|Year : 2019 | Volume
| Issue : 2 | Page : 43-48
Prevalence and predictors of hypertension among adults of urban Lucknow, India: A community-based study
Syed Esam Mahmood, Ausaf Ahmad, Saurabh Kashyap
Department of Community Medicine, Integral Institute of Medical Sciences and Research, Lucknow, Uttar Pradesh, India
|Date of Web Publication||28-Jun-2019|
Dr. Ausaf Ahmad
Room No. 107, Resident Hostel, Integral University, Dasauli Road, Lucknow - 226 026, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Background and Objective: Hypertension is an important public health problem in both economically developing and developed countries. In India, recent community surveys have reported that the prevalence of hypertension has risen among urban and rural inhabitants. This study was conducted to find out the prevalence of hypertension and to identify the risk factors among adults residing in urban areas of Lucknow.
Materials and Methods: The cross-sectional field study involved a survey of 300 respondents, aged 18 years and above using the stratified random sampling and probability proportionate to size technique. A study tool which contained risk factor questionnaire and physical measurements of height, weight, and blood pressure were used to collect the data. Data analysis was performed using the SPSS version 16. The Chi-squared test and logistic regression analysis were used to analyze the data.
Results: The prevalence of hypertension was 14.67% among urban adults. Hypertension was significantly higher among individuals aged >40 years and those who consumed tobacco products. A higher proportion of the hypertensives belonged to the illiterate category. There was a significant difference in hypertension prevalence in different education classes. Respondents living in overcrowded houses had higher odds of having hypertension than those not experiencing overcrowding.
Conclusion: Age, education, and overcrowding were independent risk factors of hypertension. Prevention measures targeting the modifiable risk factors associated with hypertension should be taken.
Keywords: Hypertension, risk factors, prevalence
|How to cite this article:|
Mahmood SE, Ahmad A, Kashyap S. Prevalence and predictors of hypertension among adults of urban Lucknow, India: A community-based study. Heart India 2019;7:43-8
|How to cite this URL:|
Mahmood SE, Ahmad A, Kashyap S. Prevalence and predictors of hypertension among adults of urban Lucknow, India: A community-based study. Heart India [serial online] 2019 [cited 2021 Jan 20];7:43-8. Available from: https://www.heartindia.net/text.asp?2019/7/2/43/261837
| Introduction|| |
Hypertension is an important public health issue for economically developed and developing countries. As per the World Health Organization (WHO) report, about 40% of people aged >25 years had hypertension in 2008. Due to the growth and aging of the population worldwide, the number of people with uncontrolled hypertension was reported to have increased between 1980 and 2008. Almost 13.5% of the global total, approximately 7.6 million premature deaths were endorsed to high blood pressure. About 54% of stroke and 47% of ischemic heart disease worldwide were attributable to high blood pressure. Hypertension has been associated with enlarged threat of coronary artery disease, and cardiovascular and cerebrovascular diseases are also cause by hypertension., A meta-analysis also reported that prehypertension, even in the low range is associated with higher risk of cardiovascular disease and also with chronic kidney diseases., The situation is serious in the southeast Asian region with studies reporting hypertension as an important risk factor for attributable burden of disease in the region., An alarming rise of hypertension projected in 2005 and 2010 by the study Global Burden of Hypertension and Global Burden of Disease Study, respectively, depicted severe image for the Indian inhabitants., Hypertension remains a challenge in various portions of the world after lots of programs for the prevention of hypertension. Observing at the prevailing load of hypertension, the Government of India has launched many programs for the prevention and control of diabetes, cancer, and cardiovascular diseases control of disease at the community level. The literature on the prevalence and risk factors of hypertension in Lucknow was scarce, thereby the present study was conducted to find out the prevalence of hypertension and to identify the risk factors.
