|Year : 2020 | Volume
| Issue : 4 | Page : 178-183
Assessment of 5-year risk of cardiovascular events among adults residing in an urban underprivileged area of Bangalore city: A community-based cross-sectional study
Nancy Angeline Gnanaselvam1, Avita Rose Johnson1, Somya Andrea Gomes2, JV Jeskezia2, Niresh Chandran1, Suchitra Bajaj3
1 Department of Community, St. John's Medical College, Karnataka, India
2 Medical Student, St. John's Medical College, Karnataka, India
3 Department of Healthcare, Biocon Foundation, Karnataka, India
|Date of Submission||11-Aug-2020|
|Date of Decision||17-Aug-2020|
|Date of Acceptance||07-Dec-2020|
|Date of Web Publication||31-Dec-2020|
Dr. Avita Rose Johnson
Department of Community Health, St. Johnfs Medical College, Bengaluru - 560 034, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Cardiovascular disease (CVD) is the major cause of premature morbidity and mortality in India and is undergoing an epidemiological transition, now affecting the urban poor. It is important to assess patients for CVD risk and mitigate risk factors as a primary mode of prevention of CVD accordingly.
Objective: The objective of the study was to assess the 5-year risk of cardiovascular events and the prevalence of CVD risk factors in an underprivileged area of Bangalore City.
Methods: Community-based house-to-house survey of all adults aged 30 years and above, using an interview schedule on Epicollect mobile application, capturing sociodemographic details and CVD risk factors based on the INTERHEART risk assessment which included dietary risk factors, smoking and alcohol, physical activity, and central obesity. Blood pressure, random blood sugar, height, weight, and waist circumference measurement were done. The National Health and Nutrition Examination Survey CVD risk assessment charts were used to calculate the 5-year risk of a cardiovascular event.
Results: Of 1184 study participants, 23% had moderate risk (10%–20%) and 30% had high risk (>20%) of a cardiovascular event in the next 5 years. Factors such as being not currently married, belonging to a religious minority, lower education, not being gainfully employed, belonging to a joint family, and salty food consumption were significantly associated with higher CVD risk.
Conclusion: Urban underprivileged areas with undermined social determinants of health have significantly high burden of CVD risk and hence require a holistic approach to CVD risk assessment and noncommunicable diseases care starting with easy to use CVD risk assessment charts by community level health workers.
Cardiovascular diseases risk assessment, diabetes, hypertension, noncommunicable diseases, urban health
Keywords: Cardiovascular diseases risk assessment, diabetes, hypertension, noncommunicable diseases, urban health
|How to cite this article:|
Gnanaselvam NA, Johnson AR, Gomes SA, Jeskezia J V, Chandran N, Bajaj S. Assessment of 5-year risk of cardiovascular events among adults residing in an urban underprivileged area of Bangalore city: A community-based cross-sectional study. Int J Non-Commun Dis 2020;5:178-83
|How to cite this URL:|
Gnanaselvam NA, Johnson AR, Gomes SA, Jeskezia J V, Chandran N, Bajaj S. Assessment of 5-year risk of cardiovascular events among adults residing in an urban underprivileged area of Bangalore city: A community-based cross-sectional study. Int J Non-Commun Dis [serial online] 2020 [cited 2022 Aug 8];5:178-83. Available from: https://www.ijncd.org/text.asp?2020/5/4/178/305998
| Introduction|| |
In South East Asia, the onset of ischemic heart disease is 10 years earlier compared to developed countries. Poor and underprivileged communities in India have limited or no access to quality diagnostic facilities and expert medical consultation, and the adoption of nontraditional or Western lifestyle and behaviors has led to a surge in cardiovascular disease (CVD) among those of disadvantaged socioeconomic background.
The use of risk assessment tools for the prediction of CVD can save health-care costs through primary prevention aimed at mitigating the common risk factors for CVD. In resource-limited settings, the National Health and Nutrition Examination Survey (NHANES) nonlaboratory-based risk prediction charts for CVD are useful in assessing CVD risk over a 5-year period. CVD risk assessment charts can assist in health-care delivery planning and at an individual level helps in forecasting CVD and intervening to prevent the same. There is a paucity of literature on prediction of fatal and nonfatal cardiovascular events in urban poor population.
