|Year : 2017 | Volume
| Issue : 3 | Page : 104-108
A cross-sectional study on the risk factors for cardiovascular disease and risk profiling of adults in central India
Chaitanya Rangangouda Patil1, Sushama Subhash Thakre1, Subhash B Thakre2
1 Department of Community Medicine, Indira Gandhi Government Medical College, Nagpur, Maharashtra, India
2 Department of Community Medicine, Government Medical College, Yavatmal, Maharashtra, India
|Date of Web Publication||4-Jul-2017|
Chaitanya Rangangouda Patil
Department of Community Medicine, Indira Gandhi Government Medical College, Nagpur - 440 018, Maharashtra
Source of Support: None, Conflict of Interest: None
Context: Cardiovascular disease (CVD) tops the list of the causes of noncommunicable disease mortality, followed by cancers, respiratory diseases, and diabetes. More than 75% of CVD deaths occur in low- and middle-income countries. Thus, estimation of the future CVD risk in this population becomes an important step. Aims: The aim is to study the prevalence of risk factors for CVD and to study the 10-year risk for fatal or nonfatal cardiovascular events. Subjects and Methods: A cross-sectional study was conducted at an urban health training center of a tertiary care hospital in Central India. Adults >30 years of age attending the outpatient department were recruited. Patients on long-term steroids, critically ill patients, and pregnant females were excluded from the study. Predesigned and pretested questionnaire was used to collect the data. For individuals above 40 years of age, the 10-year risk for cardiovascular events was estimated using the World Health Organization/International Society of Hypertension risk prediction charts. Results: A total of 243 participants (mean age 51.4 ± 12.2 years; female:male ratio 1.38:1) were included in the study. The prevalence of tobacco chewing (33.3%) and smoking (10.8%) was significantly higher among males compared with females (P < 0.001). The prevalence of hypertension, family history of CVD, overweight, and obesity was higher among females but did not attain statistical significance. The estimated 10-year risk of a cardiovascular event was <10%, 10%–<20%, 20%–<30%, 30%–<40%, and >40% in 72%, 17%, 7%, 2%, and 2% study participants, respectively. Conclusions: We found significantly higher prevalence of males consuming tobacco and smoking as compared to females. About 28% of the eligible study participants had a predicted 10-year cardiovascular risk of 10% or more in our study. This high proportion of elevated cardiovascular risk is a cause of concern and necessitates aggressive preventive efforts.
Keywords: Cardiovascular disease, Central India, primary prevention, World Health Organization/International Society of Hypertension risk prediction charts
|How to cite this article:|
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
|How to cite this URL:|
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 [serial online] 2017 [cited 2021 Apr 17];6:104-8. Available from: https://www.jcpconline.org/text.asp?2017/6/3/104/209384
| Introduction|| |
“Demographic transition” has affected the health-care needs of the world's population. There has been a paradigm shift in the focus from communicable diseases to a new epidemic of noncommunicable diseases (NCDs) and their sequelae. Cardiovascular disease (CVD), cancer, and diabetes mellitus (DM) have become the major causes of morbidity and mortality worldwide, but particularly in the Southeast Asia region where they contribute to 52% of deaths and 38% of disease burden. CVD tops this list, followed by cancers, respiratory diseases, and diabetes. More than 75% of CVD deaths occur in low- and middle-income countries. The Global Health Observatory report for the year 2012 for India reported that the age-standardized mortality rate for CVD was 306.3/1 lakh population. This epidemic of NCDs has to be tackled with a basic mantra of health promotion and education.
A number of modifiable and nonmodifiable risk factors are responsible for causation of CVD. Of these risk factors, the modifiable ones such as tobacco use, unhealthy diet, physical inactivity, obesity, and alcohol use are especially important because they can be modified through lifestyle management leading to reduction in the risk for CVD. Accordingly, the knowledge of cardiovascular risk factor prevalence and distribution in a population is required to define appropriate preventive strategies. Unfortunately, while several studies on CVD risk profiling have been done throughout India,,,,,,,,,,, there exists a paucity of data in urban areas of Maharashtra. Therefore, this study was conducted to study the prevalence of the important risk factors for CVD and to estimate the 10-year risk for fatal or nonfatal cardiovascular events in the Central India population.
