Assessment of Cardiovascular Risk Using Who/Ish Risk Prediction Charts among Adult Population In a Rural Area in Thiruvallur District, Tamil Nadu
DOI:
https://doi.org/10.61986/ijpem.v2.i3.2024.34Keywords:
Abdominal obesity Cardio-vascular disease, Modifiable risk factors, 10 years risk assessmentAbstract
Back ground Cardio-vascular diseases (CVDs) are a group of disorders of the heart and a blood vessel, including coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other conditions. In 2019, 17.9 million deaths occurred globally due to CVD. Therefore measures have to be taken to identify people at risk for developing CVD/s at an early stage.
Aim & Objective To assess the prevalence of CVD risk factors and to estimate the cardiovascular risk among adults aged >40 years, using the WHO/ISH risk charts.
Methods and Material: A cross-sectional study was carried out among 252 individuals who attended the Non-communicable Disease (NCD) clinic at the Rural Health Training Center (RHTC) of a Tertiary Care Private Medical College from January 2020 to March 2020. Individuals aged 40-79 years old attending the NCD clinic were included. Color-coded; WHO/ISH charts for the South East Asia sub-region-D were used to predict the 10-year absolute risk of a major cardiovascular event. Descriptive statistics were computed for various risk factors of CVD and also background variables. A chi-square test was done to assess the association between various risk factors and 10 years risk of CVD. Multiple logistic regression analysis determined the independent risk factors influencing CVD risk.
Results: In our study, 252 participants attending NCD clinic were enrolled. The mean age of the participants was 56.4± 9.43 years. 46 (18.3%) participants belonged to the high-risk CVD group (Risk ≥ 20%). Male gender, smoking status, abdominal obesity, stress, and BMI >30 Kg/m2 were significantly associated with high CVD risk [P-value <0.05]. After adjusting for confounding, abdominal obesity and Body Mass Index (BMI) >30 Kg/m2 were significantly associated with high CVD risk.
Conclusions: Nearly 1/5th of the participants attending the NCD screening clinic belong to the high-risk CVD group. The majority of the risk factors found in high-risk group were modifiable and hence burden of these risk factors can be reduced by behavioural change communication which in turn reduces the incidence of CVD in the future.
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Copyright (c) 2024 Yatin Mendu, Charumathi Boominathan, Koushik . M, Shiny Chrism Queen Nesan, Subhas. C, Vinodhini Balamurugan, Timsi Jain (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
World Health Organization, India. Cardiovascular diseases. Available from:http://www.searo.who.int/india/topic s/cardiovascular_diseases/en/[updated 2019 September 16; cited 2020 Mar 4]
Mackay J, Mensah GA, Greenlund K. The atlas of heart disease and stroke. World Health Organization; 2004.
Global Burden of Disease Collaborators Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study. Lancet, 390 (2017), pp. 2437-2460
Salvi S, Kumar GA, Dhaliwal RS, Paulson K, Agrawal A, Koul PA, Mahesh PA, Nair S, Singh V, Aggarwal AN, Christopher DJ. The burden of chronic respiratory diseases and their heterogeneity across the states of India: the Global Burden of Disease Study 1990–2016. The Lancet Global Health. 2018 Dec 1;6(12):e1363-74. DOI: https://doi.org/10.1016/S2214-109X(18)30409-1
Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, Barengo NC, Beaton AZ, Benjamin EJ, Benziger CP, Bonny A. Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study. Journal of the American College of Cardiology. 2020 Dec 22;76(25):2982- 3021.
Oboudi, S., Rani R Hiremath, Sh. Assessment of Risk Factors for Cardiovascular Diseases among Adults and Geriatrics Bangalore, India. Arch Pharm Pract.2020;11(S1):110-6.
Norman G, George CE, Krishnamurthy A, Mukherjee D. Burden of cardiovascular risk factors of a rural population in South India using the WHO multivariable risk prediction algorithm. Int J Med Sci Public Health. 2014;3(6):764-8. DOI: https://doi.org/10.5455/ijmsph.2014.180320141
World Health Organization. WHO/ISH risk prediction charts for 14 WHO epidemiological sub-regions. World Health Organization, Geneva. 2007.