This study was therefore conducted with the objective of assessing the 5-year risk of cardiovascular events and estimating the prevalence of CVD risk factors in an underprivileged area of Bangalore City.
| Methods|| |
Written informed consent was obtained from all participants. Institutional ethics approval was obtained.
Selection and description of participants
The Urban Health Training Centre of St. John's Medical College is located at Austin Town and provides health care to the surrounding underprivileged community. As per the Health Management Information System of the center, which is digitized and includes household-level data of this community, the population served is 6285. Adults aged 30 years and above, residing in the mentioned community were included in this study. We excluded those patients with a history of CVD such as coronary artery disease, transient ischemic attack, and stroke. Based on a previous study in a rural area of Bangalore district, where 7.6% of adults were found to have high risk of developing a cardiovascular event, using the NHANES nonlaboratory CVD risk prediction chart, the sample size was calculated with 20% relative precision and 95% confidence limits to be 1167. However, since the patients would have blood pressure and blood sugar tested as a part of this study, it was felt that no adult in this underprivileged community should miss this opportunity for screening and subsequent treatment if required. It was therefore decided to forgo sampling and instead invite all the adults in the community to be a part of the study. Hence, the universal sampling technique was employed.
It is a cross-sectional study. House-to-house visits were conducted by a team of trained community health workers (CHWs). Adults aged 30 and above were invited to participate in the study. Written informed consent was obtained from all participants. Participants with mental illness that prevented them from understanding the questions were excluded from the study. Participants who were not present even after two visits by the CHWs were also excluded from the study.
The questionnaire used in this study had three parts: (i) sociodemographic details including Modified BG Prasad socioeconomic classification, (ii) CVD risk factor assessment based on the INTERHEART risk score, which included dietary risk factors, smoking and alcohol, physical activity, and central obesity, (iii) assessment and classification into low, moderate, or high risk of a cardiovascular event over the next 5 years based on nonlaboratory-based NHANES CVD risk prediction chart. The NHANES chart was chosen for this study, as it includes overweight/obesity, unlike the nonlaboratory WHO-ISH chart which excludes body mass index (BMI). Diabetes: random blood sugar reading of =200 mg/dl or self-report of being diabetic; systolic hypertension: systolic blood pressure of =120 mmHg; smoking: ever smoked in the last 1 year; BMI: expressed as weight in kg per height in m2. BMI cutoff values were derived from the Asian Indian adults' classification. A waist circumference cutoff of =90 cm for men and =80 cm for women was considered as a measure of central obesity in our study. Blood pressure was used using a calibrated digital sphygmomanometer. Two readings were taken 15 min apart, with the patient in sitting position, and the average systolic and diastolic blood pressures were noted. Random blood sugar was estimated using a digital glucometer. Height was measured to the nearest 0.1 cm using a portable stadiometer, and weight was recorded to the nearest 100 g using a calibrated digital weighing scale. Waist circumference was measured to the nearest 0.1 cm in the horizontal plane midway between the lowest rib and the iliac crest, using a nonstretchable tape, ensuring the tape was snug but not tight. The data were collected in Epicollect application on mobile phone and later exported to Microsoft Excel.
The data were analyzed using Statistical Package for the Social Sciences Version 20, International Business Machines Corporation (IBM), Armonk, New York, United States. Sociodemographic and risk factors variables were described using frequencies and proportions. Continuous variables such as age were analyzed as mean and standard deviation. Logistic regression analysis was done to assess the association between the various exposure variables and the outcome variable (high risk of a cardiovascular event in the next 5 years). Exposure variables considered in the regression model of sociodemographic variables were marital status, religion, education, occupation, socioeconomic status, and type of family. In the risk factors for CVD model, the variables included were alcohol, consumption of fruits and vegetable, oil, salt, red meat, junk food and occupation involving vigorous activity. Adjusted odds ratio with 95% confidence interval was calculated. P < 0.05 was considered statistically significant for all analyses.
| Results|| |
A total of 1188 participants participated in this study. The sociodemographic profile is depicted in [Table 1].
