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 Table of Contents  
Year : 2020  |  Volume : 7  |  Issue : 3  |  Page : 223-229

A community-based study on modifiable risk factors of hypertension among Adults of rural Bengal, India

1 Department of Community Medicine, IQ City Medical College, Durgapur, West Bengal, India
2 Department of Community Medicine, Tripura Medical College and Dr. BRAM Teaching Hospital, Agartala, India
3 Department of Community Medicine, Medical College, Kolkata, West Bengal, India
4 Department of Maternal and Child Health, All India Institute of Hygiene and Public Health, Kolkata, India
5 Department of Community Medicine, Government Theni Medical College and Hospital, Theni, Tamil Nadu, India
6 Department of Health and Family Welfare, Government of Tripura, Agartala, India

Date of Submission14-Oct-2019
Date of Acceptance03-Mar-2020
Date of Web Publication25-Jan-2021

Correspondence Address:
Ram Prabhakar Venkataraman
Assistant Professor, Department of Community Medicine, Government Theni Medical College and Hospital, Kanavilakku - 625531, Theni District, Tamil Nadu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/cjhr.cjhr_101_19

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Background: Chronic noncommunicable diseases such as hypertension (HTN) are emerging as a major health problem in India with increasing prevalence significantly in both urban and rural population. This is largely due to preventable and modifiable risk factors such as physical inactivity, unhealthy diet, obesity, tobacco, and inappropriate use of alcohol. Objectives: This study aimed to find the prevalence and risk factors of HTN and its association with HTN among the study population, if any. Materials and Methods: A community-based study was conducted among 651 adults (age 20 years and above) in rural communities of Singur, West Bengal. Blood pressure measurement and information regarding sociodemography, behavioral risk factors, and family history of HTN were collected using a predesigned pretested schedule. Data were presented in appropriate tables, and the significance of association was analyzed with P < 0.05 as statistically significant; all statistical analysis was done in SPSS version 19.0. Results: The overall prevalence of HTN was 26.1% (male: 21.8% and female: 29.9%). The prevalence increased with increase in age group. Muslim religion, less education, tobacco usage, obesity, and sedentary lifestyles were found to be significantly associated with HTN. The association between different modifiable risk factors with HTN was found statistically significant (P < 0.05). Conclusion: The prevalence of HTN in the rural population was found to be on the higher side compared to previous reports from India. The modifiable risk factors of HTN in rural communities were found to be increased indicating implementation of strong public health measures to combat HTN and its consequences.

Keywords: Adult, fruit, hypertension, risk factors, rural population

How to cite this article:
Saha I, Karmakar N, Sarkar T, Sinha R, Venkataraman RP, Chakraborty T. A community-based study on modifiable risk factors of hypertension among Adults of rural Bengal, India. CHRISMED J Health Res 2020;7:223-9

How to cite this URL:
Saha I, Karmakar N, Sarkar T, Sinha R, Venkataraman RP, Chakraborty T. A community-based study on modifiable risk factors of hypertension among Adults of rural Bengal, India. CHRISMED J Health Res [serial online] 2020 [cited 2022 May 23];7:223-9. Available from: https://www.cjhr.org/text.asp?2020/7/3/223/307812

  Introduction Top

Non-communicable diseases (NCD), the leading global cause of adult mortality and morbidity, have reached epidemic proportions needing feasible and cost effective interventions to halt rising problem, especially in the world's low and middle income populations.[1] India too experiences a rapid health transition with the rising burden of NCD (over 42% of all deaths) over the years; hypertension (HTN) is a major chronic lifestyle disease and the most prevalent NCD in India.[2] The World Health Statistics (2012) reveals that one in three adults worldwide has raised blood pressure – a condition that caused around half of all deaths from stroke and heart disease.[3] In India, the prevalence of HTN, as per the WHO estimates of 2008, is also as high as 32.5% (male: 33.2% and female: 31.7%).[4]