| Materials and Methods|| |
The cross-sectional study was carried out among adults who were aged 18 years and above, who resided in the field practice areas of the Urban Health Training Center of the Department of Community Medicine, Integral institute of medical sciences and research, Lucknow, India. This urban health center is situated in Sarvodaynagar and caters to a huge urban population of Lucknow. Optimal sampling size was calculated on the basis of prior prevalence rate of hypertension of 25.89%. The sample size was calculated by the formula 4PQ/L 2, where P is the prevalence; Q is 100-P and L is the absolute precision, i.e., 5%. Approximate sample size came out to be 300. All individuals gave consent and participated in the study. Stratified random sampling was used to select the study participants. Demographically, the population residing around urban health center of Lucknow has people of different religion, socioeconomic status, and other different characteristics. Mohalla/area (strata) having same group of people. Stratified sampling method was appropriate for this nonhomogeneous nature of sample. All mohallas in the study were primary sample units (PSUs), i.e., strata. All adults from the PSUs selected formed sampling units. Number of adults to be taken for the survey from each mohalla was decided according to the probability proportionate to size technique. A structured pretested and predesigned questionnaire was used to assess the study participants' self-reported behavioral and lifestyle risk factors for hypertension (smoked and smokeless tobacco used, alcohol consumed, level of physical activity done, and type of diet consumed were recorded), the measurement of participant's blood pressure, and anthropometrical parameters. Modified Prasad's classification was applied to measure the individual's socioeconomic status. Questions to assess salt intake were asked to determine the average number of days required to consume one pack of salt by one household as used in the another study. Fat intake was calculated using 24 hour recall dietary survey method amongst individuals. High fat intake was defined as more than 20gms of fat consumed per day both for men and women.,, For physical examination, standardized calibrated mercury column type sphygmomanometer, stethoscope, common weighing machine, and measuring tape were used. During the course of the interview, two measurements of blood pressure on each study participant with a mercury column sphygmomanometer were made using a standardized technique 30 min apart in the sitting position. Subsequently obtaining sociodemographic data from the subject, measurement of first blood pressure were recorded and second blood pressure were recorded later clinical investigation. Blood pressure measurements were made on the left arm of each study participant, using a cuff of appropriate size at the level of the heart. The cuff pressure was inflated 30 mm Hg above the level at which radial pulse disappeared and then deflated slowly at the rate of about 2 mm/s, and the readings were recorded to the nearest 2 mm Hg. In case where the two readings differed by over 10 mm of Hg, a third reading was obtained, and the three measurements were averaged. The pressures at which sound appeared and disappeared were taken as systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively. Hypertension definition of 140/90 mm Hg or higher was used as per the 2018 ESC/ESH Guidelines for the management of arterial hypertension. Body weight was measured (to the nearest 0.5 kg) with the participant standing motionless on the weighing scale, feet about 15 cm apart, and weight equally distributed on the each leg. Participants were instructed to wear minimum outwear (as culturally appropriate) and no foot wear while their weight was being measured. Height was measured (to the nearest 0.5 cm) with the participant standing in an erect position against a vertical surface, and the head positioned so that the top of the external auditory meatus was level with the inferior margin of the bony orbit (Frankfurt's plain). Weight in kilograms divided by weight in meters squared for body mass index (BMI). Based on their BMI, individuals were classified into four groups, namely thin (BMI <18.5), normal (BMI = 18.5–24.9), overweight (BMI = 25.0–29.9), and obese (BMI >30.0) as per the WHO. Household overcrowding was calculated by dividing the number of inhabitants divided by the number of rooms criteria.
Data entry and statistical analysis were performed using the Microsoft Excel and SPSS windows version 16.0 software (SPSS Inc., Chicago, IL, USA). Tests of significance such as the Chi-squared test are applied to find out the results. Univariate analysis was performed using the SBP and DBP as the dependent variables and the various risk factors identified as the independent variables. Multiple logistic regression analysis was performed using hypertension as the dependent variables and the risk factors found significant as the independent variables. In 95% of confidence interval, odds ratios were computed for the association among the hypertension and independent variables. The level of statistical significance was at P < 0.05.
| Results|| |
Overall, 44 (14.67%) of 300 respondents studied were found hypertensive. [Table 1] shows the sociodemographic characteristics of nonhypertensive (n = 256) and hypertensive (n = 44) groups. A higher proportion of the hypertensives were in the illiterate category. Hypertension proportion in different education classes were found significant. There was no statistically significant difference in the groups in marital status, but significant difference was seen in occupation, overcrowding, and socioeconomic status categories [Table 1].
[Table 2] shows the identified risk factors among hypertensive and nonhypertensive groups. There was a significant difference in tobacco intake between the two groups. The prevalence of hypertension was not significantly higher among those who consumed alcohol than the other group. Involvement in vigorous intensity activity rate (carrying or lifting heavy loads and digging or construction work) causing large increases in breathing or heart rate for at least 10 min continuously showed highly significant difference between the two groups. A significantly higher number of the study participants were found hypertensive in the overweight and obese group as compared to the other group [Table 2].
|Table 2: Distribution of study participants with respect to risk factors of hypertension|
Click here to view
The classification table shows that overall model gives 91% correct prediction. As shown in [Table 2], of 256 participants who were nonhypertensives, this model predicts 253 to be nonhypertensives and three to be hypertensives. Of 44 hypertensive participants, the model predicts 20 to be hypertensives and 24 to be nonhypertensives. Thus, it predicts hypertensive participants with 45.5% accuracy and nonhypertensive with 98.8% accuracy [Table 3].
