A Population Based Survey on the Association Between Tobacco Smoking and Cardiovascular Risk Using WHO Risk Prediction Algorithm Among a Rural Population in Mangalore, Karnataka

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DOI:

https://doi.org/10.47203/IJCH.2020.v32i04.008

Keywords:

CVD, Chewable Tobacco, GATS, Risk level, Tobacco Forms

Abstract

Background: Higher proportion of people die in India due to Cardiovascular diseases. Smoking causes about 10% of all CVD and 6 million people die from tobacco smoking every year through CVD, cancer and other causes. Aims & Objectives: To determine the risk of developing cardiovascular events (fatal and non-fatal MI or Stroke) among the individuals above 40 years of age in next 10 years and to assess its magnitude of association with the smoking patterns among the study subjects. Methodology: A cross sectional study was conducted at Rural Mangalore among 230 residents above 40 years who were selected by simple random sampling. Pretested & pre validated proforma for sociodemographic details, WHO/ISH cardiovascular risk prediction algorithm and GATS (Global Adult Tobacco Survey) Questionnaire was used. Statistics used: Chi square test and Multiple logistic regression was used. Data was analysed using SPSS version 22 software. Results: Out of 230 participants, 64% were males and 36% were females. WHO colour coding shows that 64.8% had low risk, 25.7% had moderate risk and 9.5% had high risk of getting CVD. 58.3% consumed chewable tobacco. Current smokeless tobacco users had moderate risk of CVD and Current smokers, current and past smokeless tobacco users had high risk of getting CVD independently. Conclusion: An increased risk of nonfatal myocardial infarctions among tobacco chewers was relatively lesser than for smokers and the highest increase in risk of acute myocardial infarction was in smokers who also chewed tobacco.

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Published

2020-12-31

How to Cite

1.
Nesan SCQ, Kundapur R, Maiya GR. A Population Based Survey on the Association Between Tobacco Smoking and Cardiovascular Risk Using WHO Risk Prediction Algorithm Among a Rural Population in Mangalore, Karnataka. Indian J Community Health [Internet]. 2020 Dec. 31 [cited 2024 May 4];32(4):653-8. Available from: http://www.iapsmupuk.org/journal/index.php/IJCH/article/view/1809

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