As such, HTN has no cause, but some risk factors or attributes are associated, the emergence of which in an individual may lead to the development of HTN. These factors may be nonmodifiable risk factors such as age, sex, genetic, ethnicity, and modifiable risk factors such as obesity, lack of physical activity, salt intake, tobacco, and heavy alcohol intake. “Among this, tobacco use, unhealthy diet, lack of physical activity, and harmful use of alcohol are the four major behavioral risk factors of NCDs. Again, these may lead to four major metabolic risk factors (overweight/obesity, high blood pressure, raised blood sugar, and raised blood lipids) which are highly prevalent in this region and are on rise.”[5] Hence, an important way to control HTN and other NCDs is to focus on reducing modifiable risk factors associated with these diseases.

The CUPS study suggests that “rule of halves” is still valid in the Indian population making control of HTN in the entire population a bit inadequate.[6] Hence, more stress needs to be given to understand the nature and magnitude of modifiable risk factors of HTN at the community level. Moreover, there is a scarcity of studies related to HTN in rural areas, especially in this part of the country. With this backdrop, a study was undertaken by the researcher to find the modifiable risk factors and association of HTN with those factors, if any among adults in Singur Block of Hooghly district of West Bengal which is the rural field practice area of All India Institute of Hygiene and Public Health (AIIH and PH), Kolkata, under Rural Health Unit & Training Centre (RHUTC), Singur.

  Materials and Methods Top

This community-based epidemiological study with cross-sectional design was conducted from May 2013 to April 2014 among people aged 20 years and above residing in rural communities of Singur Block, Hooghly district, West Bengal, which is the rural field practice area of AIIH and PH, Kolkata, India.

The AIIH&PH, Kolkata, being the first school of Public Health in South East Asia region is devoted to teaching, training and research in various disciplines of Public Health and Allied Sciences with field level exposure at Urban Health Centre, Chetla, and Rural Health Unit and Training Centre (RHU&TC), Singur. After receiving assistance from the Rockefeller Foundation, it was formally opened on December 30, 1932, by John Anderson, Governor of Bengal, with Lt. Col. A D Stewart as its first director.

Singur is situated in Singur CD Block in Chandannagore subdivision of Hooghly district in West Bengal, India, which is well connected (34 km from Howrah Station) to Kolkata metropolitan city. There are 64 villages with a total population of 99141 (according to 2011 census data) in the catchment area of RHUTC, Singur. Public health services in these villages are being provided through two union health centers (UHC), namely Anandanagar UHC and Nasibpur UHC, four subcenters, and 12 health units.

Sample size

Taking 19.04%[7] as the prevalence of HTN with 20% relative allowable error, sample size becomes 409 after applying the formula – Sample size = Zα2 pq/L2 where Zα = standard normal deviate at a desired confidence level (95%), p = previous prevalence, q = 100–p, and L = allowable error (at 95% confidence interval [CI] level, Zα value = 1.96). Since a multistage random sampling technique was followed to select study population, a “design effect” of 1.5[8] and also an additional 5% increase in the sample size were required to compensate for any nonresponse. Hence, the sample size came as 645, and finally, 651 samples were collected for this study.

Sampling design

A two-stage random sampling method was followed for the selection of study participants. In the first stage, of 64 villages of the study area, 20% were selected randomly, i.e., primary sampling units were villages. In the second stage, from selected villages, a required number of adults were selected randomly. Therefore, the final sampling units were the persons aged ≥20 years.

The sampling frame for selection of villages was a list containing names of all 64 villages under the service area was collected from the office of RHU&TC, Singur. From this list, 12 villages (approximately 20%) were chosen by simple random sampling using random numbers from a random number table. In each of the selected villages (i.e., 12 villages selected in the first stage), a list of all individuals aged 20 years and above was made from the electoral list of 2011 available to the local panchayat members. The total requirement of the 645 individuals was distributed among these 12 villages according to the number of their inhabitants (probability proportionate to size – PPS method). The required number of individuals for each village was selected by simple random sampling using the available electoral lists as the sampling frame.