[Table 4] shows the results of multivariate analysis for hypertension and its risk factors. Age, gender, education, overcrowding, consumption of smoked tobacco product, and involvement in vigorous intensity activity were independently associated with hypertension. Multiple logistic regression was applied to detect independent association of factors. DBP or SBP is taken as the dependent variable. As shown in [Table 4], age group <40 years has lesser odds of having hypertension than age group >40 years. In education classes, taking illiterate as baseline, those educated up to primary and high school level had significantly higher odds of hypertension. Similarly, in occupation categories, taking unemployed and homemakers as baseline, those who were professional had significantly higher odds of hypertension. Female participants had lesser odds of having hypertension than males. Participants belonging to houses with overcrowding had higher odds of having hypertension than those who did not experience overcrowding [Table 4].
| Discussion|| |
The present study showed that the prevalence of hypertension was significantly higher in individuals >40 years as compared to those <40 years. As age increases, hypertension increases. Vasan et al., in their study, conducted among 1298 participants also found the significant association of hypertension with age. The percentage of hypertensives among the illiterate respondents was observed slightly higher as compared to the literate ones. Hypertension proportion in different education classes was found significant. Wang et al. also found that both SBP and DBP were inversely associated with the level of school education independent of all other risk factors. Education makes the people aware of the disease and the precautions to be undertaken by a healthy individual. No significant association was found between hypertension and marital status, but significant differences were found in different occupation classes. These are consistent with the findings reported by Tsutsumi et al. which revealed that occupation and related stress were independent risk factors of hypertension. Univariate analysis showed hypertension more prevalent in professional and clerk classes. The confounding factors were adjusted in the multivariate analysis which showed that skilled personnel had significantly higher odds of hypertension. Higher prevalence of hypertension was found in the upper class as compared to other classes. Similar findings were reported in a study conducted among Lucknow adults. Societies that are in transitional stage of economic and epidemiological change have a higher prevalence of hypertension among the upper socioeconomic groups. In the present study, overweight and obese participants had higher prevalence of hypertension as compared to the participants with normal weight whereas underweight participants showed higher prevalence. BMI was found to be not significantly associated with hypertension. Inconsistent findings in relation to BMI were also reported by studies conducted in Odisha and West Bengal. Among risk factors, a significant association was found with tobacco products intake in this study. This is consistent with previous where tobacco use has been found to be associated with hypertension., There was a significant association of hypertension with smoking in our study. In addition, smoking was found to be significantly associated with hypertension in the Maharashtra study. Hypertension was not significantly associated with individuals who consume alcohol than those who did not in this study. On the contrary, alcohol has been reported as an independent risk factor by other authors as well.,
Respondents belonging to overcrowded houses had higher odds of having hypertension than those not belonging to the overcrowded ones in this study. Housing instability (living in overcrowded houses), a growing public health problem, may be an independent environmental risk factor for hypertension, but limited prospective data exist.
| Conclusion|| |
It can be concluded that there is a significant burden of hypertension in urban areas in Lucknow. Age, education, and overcrowding were independent risk factors of hypertension in the present study. This study projects the need of an early detection of hypertension at the community level, which can be achieved by recurrent periodic screening of the individuals. Prevention measures targeting the modifiable risk factors associated with hypertension should be taken.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kearney PM, Whelton M, Reynolds K, Whelton PK, He J. Worldwide prevalence of hypertension: A systematic review. J Hypertens 2004;22:11-9.
Danaei G, Finucane MM, Lin JK, Singh GM, Paciorek CJ, Cowan MJ, et al.
National, regional, and global trends in systolic blood pressure since 1980: Systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5·4 million participants. Lancet 2011;377:568-77.
Lawes CM, Vander Hoorn S, Rodgers A. International Society of Hypertension. Global burden of blood-pressure-related disease, 2001. Lancet 2008;371:1513-8.
Qureshi AI, Suri MF, Kirmani JF, Divani AA, Mohammad Y. Is prehypertension a risk factor for cardiovascular diseases? Stroke 2005;36:1859-63.
Wu S, Huang Z, Yang X, Li S, Zhao H, Ruan C, et al.
