24-hours urinary sodium excretion to assess salt intake . Presence of diabetes was determined as reported by participants without blood sugar measurement. This study could not measure cholesterol level also. Despite these limitations, this study has several strengths. This was the first study conducted in the Mid-western region of Nepal that reported the prevalence of hypertension by gender, age and socioeconomic status. Random selection of participants, rigorous training to data collectors, enrolment of the participants at their own homes, age-sex stratified analysis of data, and estimation of age-sex adjusted (by standard Asian population) prevalence of hypertension were other strengths of our study.
This study found high prevalence but poor awareness, treatment, and control status of hypertension in the Mid-western region of Nepal. Age, sex, ethnicity, cigarette smoking, alcohol consumption, and body mass index were identified as associated factors of hypertension. Current findings suggest the future burden of cardiovascular and kidney diseases in Nepal. Immediate planning and implementation of public health measures and individual interventions are needed to prevent the occurrence and complications of hypertension.
The authors want to express their gratitude and appreciation to Professor Edward Denis Janus, University of Melbourne, Australia for critical review of the manuscript. They want to thank the study team and the participants. They acknowledge the staffs of Bheri Zonal Ayurveda HospitalSurkhet (namely Dr. Shanker Rijal, Shree Ram Acharye, Narendra Kathayet, Nar Bahadur Thapa, Bhanu Bhakta Thapa, Khusiram Chaudhari, Sukadev Acharye, and Prabina B C) for their logistic and managerial support. Similarly, they would like to thank field supervisor and data collector team: Ms. Nirmala, Ms Lata, Mr. Narendra, Mr. Tulsi, Mr. Man Bahadur, Ms.Deepa, Ms. Bishnu, Ms. Debisara, Ms. Laxmi, Ms. Kalpana, Ms. Shamjhana, Ms. Prema, Ms. Chitra, Ms. Sita, Ms. Jwoti, Ms. Shobha, Ms. Ranjana, Ms. Pratiksha, Ms. Amrita, and Mr. Deepak. The study team wants to thank Mr. Nilkantha Khanal and female community health volunteers of District Health Office for supporting in community mobilization. We want to thank Mr. Pratik Bhandari for proof-reading the manuscript.
- 1. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J Global burden of hypertension: analysis of worldwide data. The Lancet 365: 217–223.
- 2. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380: 2224–2260. pmid:23245609
- 3. WHO (2013) A global brief on Hypertension Geneva: World Health Organization.
- 4. WHO (2014) Global status report on noncommunicable diseases 2014. Geneva: World Health Organization.
- 5. Aryal KK, Mehata S, Neupane S, Vaidya A, Dhimal M, Dhakal P, et al. (2015) The Burden and Determinants of Non Communicable Diseases Risk Factors in Nepal: Findings from a Nationwide STEPS Survey. PLoS One 10: e0134834. pmid:26244512
- 6. Dhungana RR, Devkota S, Khanal MK, Gurung Y, Giri RK, Parajuli RK, et al. (2014) Prevalence of cardiovascular health risk behaviors in a remote rural community of Sindhuli district, Nepal. BMC Cardiovasc Disord 14: 92. pmid:25066117
- 7. Karmacharya BM, Koju RP, LoGerfo JP, Chan KC, Mokdad AH, Shrestha A, et al. (2017) Awareness, treatment and control of hypertension in Nepal: findings from the Dhulikhel Heart Study. Heart Asia 9: 1–8. pmid:28123454
- 8. Neupane D, Shrestha A, Mishra SR, Bloch J, Christensen B, McLachlan CS, et al. (2017) Awareness, Prevalence, Treatment, and Control of Hypertension in Western Nepal. Am J Hypertens.