Inclusion criteria

All the inhabitants aged 20 years and above.

Exclusion criteria

Unwilling individuals, pregnant women, and moribund patients.


A predesigned and pretested schedule, mercury sphygmomanometer, stethoscope, weighing machine, and nonstretchable measuring tape.


Interview of participants, blood pressure checkup, and review of past records such as outpatient department (OPD) tickets and doctor's prescription.

Methods of data collection

Study participants were interviewed at their family setting after explaining academic nature of this research. Then, information was obtained in predesigned and pretested schedule about their sociodemographic and behavioral characteristics. Each participant was examined for blood pressure using the JNC VII guidelines.[9] Previous records such as prescription or OPD tickets, if any, had been scrutinized. At least three attempts were made to interview a particular individual he/she could not be accessed the first time or he/she was suffering from any acute illness on days of earlier visits. During this study, individuals with blood pressure level ≥140/90 mmHg were advised to visit the nearest UHC for further investigations and treatment.

Ethical permission

At first, the study proposal with interview schedule was submitted and the approval for ethical clearance was taken from the Institutional Ethics Committee of AIIH and PH, Kolkata. After this, data collection was initiated with informed written consent in local language (Bengali) from every interviewee.

Statistical analysis

The collected data were entered in Microsoft Excel worksheet (Microsoft, Redwoods, WA, USA) and checked for any duplicate or erroneous entry. Data were presented in appropriate tables, and the significance of association between HTN (dependent variable) with the different independent variables was analyzed by Chi-square (χ2) test; P < 0.05 was considered as statistically significant. All statistical analysis was done in SPSS software version 19.0 (Statistical Package for the Social Sciences Inc., Chicago, IL, USA).

  Results Top

A total of 651 participants were included in this study where majority (32.9%) belonged to 20–30 years (mean age: 38.4 ± 14.3 years, male – 47.2%). Majority of the participants (94.2%) were Hindu and 54.2% were from nuclear family. Most of them (79.9%) were currently married followed by 16% who were never married; 16.3% were illiterate, and among literate, 30% completed primary school. As per the “Classification of activities based on occupations” of the National Institute of Nutrition,[10] 74.7% were sedentary workers and the rest (25.3%) were moderate workers. Nearly half (47%) belonged to Class IV followed by 45.3% in Class V socioeconomic category as per the modified BG Prasad scale 2013.[11] In this current survey, 170 (26.1%) participants were found as hypertensive and the remaining 481 (73.9%) nonhypertensive.

[Table 1] shows that there was an association between different modifiable risk factors with HTN which was found to be statistically significant in χ2 test (P < 0.05) except few other risk factors such as alcohol usage, fruit intake, vegetable intake, and presence of mental stress.
Table 1: Distribution of the hypertensive and nonhypertensive study population according to covariates (n=651)

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Important modifiable risk factors (i.e., low physical activity, obesity [body mass index (BMI) >23.00)], abdominal obesity [waist circumference >90 cm for males and >80 cm for females], having diabetes mellitus [DM], addiction to tobacco and alcohol, additional salt intake, mental stress, and family history of HTN) were taken into consideration. Proportion of hypertensives increased gradually with increase in number of risk factors. The least number of hypertensives was observed with no risk factors present, while proportion was maximum (34.7%) among those having four modifiable risk factors (P < 0.05) [Table 2].
Table 2: Distribution of the hypertensive and nonhypertensive study population according to the presence of important modifiable risk factors (n=651)

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Physical activity, obesity (BMI), abdominal obesity, and systolic and diastolic blood pressure (SBP and DBP) were considered for multifactorial analysis of blood pressure variations where almost all independent variables had a significant positive correlation with both SBP and DBP, except physical activity with DBP, that means increase in independent variable will also increase dependent variable, i.e., both SBP and DBP. Moreover, there were significant correlations between many independent variables suggesting that these variables themselves may have a synergistic influence in the prediction of SBP and DBP of an individual [Table 3].
Table 3: Correlation matrix of modifiable risk factors of hypertension (n=651)