| Subjects and Methods|| |
This hospital-based cross-sectional study conducted at an urban health training center of a tertiary care hospital in Maharashtra. The study duration was from January 2015 to March 2015. The participants who were >30 years of age permanently residing in the field practice area of the above urban health center and attended the routine outpatient department were included in the study. The participants who were on long-term steroids, had a suspected cardiac illness, or were critically ill were excluded from the study. Pregnant females were also excluded from the study. From this population, the study cohort was selected using simple random sampling. As per the reports of the World Health Organization (WHO), the prevalence of hypertension in India is approximately 21.4%. Using this prevalence, with 95% confidence interval and an absolute precision of 5.5%, the minimum sample to be covered was calculated to be 214. We included 243 patients in our study. Written informed consent was obtained from the study participants, and the study was approved by the Institutional Ethical Committee.
The data on socioeconomic and demographic variables were collected using a predesigned and pretested questionnaire. Anthropometric variables such as weight (kg) nearest to 100 g and height (cm) nearest to 0.2 cm were measured using standard equipment and procedures. Three measurements of blood pressure using a mercury sphygmomanometer were taken in reclining position for all men and women. Average reading of the blood pressure was considered for diagnosing hypertension in these individuals. Risk factors such as smoking, tobacco chewing, family history of CVD, history of DM, and hypertension were assessed through interviewed. Hypertension was defined according to the Joint National Committee recommendations as mean systolic blood pressure ≥140 mmHg and/or mean diastolic blood pressure ≥90 mmHg or the use of antihypertensive medications. Body mass index <18.5 kg/m 2 was classified as undernutrition, 18.5–24.99 kg/m 2 as normal, 25.00–29.99 kg/m 2 as overweight, and >30 kg/m 2 as obese.
For individuals >40 years of age, the 10-year risk for fatal or nonfatal major cardiovascular events was estimated using the WHO/International Society of Hypertension (ISH) risk prediction charts. These charts estimate CVD risk on the basis of age, gender, systolic blood pressure, smoking status, and presence/absence of DM.
Following data collection, the study participants were provided counseling about healthy lifestyle, such as cessation of smoking and tobacco use, increased physical activity, etc. The individuals who were diagnosed as hypertensive for the first time were advised to reduce salt intake and were also referred to a physician for the further confirmation and management.
EPI Info™ (Version 7.1, Centers for Disease Control and Prevention, Atlanta, Georgia, USA) was used to collect the information, compilation, and analysis. Prevalence rates were calculated for the risk factors and presented in percentages. Continuous data were handled using mean ± standard deviation. Categorical variables were compared using Fisher's exact test or Chi-square test. All analyses were two tailed, and P< 0.05 was considered to be statistically significant.
| Results|| |
[Table 1] shows the sociodemographic characteristics of the study participants.
|Table 1: Sociodemographic characteristics of the study participants (n=243)|
Click here to view
Mean age of the study participants was 51.4 ± 12.2 years with female:male ratio of 1.38:1. More than half of them were educated till at least secondary education level (62.5%) and belonged to upper-middle or upper socioeconomic status (54.8%).
[Table 2] shows the prevalence of risk factors for CVD according to gender. The prevalence of hypertension among males and females was 35.3% and 38.2%, respectively, but the difference was not statistically significant (P = 0.63). Similarly, 5.9% of males and 2.8% of females reported to have a family history of CVD (P = 0.23). The prevalence of tobacco chewing and smoking was significantly higher in males as compared to females (P < 0.01). A higher number of females were overweight and obese when compared to males, but this difference did not attain statistical significance (P = 0.07).
|Table 2: Prevalence of cardiovascular disease risk factors based on gender|
Click here to view
Of the 243 participants included in the study, 204 were above 40 years of age and were eligible for 10-year CVD risk estimation. It was found that 28% of them had estimated 10-year CVD risk ≥10% [Figure 1].
|Figure 1: Distribution of eligible study participants according to the estimated 10-year cardiovascular risk based on the World Health Organization/International Society of Hypertension charts (n = 204)|
Click here to view
| Discussion|| |
Prevention of CVD is an essential step to control the epidemic of NCDs in India. We conducted a hospital-based cross-sectional study of 243 participants to study the risk factors for CVD and to estimate the 10-year CVD risk among the eligible participants using the WHO/ISH risk prediction charts. We found gender variation in the prevalence of various CVD risk factors with tobacco chewing and smoking being more common in men, whereas overweight/obesity being more common in women. In addition, we found that more than a quarter of the participants had estimated 10-year CVD risk more than 10%.
