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

Document Type: Original Article

Authors

1 Sri Manakula Vinayagar Medical College and Hospital, Pondicherry, India

2 Shri Sathya Sai Medical College and Research Institute, Kancheepuram, India

3 Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India

4 Mysore Medical College and Research Institute, Mysore, Karnataka, India

Abstract

Background
World Health Organization/International Society of Hypertension (WHO/ISH) charts have been employed to predict the risk of cardiovascular outcome in heterogeneous settings. The aim of this research is to assess the prevalence of Cardiovascular Disease (CVD) risk factors and to estimate the cardiovascular risk among adults aged >40 years, utilizing the risk charts alone, and by the addition of other parameters.
 
Methods
A cross-sectional study was performed in two of the villages availing health services of a medical college. Overall 570 subjects completed the assessment. The desired information was obtained using a pretested questionnaire and participants were also subjected to anthropometric measurements and laboratory investigations. The WHO/ISH risk prediction charts for the South-East Asian region was used to assess the cardiovascular risk among the study participants.
 
Results
The study covered 570 adults aged above 40 years. The mean age of the subjects was 54.2 (±11.1) years and 53.3% subjects were women. Seventeen percent of the participants had moderate to high risk for the occurrence of cardiovascular events by using WHO/ISH risk prediction charts. In addition, CVD risk factors like smoking, alcohol, low High-Density Lipoprotein (HDL) cholesterol were found in 32%, 53%, 56.3%, and 61.5% study participants, respectively.
 
Conclusion
Categorizing people as low (<10%)/moderate (10%-20%)/high (>20%) risk is one of the crucial steps to mitigate the magnitude of cardiovascular fatal/non-fatal outcome. This cross-sectional study indicates that there is a high burden of CVD risk in the rural Pondicherry as assessed by WHO/ISH risk prediction charts. Use of WHO/ISH charts is easy and inexpensive screening tool in predicting the cardiovascular event.