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In multivariate logistic regression (forward conditional method), some variables such as salt intake, obesity (BMI), and family history of HTN lost their significance even though they were significant on bivariate analysis (χ2). As evident form Cox and Snell's R2 and Nagelkerke's R2, DM alone explained 16%–23.4% variation of HTN. Tobacco usage, abdominal obesity, physical activity, and DM together contributed 21.3%–31.3% variation of HTN. Abdominal obesity, physical activity, tobacco usage, and DM had a significant positive association with HTN as evident from adjusted odds ratio (OR). Goodness of fit of each model of the hierarchical multivariate logistic regression was tested with Hosmer–Lemeshow test, and all the six models were good fit (P > 0.05) [Table 4].
Table 4: Association of hypertension with modifiable risk factors among study population (logistic regression by forward conditional method) n=651

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  Discussion Top

In this community-based study, we found that HTN was associated with different modifiable risk factors (P < 0.05) except few such as alcohol usage, fruit intake, vegetable intake, and presence of mental stress. Proportion of hypertensives increased gradually with increase in number of risk factors (among hypertensives, 34.7% had four modifiable risk factors), which was statistically significant (P < 0.05).

The present study found that both obesity (BMI) and abdominal obesity had a significant positive association with HTN (P < 0.05) similar to studies done elsewhere.[12],[13],[14],[15],[16] Sadhukhan and Dan[17] in multifactorial analysis revealed that as an individual factor, BMI explained about 3.10% of SBP and 7.78% of DBP variations. The current study showed that there was a significant relation of HTN with obesity on bivariate analysis, but when adjusted with all the variables of the study, it lost its significance. Khan et al.[18] in a subsample showed that both SBP and DBP were positively associated with high BMI and high waist circumference (P < 0.01).

Manandhar K et al.[19] found more hypertensive with non-vegetarian eating habits, saturated fat intake (P < 0.05), but there was significantly lower number of cases among respondents who took green leafy vegetable at least once a week (P < 0.05). In the current study, majority of hypertensives (92.9%) were from those participants who took fruits <5 days/week, but only 1.2% of hypertensives from those taking vegetables <5 days per week, similarly other studies found diet was not significantly associated HTN.[12],[15]

A significant linear trend between salt intake and HTN (P < 0.05) was found in previous studies.[14],[17],[20] In the current study, 54.2% of hypertensives were consuming additional salt which had a significant relation with HTN in bivariate analysis, but after adjustment, it lost its significance.

Previous literature showed that sedentary activity was significantly (P < 0.05) associated with risk of HTN.[7],[12],[16],[21],[22] Parker et al. considering a variety of sociobehavioral factors found attenuation in association between incident HTN and average physical activity (hazard rate ratio = 0.85; 95% CI = 0.76–0.96).[23] Another study by Jackson et al. found thatthat though individually both BMI and physical activity were associated with risk of HTN (P for trend < 0.001); conjoint effect depicted greater risk of HTN in obese high active women (OR = 3.43, 95% CI = 2.68–4.39) and in obese inactive women (OR = 4.91, 95% CI = 3.92–6.13) compared to healthy weight high active women.[24] The present study showed that tobacco usage, abdominal obesity, physical activity, and DM together contributed 21.3%–31.3% variation of HTN (P < 0.05).