Recent reports of the National Family Health Survey-4 (NFHS) of Maharashtra state reported the prevalence of overweight/obesity being 32.4% in females and 31.2% in males. These figures are lower than those in our study, likely because NFHS data are based on a community-based survey involving much larger population. NFHS also reported a lower prevalence of tobacco use in any form (33.9% in males and 4.2% in females) and hypertension (7% in males and 9% in females) when compared to our study.
Several other individual studies have reported the prevalence of various CVD risk factors in different population groups in our country. A review conducted by Shah and Mathur  reported the prevalence of hypertension among urban areas in India to be 30.2% and 25.7% among males and females, respectively. The prevalence of hypertension in our study was in concordance with this study. Similarly, Sekhri et al. collected data on 12,608 government employees living in different parts of India. They found that the prevalence of family history of premature coronary artery disease was 4.4% and 6% and that of overweight/obesity was 46.1% and 55.3% in males and females, respectively. The differences between males and females were statistically significant. Our findings are in accordance with these findings though we could not find statistically significant differences between males and females.
A multicentric study conducted by Otgontuya et al. estimated the 10-year CVD risk to be more than 20% in 6%, 2.3%, and 1.3% of the study population of Cambodia, Malaysia, and Mongolia, respectively. A similar study conducted in Nepal by Dhungana et al. reported an estimated risk of more than 20% in 14.6% of the study population. In a study conducted by Ahmed et al., in the urban population of Bangladesh, the 10-year CVD risk as per the WHO/ISH charts was estimated to be more than 20% in 3.4% of the population. The predicted risk of our study was higher when compared to studies by Otgontuya et al. and Ahmed et al. and was lower than the predicted risk by Dhungana et al.
A study conducted by Shrivastava et al. in a rural community of Puducherry found that 4.9% were having high risk (>20% 10-year CVD risk), 9.1% were having moderate risk (10%–20% risk), and 86% were having low risk (<10% risk). Similarly, a study from rural area of Kurnool district of Andhra Pradesh by Bandela et al. estimated that 0.69% of population had >30% risk, 5.48% had 10%–30% risk, and 93.8% had <10% estimated risk. Yet another cross-sectional study conducted by Savitharani et al. estimated that the 10-year risk of having a cardiovascular event was >10% in case of 1.7% of the study participants (supporting staff of a tertiary hospital). Finally, a study conducted by Aswin et al., in Group C employees at JIPMER, Puducherry, found 0.5%, 1.8%, 1.4%, and 96.3% of the participants having very high (>30%), high (20%–30%), moderate (10%–20%), and low risk (<10%), respectively. Compared to these studies, in our study, we found a higher proportion of individuals at >10% 10-year CVD risk. However, Nordet et al. concluded in their study that 1.6% were having very high risk, 3.0% were having high risk, 12.7% were having moderate risk, and 82.7% were having low risk which was in concordance with our study results.
The varied proportions of the estimated risk are probably due to the fact that these studies are conducted in different sets of populations. Our study was included those attending the outpatient department of a tertiary hospital, so the proportions of all risk factors are likely to be higher. Similar studies if conducted in a community might yield more comparable and precise results.
