Journal of Cardiovascular Medicine and Therapeutics

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Reach Us +44-7360-538437

Short Communication - Journal of Cardiovascular Medicine and Therapeutics (2022) Volume 6, Issue 1

Coronary artery disease and its risk factor in India.

Paul Leeson*

Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom

*Corresponding Author:
Paul Leeson
Department of Cardiovascular Medicine
University of Oxford
Oxford, United Kingdom
E-mail: [email protected]

Received: 02-Jan-2022, Manuscript No. AACMT-22-53255; Editor assigned: 04-Jan-2022, PreQC No. AACMT-22-53255(PQ); Reviewed: 19-Jan-2022, QC No. AACMT -22-53255; Revised: 22-Jan-2022, Manuscript No. AACMT-22-53255(R); Published: 29-Jan-2022, DOI:10.35841/aacmt-6.1.102

Citation: Leeson P. Coronary artery disease and its risk factor in India. J Cardiovasc Med Ther. 2022;6(1):102



Coronary artery disease is the leading cause of disability and death worldwide and is one of the top five causes of death in India's population. CAD mortality rates for Indians are expected to rise rapidly, surpassing those in high-income countries. For adults over the age of 20, CHD doubled in rural areas and sixfold in urban areas between 1960 and 2002. Previous studies have shown a high prevalence of CAD among Native Americans in Asia living in the United States. However, there is no robust and up-to-date data on Native American CHD. Ahmed et al. In a systematic review of CHD prevalence in India. He commented that none of the studies met the requirements of quality epidemiological studies. With a population of over 33 million, Kerala is the most advanced state of the epidemiological transition and has the highest prevalence of CHD risk factors in India. The state is reported to be a precursor to what will be brought to other parts of India in the near future. The INTERHEART study reported on the importance of common risk factors associated with CAD [1]. The prevalence of CAD risk factors is highest in Kerala, but there are no recent studies on the prevalence of CAD in that state. The only 1993 communitybased study from rural areas in the southernmost counties of the state reported a CHD prevalence of 7.4%. The Kerala environment contributes to an increased risk factor for CHD and can lead to an increased prevalence of CHD. Therefore, I wanted to find out the current prevalence of CHD in Kerala and its major risk factors. Detailed descriptions of study designs, samples, and methods have already been published. Simply put, this was a community-based cross-sectional study that spanned January-June 2011.

Based on data from Kutty et al., We estimated the sample size based on the expected prevalence of 7.4% in rural CAD in Kerala. Based on 11% of the city Kerala studied by Mohan in Chennai. The total sample size was estimated to be 3000 in rural areas and 2400 in urban areas. The pattern selection process is given in. Subjects aged 20-79 years were selected using a multi-level cluster sampling method. In the first phase, three of the 14 districts of Kerala were selected. The 14 districts were divided into 5 districts in the north, 5 districts in the south, and 4 districts in the centre. From the northern district group, the Calicut district, including the Calicut City Association, was selected. In the southern district group, there were city companies in the Thiruvananthapuram and Column districts. From these, Thiruvananthapuram was randomly selected. The Central District Group had two districts, including businesses Ernakulum and Thrissur. From these, the Thrissur district was randomly selected. In the second stage, one district was randomly selected from each of the three municipal districts in the metropolitan area. Each selected district was divided into 6 geographic regions. One of these geographic areas was randomly selected as the study area. All households in this area can be included in this sample. One person aged 20 to 59 years was selected using the KISH method, and all subjects aged 60 to 79 years were included. In rural areas, two Panchayati were randomly selected from the above three districts. One district was randomly selected from each of these Panchayati.

Each selected individual was invited to visit an easily accessible facility with all past medical records after overnight fasting. Trained investigators collected all the relevant data. Using a structured interview schedule, information on basic socioeconomic and demographic details, and smoking, physical activity, dietary habits, personal history of hypertension, dyslipidaemia, diabetes mellitus and CAD were collected [2]. Instruments include the Rose Angina Questionnaire (RAQ) and documented previous myocardial infarction, unstable angina, coronary artery bypass graft (CABG) surgery, noninvasive assessment of CHD, coronary angiography, coronary angioplasty. It also included questions about the history of plastic surgery and documentation of drug use. For CAD, and for CAD hospitalization. A family history of ischemic heart disease, stroke, and coronary risk factors was also recorded. Height was measured in centimetres using a wall-mounted studio meter (Model 206, Seca, Hamburg, Germany). Subjects were asked to stand upright, with their backs facing the wall, their heels aligned, and their eyes facing forward, without shoes.

Weight was measured on a portable electronic scale (Model HN 283, OMRON Corporation, Shimogyo, Kyoto, Japan) held on a solid horizontal surface. Subjects were asked to wear light clothing and take off their shoes. The weight was given in kilograms with an accuracy of 0.5 kg. Body mass index was calculated as body weight in kg / (height in square meters). The waist area was measured with a non-stretchable tape measure. Subjects were asked to stand upright in a relaxed position with their feet together. Waist circumference was measured to the nearest centimetre between the iliac crest and the lower end of the ribs at the end of exhalation [3].


  1. Yusuf S, Reddy S, O?unpuu S, Anand S. Global burden of cardiovascular diseases: Part II: variations in cardiovascular disease by specific ethnic groups and geographic regions and prevention strategies. Circulation. 2001;104(23):2855-64.
  2. Indexed at, Google Scholar, Cross Ref

  3. Audrain?McGovern J, Benowitz NL. Cigarette smoking, nicotine, and body weight. Clin Pharmacol Ther. 2011;90:164-8.
  4. Indexed at, Google Scholar, Cross Ref

  5. Huang JH, Zager EL. Thoracic outlet syndrome. Neurosurgery. 2004;55(4):897-903.
  6. Indexed at, Google Scholar, Cross Ref

Get the App