The risk factors as in the NHANES CVD risk prediction chart are mentioned in [Table 2]. Most of our study participants are females, nonsmokers, and nondiabetics.
|Table 2: Risk factors in the national health and nutrition examination survey cardiovascular disease risk prediction chart (n=1188)|
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Most consume red meat, junk food, and salt-rich food regularly. Fruits and vegetable consumption was significantly less as compared to the recommended servings. Nearly all the participants (99.4%) had a BMI of =23, which is the Asian cutoff for overweight.
Nearly 30% of the patients were at high risk (>20% chance) and 23% were of moderate risk (10%–20% chance) of developing a cardiovascular event (fatal and nonfatal) in the next 5 years.
Being single, belonging to minority religions, lower educational qualifications, not gainfully employed, and living with a joint family were significantly associated with a higher risk for CVD [Table 3].
|Table 3: Sociodemographic characteristics and cardiovascular disease risk among the study participants|
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History of consumption of alcohol and consumption of salty food was significantly associated with high risk for CVD [Table 4].
| Discussion|| |
Urban underprivileged areas in India are characterized by poverty, infectious diseases, and nutritional diseases. However, noncommunicable diseases which were once considered as the diseases of the rich are becoming increasingly common among this population. The study population mostly belonged to lower socioeconomic class and considering the universal concept of marriage in India, most of the study population were married. Our study population has a significant proportion of religious minorities (Muslims and Christians). Urban slums have more number of religious and caste minorities as compared to national averages as urban residences are thought to be free from strict social norms and ways to economic emancipation. Due to their easy access to education, through government schools, most of our study population were educated up till high school. In our study, most of the population was not gainfully employed. This is due to the larger proportion of women in the study, as the data collection was conducted during work hours when most adult men are out at work, away from their home. This also reflects the unpaid labor women provide to the families in homemaking. Most of our study population mentioned that they were working as domestic maids, drivers, unskilled work in construction, and housework. This also reflects the fact that, even though slums are close to rapidly developing cities, due to a lack of higher education, employment opportunities are scarce. In our study, most of the study population live in nuclear families. Owing to urbanization, education, and demographic transition, traditional joint family system has given way to more of a nuclear family setup.
More than half of the study population was hypertensive. This finding is in line with a study done in Kolkata slums where 42% of the population were hypertensive. Only 3.1% of our study population smoke tobacco. This is in contrast to the national averages where 47% of males smoke tobacco. Only 1.7% of the study population reported to consuming alcohol for 3 or more days a week even though the national prevalence is 2.6%. The low prevalence of smoking and alcohol consumption could be due to social desirability bias since the questions in the study were asked by health workers who were familiar to the community. Among the study participants, 21.5% were diabetic. This is in line with a study done by Shivaraj et al. in urban slums of Bangalore where the prevalence of diabetes was 32%. In general, slum areas have a higher prevalence of diabetes due to lifestyle factors. Nearly all the participants of the study population were overweight or obese. This is a significant finding. Due to lack of physical activity, lack of access to recreational facilities, inadequate consumption of fruits and vegetables, the urban poor are often overweight and obese. In poor households, when the issue of hunger itself remains unaddressed, starchy, and grain-related foods receive top most priority in consumption as compared to expensive fruits and vegetables. It was also found that one in ten participants consumed oil in excess of the recommended limit of 500 ml. The distribution of vegetable oil through the public distribution system, increasing incomes, urbanization, retailing strategies, and increasing consumption patterns of fried foods have attributed to this risk factor. More than three-fourth of the study population consumed salty food in the previous week of the interview. This finding reflects the general Indian dietary pattern, in which salt consumption is 11 g/day on an average as compared to the recommended 5 g a day. Generally, the Indian population prefers chicken meat consumption. However, in our study area, due to religious and caste reasons, there was increased consumption of red meat. More than half of our study population reported junk food consumption. This could be due to barriers of financial, educational, and attitude reasons. This urban underprivileged study area has plenty of small shops selling cheap salty fried snacks attractively packed and displayed to be eye-catching. Only 1.2% of the study population walk or cycle to work. This could be due to the distant location of their workplaces, where public transport is preferred. In our study, 27.8% of participants were found to have a moderate-to-high risk for coronary heart disease in the next 5 years. However, in a study done in a rural area by Ghorpade et al., 17% of the study population had a moderate-to-high risk for CVDs. The difference could be explained by the study setting our study was in an urban community with resultant practices of unhealthy diet and low physical activity. This is exemplified by another study done by Patil et al. in an urban health center in Maharashtra, which reported that 28% of the population had moderate to high risk for CVDs, similar to our study.