Our study has several limitations that merit attention. This was a hospital-based study, conducted in a select type of population, which precludes generalization of our study findings. In addition, due to logistic constraints, we could not include some of the other important CVD risk factors such as dyslipidemia, abnormalities of glucose metabolism, and psychosocial stress. Finally, the WHO/ISH risk prediction charts may not be the most accurate method for predicting CVD risk among the Indian population., However, the WHO publication on the strengths and limitations of the charts recommends that it is a safe and useful tool for guiding management and treatment decisions for individuals. Moreover, from the epidemiological point of view, these charts can be used to compare the estimated risks across different geographical locations.
| Conclusions and Recommendations|| |
In conclusion, our study provides a valuable insight into the cardiovascular health of an urban population from Central India. We found a high prevalence of some of the CVD risk factors among apparently healthy individuals. More than one-fourth of the eligible study participants had a predicted 10-year cardiovascular risk of 10% or more. This high proportion of elevated cardiovascular risk is a cause of concern and necessitates aggressive preventive efforts. However, multicentric, community-based studies need to be conducted to predict the actual burden of CVD in India.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organisation: Global Health Observatory Data Repository of Cardiovascular Diseases, Deaths Per 100 000 – Data by Country. Available from: http://www.apps.who.int/gho/data/node
.country. [Last updated on 2016 Aug 05; Last cited on 2016 Sep 28].
Dhungana RR, Khanal MK, Pandey AR, Thapa P, Devkota S, Mumu SJ, et al.
Assessment of short term cardiovascular risk among 40 years and above population in a selected community of Kathmandu, Nepal. J Nepal Health Res Counc 2015;13:66-72.
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.
Fatema K, Zwar NA, Milton AH, Rahman B, Ali L. Application of two versions of the WHO/international society of hypertension absolute cardiovascular risk assessment tools in a rural Bangladeshi population. BMJ Open 2015;5:e008140.
Raghu A, Praveen D, Peiris D, Tarassenko L, Clifford G. Implications of cardiovascular disease risk assessment using the WHO/ISH risk prediction charts in rural India. PLoS One 2015;10:e0133618.
Aswin K, Ghorpade AG, Kar SS, Kumar G. Cardiovascular disease risk factor profiling of group C employees in JIPMER, Puducherry. J Family Med Prim Care 2014;3:255-9.
] [Full text]
Bandela PV, Dongre N, Ambekar JG, Durga Prasad K. Assessment of cardiovascluar risk of rural population in Kurnool district using WHO/ISH multivariable risk prediction algorithm. J Pharm Sci Res 2016;8:338-42.
Ahmed MS, Moniruzzaman M, Chowdhury S, Banik PC. Cardiovascular risk assessment among urban population of Bangladesh using WHO/ISH risk prediction chart. Int J Epidemiol 2015;44:i202.
Shrivastava SR, Ghorpade AG, Shrivastava PS. A community-based cross-sectional study of cardiovascular risk in a rural community of Puducherry. Heart Views 2015;16:131-6.
] [Full text]
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 2013;13:539.
Nordet P, Mendis S, Dueñas A, de la Noval R, Armas N, de la Noval IL, et al.
Total cardiovascular risk assessment and management using two prediction tools, with and without blood cholesterol. MEDICC Rev 2013;15:36-40.
Savitharani BB, Madhu B, Renuka M, Ashok NC. Utilization of WHO-ISH 10-year CVD risk prediction chart as a screening tool among supporting staff of a tertiary care hospital, Mysuru, India. Heart India 2016;4:13-6. [Full text]
Frese EM, Fick A, Sadowsky HS. Blood pressure measurement guidelines for physical therapists. Cardiopulm Phys Ther J 2011;22:5-12.
Armstrong C. Practice guidelines JNC 8 guidelines for the management of hypertension AAFP's five key metrics for financial success. Am Fam Physician 2014;90:503-4.
Shah B, Mathur P. Surveillance of cardiovascular disease risk factors in India: The need and scope. Indian J Med Res 2010;132:634-42.
] [Full text]
Sekhri T, Kanwar RS, Wilfred R, Chugh P, Chhillar M, Aggarwal R, et al.
Prevalence of risk factors for coronary artery disease in an urban Indian population. BMJ Open 2014;4:e005346.
Bansal M, Kasliwal RR, Trehan N. Comparative accuracy of different risk scores in assessing cardiovascular risk in Indians: A study in patients with first myocardial infarction. Indian Heart J 2014;66:580-6.
Bansal M, Kasliwal RR, Trehan N. Relationship between different cardiovascular risk scores and measures of subclinical atherosclerosis in an Indian population. Indian Heart J 2015;67:332-40.
[Table 1], [Table 2]