Meshram et al.[21] showed that the risk of HTN was significantly (P < 0.05) associated with smoking and duration of tobacco chewing among both sexes but lost significance in multivariate analysis. Bansal et al.[15] showed that smoking did not find any risk predictor of HTN, but significant for alcohol users in male; studies elsewhere[12],[14],[25] found an association between HTN and alcohol consumption (P < 0.05). Todkar et al.[26] showed an association between HTN with tobacco and alcohol consumption (P < 0.05); higher prevalence compared to the present study might be due to nonalcoholics and tobacco users among females and overall less consumption in the total study population. Smoking, alcohol use, and not working outside home were associated with a higher risk in rural Nepal.[18] Again, in rural Africa alcohol intake, smoking, fruit and vegetable intake, and BMI were not significantly associated with HTN (P > 0.05).[27]

In Manipur, 13.8% of individuals had co-prevalence of DM and HTN; effect of risk factors on co-prevalence of DM and HTN showed the difference when compared with the occurrence of only DM or HTN.[28] Vimala et al. showed that a higher prevalence of HTN was found with DM (P < 0.05).[20] Obesity, smoking, alcohol consumption, and diabetes were found to be associated with HTN, but after adjustment, only obesity remains strongly associated with HTN.[29] In the present study, both bivariate and multivariate analyses found a significant relation between DM and HTN. Both SBP and DBP were positively associated with high triglycerides, high HbA1c, and raised fasting glucose after adjusting for potential confounders (P < 0.01).[18]

The prevalence of HTN was higher in participants having a parental history of HTN and stroke (P < 0.05)[13],[14],[25] similar to the present study finding. Grimsrud et al. found that HTN diagnosis was associated with 12-month anxiety disorders (OR = 1.55, 95% CI = 1.10–2.18) but not 12-month depression or comorbid anxiety–depression.[30] These findings might not be comparable with the present study findings of mental stress and HTN as it was assessed on the basis of subjective response.

This study had a number of strengths with some addition and future scope. This study unfolded magnitude of HTN along with it's modifiable risk factors as a growing NCD threat to the rural population of Bengal. Interventions specifically aimed at these risk factors may reduce the development of new cases and associated complications. There is a strong felt necessity of integrating HTN control activities with prevention and control of other common NCDs such as cardiovascular disease and stroke. Lunch of the National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular diseases and Stroke by the Government of India in this regard is a welcoming step which hopefully will play a role in letting India reap it's dividend on account of its youth population in a long period. After all, when Indian population suffered from NCD such as HTN, it damages Indian economy by reducing productivity, causing early retirement of the massive Indian workforce, and by increasing health-care costs.


This study had certain limitations. As the sample size was calculated from overall prevalence of HTN in previous literature; age group wise HTN (20–30, 30–40 years etc.) found in present study might have some limitations due to relatively inadequate sample size in respective age groups. age group-wise (20–30, 30–40 years, etc.,) HTN as revealed in the present study might have some limitations due to relatively inadequate sample size in respective age groups. Blood pressure was recorded only one time, for 12 months covering all seasons might cause some error due to seasonal variation. Again, blood pressure was recorded at individual household level during the daytime, so normal diurnal variation of blood pressure could not be assessed. Due to multifactorial causation of HTN, missing of some potential risk factors cannot be ruled out even after extensive search of literature. Laboratory investigations could not be done by the researcher due to financial constraints and other logistic problems.

  Conclusion Top

There is a strong correlation between modifiable risk factors and increased HTN; the higher prevalence in this study supports the trend of changing lifestyles in rural Indian communities which are under epidemiological transition. Hence, an appropriate community-based intervention program for the prevention and control of HTN in India, especially among rural population, is a need of hour, keeping in mind about important modifiable risk factors of HTN in the area such as physical activity, obesity, diabetes mellitus, tobacco use, and inappropriate use of alcohol.


We are grateful to the Officer-in-Charge of RHUTC, Singur, for his support to carry out this research work in the abovementioned area. We are grateful to all the health workers, ASHA, participants, and families for their extensive collaboration, without which this study could not have been conducted.

Author Contributions

IS1- Concept of study, Data analysis, drafting of the manuscript, critical revision of the manuscript for important intellectual content, final approval of the version to be published.