- 9. Dhungana RR, Pandey AR, Bista B, Joshi S, Devkota S (2016) Prevalence and Associated Factors of Hypertension: A Community-Based Cross-Sectional Study in Municipalities of Kathmandu, Nepal. Int J Hypertens 2016: 1656938. pmid:27293880
- 10. Devkota S, Dhungana RR, Pandey AR, Bista B, Panthi S, Thakur KK, et al. (2016) Barriers to Treatment and Control of Hypertension among Hypertensive Participants: A Community-Based Cross-sectional Mixed Method Study in Municipalities of Kathmandu, Nepal. Front Cardiovasc Med 3: 26. pmid:27532038
- 11. Law MR, Morris JK, Wald NJ (2009) Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ 338.
- 12. Di Cesare M, Bennett JE, Best N, Stevens GA, Danaei G, Ezzati M (2013) The contributions of risk factor trends to cardiometabolic mortality decline in 26 industrialized countries. International Journal of Epidemiology 42: 838–848. pmid:23744994
- 13. CBS (2014) National Population and Housing Census 2011. Kathmandu: Central Bureau of Statistics, Nepal.
- 14. CBC (2014) Population Monograph of Nepal. Kathmandu. Central Bureau of Statistics, Nepal
- 15. Aryal KN, S; Mehata, S; Vaidya, A; Singh, S; Paulin, F; Madanlal, RG; Riley, LM; Cowan, M; Guthold, R; Singh, SP; Bhusal, CL; Lohani, GR (2014) Non communicable diseases risk factors: STEPS Survey Nepal 2013. Kathmandu.
- 16. Lwanga S.K SL (1991) Sample size determination in health studies: A practical manual. Geneva. World Health Organization
- 17. WHO (2005) WHO STEPS Surveillance Manual: The WHO STEPwise approach to chronic disease risk factor surveillance / Noncommunicable Diseases and Mental Health. Geneva: World Health Organization.
- 18. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr., et al. (2003) The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 289: 2560–2572. pmid:12748199
- 19. Central Bureau of Statistics and World Bank (2012) Poverty in Nepal 2010–11, NLSS-III, 2010-11. CBS Nepal.
- 20. Chow CK, Teo KK, Rangarajan S, Islam S, Gupta R, Avezum A, et al. (2013) Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA 310: 959–968. pmid:24002282
- 21. WHO (2006) Reducing salt intake in populations. Report of WHO Forum and Technical Meeting. Paris. World Health Organization
- 22. WHO (1997) Preventing and Managing the Global Epidemic of Obesity. Report of the World Health Organization Consultation of Obesity. Geneva.
- 23. WHO (2008) Waist circumference and waist–hip ratio: report of a WHO expert consultation. Geneva. World Health Organization.
- 24. Sankoh O, Sharrow D, Herbst K, Kabudula CW, Alam N, Kant S, et al. (2014) The INDEPTH standard population for low- and middle-income countries, 2013. Global Health Action 7.
- 25. Sharma SK, Ghimire A, Radhakrishnan J, Thapa L, Shrestha NR, Paudel N, et al. (2011) Prevalence of hypertension, obesity, diabetes, and metabolic syndrome in Nepal. Int J Hypertens 2011: 821971. pmid:21629873
- 26. Manandhar K, Koju R, Sinha NP, Humagain S (2012) Prevalence and associated risk factors of hypertension among people aged 50 years and more in Banepa Municipality, Nepal. Kathmandu Univ Med J (KUMJ) 10: 35–38.
- 27. Chataut J, Adhikari RK, Sinha NP (2011) The prevalence of and risk factors for hypertension in adults living in central development region of Nepal. Kathmandu Univ Med J (KUMJ) 9: 13–18.
- 28. Meshram II, Arlappa N, Balkrishna N, Rao KM, Laxmaiah A, Brahmam GN (2012) Prevalence of hypertension, its correlates and awareness among adult tribal population of Kerala state, India. J Postgrad Med 58: 255–261. pmid:23298919
- 29. Weber MA, Neutel JM, Cheung DG (1989) Hypertension in the aged: a pathophysiologic basis for treatment. Am J Cardiol 63: 25H–32H. pmid:2650521
- 30. Chataut J, Khanal K, Manandhar K (2015) Prevalence and Associated Factors of Hypertension among Adults in Rural Nepal: A Community Based Study. Kathmandu Univ Med J (KUMJ) 13: 346–350.