Being single, belonging to minority religions, lower educational qualification, not gainfully employed, and belonging to joint family were associated to a higher risk for CVDs in our study. Marital status was found to be a protective factor for CVDs. Spousal support and care, social acceptance, and financial benefits associated with marriage could have attributed to this finding. Lower educational qualification denotes multiple social disadvantages such as lack of access to health care, lack of knowledge on health seeking, and it also affects the other determinants of health in general like access to healthy diet. Healthy worker effect and younger age of those gainfully employed could have had a lowering effect on the CVD risk. Furthermore, homemakers have limited access to recreational facilities, and the stress associated with unpaid work could have made them more prone for CVD risk. Joint families in slums translate into crowded surroundings, lesser income to share, and more dependents. This stress could have made these patients more at risk for CVD. Salty food consumption was significantly associated with CVD risk in our study, probably as salty food consumption also means higher risk for hypertension and consumption of transfats as an accompaniment.
These findings point out to the larger picture of social determinants of health which regulate the conditions of lives such as changing pattern of sociocultural norms, dietary practices, lifestyle and behavior, health policies, globalization, and urbanization as well as social exclusion, marginalization of migrants and minorities, all ofwhich predispose patients to higher risk for CVD.
| Conclusion|| |
Our study in an urban underprivileged area found that 30% of the patients were at high risk (>20% chance) and 23% were at moderate risk (10%–20% chance) of developing a cardiovascular event (fatal and nonfatal) in the next 5 years. Factors such as being not currently married, belonging to a religious minority, lower education qualification, not being gainfully employed, belonging to a joint family, and salty food consumption were significantly associated with higher CVD risk. In the short term, what is needed is training of grassroot level health workers in CVD risk assessment with easy to use CVD risk stratification charts, health education, and referral of those at higher risk of CVD for further evaluation and management. In the long term, we need policies to create a “cardiovascular friendly environment” with easy access to healthful nutrition and physical activity, as well as health system reforms focused on social transformations to end poverty, hunger, and social exclusion to effectively address the determinants of CVD.
Ethical approval was obtained from the Institutional Ethics Committee, St. John's National Academy of Health Sciences.
We acknowledge the effort of Community Health workers of Biocon Foundation who conducted the fieldwork of the risk assessment.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Siegel Karen R, Patel Shivani A, Ali Mohammed K. Non-communicable diseases in South Asia: Contemporary perspectives. Br Med Bull 2014;111:31-44.
Krishnan MN. Coronary heart disease and risk factors in India – On the brink of an epidemic? Indian Heart J 2012;64:364-7.
Pandya A, Weinstein MC, Gaziano TA. A comparative assessment of non-laboratory-based versus commonly used laboratory-based cardiovascular disease risk scores in the NHANES III population. PLoS One
Nethan S, Sinha D, Mehrotra R. Non communicable disease risk factors and their trends in India. Asian Pac J Cancer Prev 2017;18:2005-10.
Otgontuya, D, Oum S, Buckley BS, Bonita R. Assessment of total cardiovascular risk using WHO/ISH risk prediction charts in three low and middle income countries in Asia. BMC Public Health
Upadhyay RP. An overview of the burden of non-communicable diseases in India. IranS J Public Health 2012;41:1-8.