NK2- Concept and design of study, Literature review, Data Collection, Data analysis and interpretation of data, manuscript writing, final approval of the version to be published.

TS3- Data collection, manuscript writing, final approval of the version to be published.

RNS4- Concept of the study, Supervision of the study and manuscript review, final approval of the version to be published.

RPV5- Data collection, Data analysis and interpretation of data, final approval of the version to be published.

TC6- Data analysis, Manuscript review, final approval of the version to be published.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

World Health Organisation. Global Status Report on Non-communicable Diseases 2010; 2010 Available from: http://www.who.int/nmh/publications/ncd_report_full_en.pdf. [Last accessed on 2014 Jan 12].  Back to cited text no. 1
Kumar S, Kaushik A. Non- communicable disease: A challenge. Indian J Community Health 2012;24:252-4.  Back to cited text no. 2
World Health Organisation. New Data Highlight Increases in Hypertension, Diabetes Incidence; 2012. Available from: http://www.who.int/mediacentre/news/releases/2012/world_health_statistics_20120516/en/. [Last cited on 2014 Sep 11].  Back to cited text no. 3
World Health Organisation. Non-Communicable Diseases Country Profiles 2014; 2014. Available from: http://www.who.int/nmh/countries/ind_en.pdf. [Last accessed on 2015 Dec 25].  Back to cited text no. 4
World Health Organization, Regional Office for South-East Asia. Non-Communicable Diseases in the South-East Asia Region: Situation and Response 2011; 2011. Available from: http://www.searo.who.int/nepal/mediacentre/2011_non_communicable_diseases_in_the_south_east_asia_region.pdf. [Last accessed on 2017 Jul 01].  Back to cited text no. 5
Deepa R, Shanthirani CS, Pradeepa R, Mohan V. Is the 'rule of halves' in hypertension still valid? – Evidence from the Chennai Urban Population Study. J Assoc Physicians India 2003;51:153-7.  Back to cited text no. 6
Kokiwar PR, Gupta SS, Durge PM. Prevalence of hypertension in a rural community of central India. J Assoc Physicians India 2012;60:26-9.  Back to cited text no. 7
WHO STEPS Surveillance-Section 2: Preparing the Sample. World Health Organisation, 2008; 2008. Available from: http://http://www.who.int/ncds/surveillance/steps/Section%202%20Preparing%20the%20 Sample.pdf. [Last accessed on 2013 Jan 12].  Back to cited text no. 8
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The JNC 7 report. JAMA 2003;289:2560-72.  Back to cited text no. 9
Gopalan C, Rama Sastri BV, Balsubramanian SC. Nutrtive Value of Indian Foods, 1st Revised Edition. Hyderabad: NIN ICMR; 2012. p. 9-10.  Back to cited text no. 10
Dudala SR, Arlappa N. An updated prasad's socio economic status classification for 2013. Int J Res Dev Health 2013;1:26-8.  Back to cited text no. 11
Chataut J, Adhikari RK, Sinha NP. The prevalence of and risk factors for hypertension in adults living in central development region of Nepal. Kathmandu Univ Med J (KUMJ) 2011;9:13-8.  Back to cited text no. 12
Gupta S, Agarwal Kumar B, Sehajpal PK, Goel RK. Prevalence and predictors of hypertension in the rural population of Haryana, India: An hospital based study. J Rural Trop Public Health 2011;10:29-34.  Back to cited text no. 13
Saxena P, Saxena V, Saxena Y. Bio-social factors associated with hypertension in hilly population of TehriGarhwal. Indian J Community Health 2011;23:81-3.  Back to cited text no. 14
Bansal SK, Saxena V, Kandpal SD, Gray WK, Walker RW, Goel D. The prevalence of hypertension and hypertension risk factors in a rural Indian community: A prospective door-to-door study. J Cardiovasc Dis Res 2012;3:117-23.  Back to cited text no. 15