Cardiovascular events in a prehypertensive Chinese population: Four-year follow-up study. Int J Cardiol 2013;167:2196-9.
Huang Y, Wang S, Cai X, Mai W, Hu Y, Tang H, et al.
Prehypertension and incidence of cardiovascular disease: A meta-analysis. BMC Med 2013;11:177.
Kim MJ, Lim NK, Park HY. Relationship between prehypertension and chronic kidney disease in middle-aged people in Korea: The Korean genome and epidemiology study. BMC Public Health 2012;12:960.
Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al.
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 2012;380:2224-60.
Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJ. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. Lancet 2006;367:1747-57.
Kishore J. National Health programs of India. 11th
ed. New Delhi, India: National Health Programs of India, Century Publications; 2014.
Mahmood SE, Srivastava JP, Bhardwaj P, Zaidi ZH, Mathur KP. Prevalence and risk factors of hypertension among adults in Lucknow, India. Natl J Res Community Med 2017;6:163-70.
Agarwal A. Social classification: The need to update in the present scenario. Indian J Community Med 2008;33:50-1.
] [Full text]
Agrawal VK, Bhalwar R, Basannar DR. Prevalence and determinants of hypertension in a rural community. Med J Armed Forces India 2008;64:21-5.
National Institutes of Medical Statistics, Indian Council of Medical Research (ICMR), 2009. IDSP Non Communicable Disease Risk Factors Survey. Interviewers Guide. Phase I States of India 2007-2008.
Gopalan C, Rama Sastri BV, Balasubramanian SC. Nutritive Value of Indian Foods. 11th
ed. Hyderabad: National Institute of Nutrition, Indian Council of Medical Research; 2004.
Indian Council of Medical Research. Nutrient Requirements and Recommended Dietary Allowance for Indians. Hyderabad: National Institute of Nutrition; 1989.
World Health Organization. Hypertension Control. Technical Report Series. World Health Organization; 1996.
Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al.
2018 ESC/ESH guidelines for the management of arterial hypertension. Eur Heart J 2018;39:3021-104.
Physical status: The use and interpretation of anthropometry. Report of a WHO expert committee. World Health Organ Tech Rep Ser 1995;854:1-452.
Vasan RS, Beiser A, Seshadri S, Larson MG, Kannel WB, D'Agostino RB, et al.
Residual lifetime risk for developing hypertension in middle-aged women and men: The Framingham heart study. JAMA 2002;287:1003-10.
Wang Y, Chen J, Wang K, Edwards CL. Education as an important risk factor for the prevalence of hypertension and elevated blood pressure in Chinese men and women. J Hum Hypertens 2006;20:898-900.
Tsutsumi A, Kayaba K, Tsutsumi K, Igarashi M. Jichi Medical School Cohort Study Group. Association between job strain and prevalence of hypertension: A cross sectional analysis in a Japanese working population with a wide range of occupations: The Jichi medical school cohort study. Occup Environ Med 2001;58:367-73.
Patnaik L, Sahani NC, Sahu T, Sethi S. A study on hypertension in urban slum of Brahmapur, Orissa. J Community Med 2007;3:1-10.
Bose K, Ghosh A, Roy S, Gangopadhyay S. Blood pressure and waist circumference: An empirical study of the effects of waist circumference on blood pressure among Bengalee male jute mill workers of Belur, West Bengal, India. J Physiol Anthropol Appl Human Sci 2003;22:169-73.
Pandey A, Patni N, Sarangi S, Singh M, Sharma K, Vellimana AK, et al.
Association of exclusive smokeless tobacco consumption with hypertension in an adult male rural population of India. Tob Induc Dis 2009;5:15.
Shanthirani CS, Pradeepa R, Deepa R, Premalatha G, Saroja R, Mohan V. Prevalence and risk factors of hypertension in a selected South Indian population – The Chennai urban population study. J Assoc Physicians India 2003;51:20-7.
Manimunda SP, Sugunan AP, Benegal V, Balakrishna N, Rao MV, Pesala KS. Association of hypertension with risk factors and hypertension related behaviour among the aboriginal Nicobarese tribe living in car Nicobar Island, India. Indian J Med Res 2011;133:287-93.
] [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.
Vijayaraghavan M, Kushel MB, Vittinghoff E, Kertesz S, Jacobs D, Lewis CE, et al.
Housing instability and incident hypertension in the CARDIA cohort. J Urban Health 2013;90:427-41.
[Table 1], [Table 2], [Table 3], [Table 4]