Fathima FN, Raghunath D, Hegde SK, Agrawal T, Misquith D, Sreekantiah P. Predictive accuracy of a cardiovascular disease risk prediction model in rural south India: A community based retrospective cohort study. Indian J Community Health 2015;27:110-6.
Dalvi TM, Khairnar MR, Kalghatgi SR. An update of B.G. Prasad and Kuppuswamy socio-economic status classification scale for Indian population. Indian J Pediatr 2020;87:567-8.
McGorrian C, Yusuf S, Islam S, Jung H, Rangarajan S, Avezum A, et al
. Estimating modifiable coronary heart disease risk in multiple regions of the world: The INTERHEART Modifiable Risk Score. Eur Heart J 2011;32:581-9.
Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: The NHANES I Follow-up Study cohort. Lancet 2008;371:923-31.
Lim JU, Lee JH, Kim JS, Hwang YL, Kim TH, Lim SY, et al
. Comparison of World Health Organization and Asia-Pacific body mass index classifications in COPD patients. Int J Chron Obstruct Pulmon Dis 2017;12:2465-75.
Pratyush DD, Tiwari S, Singh S, Singh SK. Waist circumference cutoff and its importance for diagnosis of metabolic syndrome in Asian Indians: A preliminary study. Indian J Endocrinol Metab 2012;16:112-5.
Gowshall M, Taylor-Robinson SD. The increasing prevalence of non-communicable diseases in low-middle income countries: The view from Malawi. Int J Gen Med 2018;11:255-64.
Mosse D. Caste and development: Contemporary perspectives on a structure of discrimination and advantage. World Dev 2018;110:422-36.
Subbaraman R, O'Brien J, Shitole T, Shitole S, Sawant K, Bloom DE, et al. Off the map:
The health and social implications of being a non-notified slum in India. Environ Urban 2012;24:643-63.
Banerjee S, Mukherjee TK, Basu S. Prevalence, awareness, and control of hypertension in the slums of Kolkata. Indian Heart J 2016;68:286-94.
Shah S, Dave B, Shah R, Mehta TR, Dave R. Socioeconomic and cultural impact of tobacco in India. J Family Med Prim Care 2018;7:1173-6.
] [Full text]
Eashwar VM, Umadevi R, Gopalakrishnan S. Alcohol consumption in India- An epidemiological review. J Family Med Prim Care 2020;9:49-55.
] [Full text]
Shivaraj BM, Kiran BV, Ranganath T. Prevalence of hypertension and diabetes mellitus at selected urban slums in Bangalore, India: A cross sectional study. Int J Community Med Public Health 2017;3:74-7.
Raj JP, Ploriya S. Prevalence of obesity among rehabilitated urban slum dwellers and altered body image perception in India (PRESUME). Indian J Endocrinol Metab 2018;22:23-9.
Pillay DP, Kumar TK. Food security in India: Evolution, efforts and problems. Strateg Anal 2018;42:595-611.
Johnson C, Praveen D, Pope A, Raj TS, Pillai RN, Land MA, et al
. Mean population salt consumption in India: A systematic review. J Hypertens 2017;35:3-9.
Devi SM, Balachandar V, Lee SI, Kim IH. An outline of meat consumption in the Indian population – A pilot review. Korean J Food Sci Anim Resour 2014;34:507-15.
Ghorpade AG, Shrivastava SR, Kar SS, Sarkar S, Majgi SM, Roy G. Estimation of the cardiovascular risk using World Health Organization/International Society of Hypertension (WHO/ISH) risk prediction charts in a rural population of South India. Int J Health Policy Manag 2015;4:531-6.
Patil CR, Thakre SS, Thakre SB. A cross-sectional study on the risk factors for cardiovascular disease and risk profiling of adults in Central India. J Clin Prev Cardiol 2017;6:104-8. [Full text]
Wong CW, Kwok CS, Narain A Gulati M, Mihalidou AS, Wu P, et al
. Marital status and risk of cardiovascular diseases: A systematic review and meta-analysis. Heart 2018;104:1937-48.
[Table 1], [Table 2], [Table 3], [Table 4]