  [Full text]  
Deshmukh PR, Gupta SS, Bharambe MS, Aliye CM, Kaur S, Garg BS. Prevalence of hypertension, its correlates and levels of awareness in Rural Wardha, Central India. Journal of Health & Population in Developing Countries. 2005. Available from: http://www.jhpdc.unc. edu. [Last accessed on 2014 Jul 01].  Back to cited text no. 16
Sadhukhan SK, Dan A. Multifactorial analysis of blood pressure variations in a rural community of West Bengal. Indian J Community Med 2005;30:57-9.  Back to cited text no. 17
  [Full text]  
Khan RJ, Stewart CP, Christian P, Schulze KJ, Wu L, Leclerq SC, et al. A cross-sectional study of the prevalence and risk factors for hypertension in rural Nepali women. BMC Public Health 2013;13:55.  Back to cited text no. 18
Manandhar K, Koju R, Sinha NP, Humagain S. Prevalence and associated risk factors of hypertension among people aged 50 years and more in Banepa Municipality, Nepal. Kathmandu Univ Med J (KUMJ) 2012;10:35-8.  Back to cited text no. 19
Vimala A, Ranji SA, Jyosna MT, Chandran V, Mathews SR, Pappachan JM. The prevalence, risk factors and awareness of hypertension in an urban population of Kerala (South India). Saudi J Kidney Dis Transpl 2009;20:685-9.  Back to cited text no. 20
[PUBMED]  [Full text]  
Meshram II, Arlappa N, Balkrishna N, Rao KM, Laxmaiah A, Brahmam GN. Prevalence of hypertension, its correlates and awareness among adult tribal population of Kerala state, India. J Postgrad Med 2012;58:255-61.  Back to cited text no. 21
[PUBMED]  [Full text]  
Midha T, Idris MZ, Saran RK, Srivastav AK, Singh SK. Prevalence and determinants of hypertension in the urban and rural population of a North Indian district. East Afr J Public Health 2009;6:268-73.  Back to cited text no. 22
Parker ED, Schmitz KH, Jacobs DR Jr., Dengel DR, Schreiner PJ. Physical activity in young adults and incident hypertension over 15 years of follow-up: The CARDIA study. Am J Public Health 2007;97:703-9.  Back to cited text no. 23
Jackson C, Herber-Gast GC, Brown W. Joint effects of physical activity and BMI on risk of hypertension in women: A longitudinal study. J Obes 2014;2014:271532.  Back to cited text no. 24
Steyn K, Bradshaw D, Norman R, Laubscher R. Determinants and treatment of hypertension in South Africans: The first Demographic and Health Survey. S Afr Med J 2008;98:376-80.  Back to cited text no. 25
Todkar SS, Gujarathi VV, Tapare VS. Period prevalence and sociodemographic factors of hypertension in rural Maharashtra: A cross-sectional study. Indian J Community Med 2009;34:183-7.  Back to cited text no. 26
[PUBMED]  [Full text]  
Ntuli ST, Maimela E, Alberts M, Choma S, Dikotope S. Prevalence and associated risk factors of hypertension amongst adults in a rural community of Limpopo Province, South Africa. Afr J Prim Health Care Fam Med 2015;7:847.  Back to cited text no. 27
Shah A, Afzal M. Prevalence of diabetes and hypertension and association with various risk factors among different Muslim populations of Manipur, India. J Diabetes Metab Disord 2013;12:52.  Back to cited text no. 28
Arrey WT, Dimala CA, Atashili J, Mbuagbaw J, Monekosso.GL. Hypertension, an emerging problem in rural cameroon: Prevalence, risk factors, and control. Int J Hypertens 2016;2016:5639146.  Back to cited text no. 29
Grimsrud A, Stein DJ, Seedat S, Williams D, Myer L. The association between hypertension and depression and anxiety disorders: Results from a nationally-representative sample of South African adults. PLoS One 2009;4:e5552.  Back to cited text no. 30


  [Table 1], [Table 2], [Table 3], [Table 4]


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