- 31. Klungel OH, de Boer A, Paes AH, Seidell JC, Bakker A (1997) Sex differences in the pharmacological treatment of hypertension: a review of population-based studies. J Hypertens 15: 591–600. pmid:9218177
- 32. Bowman TS, Gaziano JM, Buring JE, Sesso HD (2007) A prospective study of cigarette smoking and risk of incident hypertension in women. J Am Coll Cardiol 50: 2085–2092. pmid:18021879
- 33. Primatesta P, Falaschetti E, Gupta S, Marmot MG, Poulter NR (2001) Association Between Smoking and Blood Pressure. Evidence From the Health Survey for England 37: 187–193.
- 34. Green MS, Jucha E, Luz Y (1986) Blood pressure in smokers and nonsmokers: epidemiologic findings. Am Heart J 111: 932–940. pmid:3706114
- 35. Sesso HD, Cook NR, Buring JE, Manson JE, Gaziano JM (2008) Alcohol consumption and the risk of hypertension in women and men. Hypertension 51: 1080–1087. pmid:18259032
- 36. Kaplan NM (1995) Alcohol and hypertension. Lancet 345: 1588–1589. pmid:7783532
- 37. Beilin LJ, Puddey IB (2006) Alcohol and Hypertension. An Update 47: 1035–1038.
- 38. Sacco RL, Elkind M, Boden-Albala B, et al. (1999) The protective effect of moderate alcohol consumption on ischemic stroke. JAMA 281: 53–60. pmid:9892451
- 39. Kannel WB, Ellison RC (1996) Alcohol and coronary heart disease: the evidence for a protective effect. Clin Chim Acta 246: 59–76. pmid:8814971
- 40. Xin X, He J, Frontini MG, Ogden LG, Motsamai OI, Whelton PK (2001) Effects of Alcohol Reduction on Blood Pressure. A Meta-Analysis of Randomized Controlled Trials 38: 1112–1117.
- 41. Roerecke M, Kaczorowski J, Tobe SW, Gmel G, Hasan OSM, Rehm J The effect of a reduction in alcohol consumption on blood pressure: a systematic review and meta-analysis. The Lancet Public Health 2: e108–e120.
- 42. Rocchini AP, Key J, Bondie D, Chico R, Moorehead C, Katch V, et al. (1989) The effect of weight loss on the sensitivity of blood pressure to sodium in obese adolescents. N Engl J Med 321: 580–585. pmid:2668763
- 43. Cooper R, Van Horn L, Liu K, Trevisan M, Nanas S, Ueshima H, et al. (1984) A randomized trial on the effect of decreased dietary sodium intake on blood pressure in adolescents. J Hypertens 2: 361–366. pmid:6530546
- 44. Nelson L, Jennings GL, Esler MD, Korner PI (1986) Effect of changing levels of physical activity on blood-pressure and haemodynamics in essential hypertension. Lancet 2: 473–476. pmid:2875235
- 45. Sharma D, Bkc M, Rajbhandari S, Raut R, Baidya SG, Kafle PM, et al. (2006) Study of Prevalence, Awareness,and control of Hypertension in a Suburban Area of Kathmandu, Nepal. Indian Heart J 58: 34–37. pmid:18984928
- 46. Janus ED, Bunker SJ, Kilkkinen A, Mc Namara K, Philpot B, Tideman P, et al. (2008) Prevalence, detection and drug treatment of hypertension in a rural Australian population: the Greater Green Triangle risk factor study 2004–2006. Intern Med J 38: 879–886. pmid:18284462
- 47. Kowalski K, Rhodes R, Naylor P-J, Tuokko H, MacDonald S (2012) Direct and indirect measurement of physical activity in older adults: a systematic review of the literature. The International Journal of Behavioral Nutrition and Physical Activity 9: 148–148. pmid:23245612
- 48. McLean RM (2014) Measuring Population Sodium Intake: A Review of Methods. Nutrients 6: 4651–4662. pmid:25353661