World Health Organization. Prevention of cardiovascular disease: guidelines for assessment and management of total cardiovascular risk. World Health Organization; 2007.
World Health Organization. WHO STEPS surveillance manual: the WHO STEP wise approach to chronic disease risk factor surveillance. World Health Organization; 2005.
Valaulikar R, Balu PS, Bhat RA. Assessment of 10-Year Risk of Developing a Major Cardiovascular Event in Type- 2 Diabetes Patients Attending a Hospital in Davangere, Karnataka. Natl J Community Med 2017; 8(4):193-197
Van Holle V, De Bourdeaudhuij I, Deforche B, Van Cauwenberg J, Van Dyck D. Assessment of physical activity in older Belgian adults: validity and reliability of an adapted interview version of the long International Physical Activity Questionnaire (IPAQ-L). BMC public health. 2015 Dec 1;15(1):433. DOI: https://doi.org/10.1186/s12889-015-1785-3
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. International journal of health policy and management. 2015 Aug;4(8):531. DOI: https://doi.org/10.15171/ijhpm.2015.88
Rose GA, Blackburn H, Gillum RF, Prineas RJ. Cardiovascular survey methods. Geneva, Switzerland; WHO; 1982.
Riley L, Guthold R, Cowan M, Savin S, Bhatti L, Armstrong T, Bonita R. The World Health Organization Stepwise approach to non-communicable disease risk-factor surveillance: methods, challenges, and opportunities. American journal of public health. 2016 Jan;106(1):74-8. DOI: https://doi.org/10.2105/AJPH.2015.302962
Vikramaditya B, Satija M, Chaudhary A, Sharma S, Girdhar S, Bansal P. A community based cross sectional study to estimatetotal cardiovascular risk in rural Punjab. Int J Community Med Public Health 2017;4:1295-302 DOI: https://doi.org/10.18203/2394-6040.ijcmph20171365
Balaji BV, Rajanandh MG, Udayakumar N, Seenivasan P. Prediction of cardiovascular risk in a rural Indian population using WHO/ISH risk prediction charts: a community-based cross-sectional study. Drugs & Therapy Perspectives. 2018 Aug;34(8):386-91. DOI: https://doi.org/10.1007/s40267-018-0515-1
Khanal MK, Ahmed MM, Moniruzzaman M, Banik PC, Dhungana RR, Bhandari P, Devkota S, Shayami A. Total cardiovascular risk for next 10 years among rural population of Nepal using WHO/ISH risk prediction chart. BMC research notes. 2017 Dec;10(1):1-7. DOI: https://doi.org/10.1186/s13104-017-2436-9
Priya Bansal , Anurag Chaudhary , Praneet Wander , Mahesh Satija , Sarit Sharma Sangeeta Girdhar , Pushapindra Kaushal , Vikram Kumar Gupta. Cardiovascular Risk Assessment Using WHO/ISH Risk Prediction Charts In a Rural Area of North India. Journal of Research in Medical and Dental Science.2016;4(2) DOI: https://doi.org/10.5455/jrmds.20164210
Krishnan A, Gupta V, Ritvik BN, Thakur JS. How to effectively monitor and evaluate NCD programmes in India. Indian journal of community medicine: official publication of Indian Association of Preventive & Social Medicine. 2011 Dec;36(Suppl1):S57. DOI: https://doi.org/10.4103/0970-0218.94710
Mohanty S, Venkatarao E, Yasobant S. Non-communicable disease care and physical activity promotion in India: analysis of recent policies, guidelines and workplans. Fam Med Community Health. 2020;8(2):e000206. DOI: https://doi.org/10.1136/fmch-2019-000206
Ordunez P, Campbell NR. Beyond the opportunities of SDG 3: the risk for the NCDs agenda. The Lancet Diabetes & Endocrinology. 2016 Jan 1;4(1):15-7. DOI: https://doi.org/10.1016/S2213-8587(15)00488-X