Keywords

Main Subjects


  1. Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJ. Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet 2006; 367: 1747-57. doi: 10.1016/s0140-6736(06)68770-9
  2. Abegunde DO, Mathers CD, Adam T, Ortegon M, Strong K. The burden and costs of chronic diseases in low-income and middle-income countries. Lancet 2007; 370: 1929-38. doi: 10.1016/s0140-6736(07)61696-1
  3. Mathers CD, Boerma T, Ma Fat D. Global and regional causes of death. Br Med Bull 2009; 92: 7-32. doi: 10.1093/bmb/ldp028
  4. World Health Organization (WHO). Prevention of cardiovascular disease: Guidelines for assessment and management of cardiovascular risk. Geneva: WHO; 2007.
  5. World Health Organization (WHO). Cardiovascular diseases - Fact sheet N°317 [internet]. 2013. [cited 2014 Nov 19]. Available from: http://www.who.int/mediacentre/factsheets/fs317/en/
  6. Mackay J, Mensah GA. The atlas of heart disease and stroke [internet]. World Health Organization & Center for Disease Control and Prevention; 2012. [cited 2014 Nov 19]. Available from: http://www.who.int/cardiovascular_diseases/resources/atlas/en/
  7. Chandola T, Plewis I, Morris JM, Mishra G, Blane D. Is adult education associated with reduced coronary heart disease risk? Int J Epidemiol 2011; 40: 1499-509. doi: 10.1093/ije/dyr087
  8. Saidi O, Ben Mansour N, O’Flaherty M, Capewell S, Critchley JA, Ben Romdhane H. Analyzing recent coronary heart disease mortality trends in Tunisia between 1997 and 2009. PLoS One 2013; 8: e63202. doi: 10.1371/journal.pone.0063202
  9. Kar SS, Thakur JS, Virdi NK, Jain S, Kumar R. Risk factors for cardiovascular diseases: is the social gradient reversing in northern India? Natl Med J India 2010; 23: 206-9.
  10. Samuel P, Antonisamy B, Raghupathy P, Richard J, Fall CH. Socio-economic status and cardiovascular risk factors in rural and urban areas of Vellore, Tamilnadu, South India. Int J Epidemiol 2012; 41: 1315-27.
  11. Kamble PH, Rode MV, Phatak MS, Tayade P. Is smokeless tobacco use a risk factor for coronary artery disease? A comparative study of smokers and smokeless tobacco users. Indian Journal of Basic & Applied Medical Research 2011; 1: 22-30.
  12. Cooney MT, Dudina AL, Graham IM. Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians. J Am Coll Cardiol 2009; 54: 1209-27.
  13. Ndindjock R, Gedeon J, Mendis S, Paccaud F, Bovet P. Potential impact of single-risk-factor versus total risk management for the prevention of cardiovascular events in Seychelles. Bull World Health Organ 2011; 89: 286-95. doi: 10.2471/blt.10.082370
  14. Kuklina EV. Assessing and managing risk for cardiovascular disease: A worldwide perspective. N A J Med Sci 2010; 3: 94-103. doi: 10.7156/v3i1p094
  15. Mendis S, Lindholm LH, Mancia G, Whitworth J, Alderman M, Lim S, et al. World Health Organization (WHO) and International Society of Hypertension (ISH) risk prediction charts: assessment of cardiovascular risk for prevention and control of cardiovascular disease in low and middle-income countries. J Hypertens 2007; 25: 1578-82. doi: 10.1097/hjh.0b013e3282861fd3
  16. D’Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 2008; 117: 743-53. doi: 10.1161/circulationaha.107.699579
  17. Zhang XF, Attia J, D’Este C, Yu XH, Wu XG. A risk score predicted coronary heart disease and stroke in a Chinese cohort. J Clin Epidemiol 2005; 58: 951-8. doi: 10.1016/j.jclinepi.2005.01.013
  18. Asia Pacific Cohort Studies Collaboration, Barzi F, Patel A, Gu D, Sritara P, Lam TH, et al. Cardiovascular risk prediction tools for populations in Asia. J Epidemiol Community Health 2007; 61: 115-21. doi: 10.1136/jech.2005.044842
  19. WHO/ISH Risk prediction charts for 14 WHO epidemiological sub-regions [internet]. 2007. [cited 2014 Nov 19]. Available from: http://ish-world.com/downloads/activities/colour_charts_24_Aug_07.pdf
  20. Al-Lawati JA, Barakat MN, Al-Lawati NA, Al-Maskari MY, Elsayed MK, Mikhailidis DP, et al. Cardiovascular risk assessment in diabetes mellitus: comparison of the general Framingham risk profile versus the World Health Organization / International Society of Hypertension risk prediction charts in Arabs - clinical implications. Angiology 2013; 64: 336-42. doi: 10.1177/0003319712458349
  21. Sawhney JP, Sawhney A. The total risk approach to prevention of coronary heart disease. J Preventive Cardiology 2011; 1: 16-21.
  22. Ministry of Home Affairs, India. Census of India 2011 [internet]. New Delhi: Office of the Registrar General & Census Commissioner; 2011. [cited 2014 Nov 22]. Available from: http://censusindia.gov.in/2011-prov-results/prov_results_paper1_india.html
  23. Majgi SM, Soudarssanane BM, Roy G, Das AK. Risk factors of diabetes mellitus in rural Puducherry. Online J Health Allied Sci 2012; 11: 4.
  24. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 2001; 285: 2486-97. doi: 10.1001/jama.285.19.2486
  25. The United Nations Educational, Scientific and Cultural Organization (UNESCO). ISCED: International standard classification of education [internet]. 1997. [cited 2014 Nov 22]. Available from: http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx
  26. Ministry of Home Affairs, India. Census of India 2001. New Delhi: Office of the Registrar General & Census Commissioner [internet]. 2001. [cited 2014 Nov 19]. Available from: http://www.censusindia.gov.in/2011-common/CensusData.html
  27. Agarwal AK. Social classification: the need to update in the present scenario. Indian J Community Med 2008; 33: 50-1. doi: 10.4103/0970-0218.39245
  28. International Physical Activity Questionnaire (IPAQ). IPAQ scoring protocol [internet]. 2005. [cited 2014 Nov 19]. Available from: https://sites.google.com/site/theipaq/scoring-protocol
  29. World Health Organization (WHO). STEPwise approach to surveillance (STEPS) field manual appendices [internet]. [cited 2014 Oct 22].Available from: http://www.who.int/chp/steps/en/
  30. Rhem J, Room R, Monteiro M, Gmel G, Grahm K, Rhen N, et al. Alochol use. In: Ezzati M, editor. Comapritive quantification of health risk: Global and regional burden of disease attributable to selected major risk factors. Geneva: WHO; 2004. p. 959-1108.
  31. Indian Council of Medical Research. Guidelines for management of type 2 diabetes. New Delhi: Indian Council of Medical Research; 2005.
  32. World Health Organization (WHO). Cardiovascular Survey Methods. Geneva: WHO;  1982.
  33. Ministry of Health & Family Welfare, Government of India. Non-communicable disease risk factors survey - Integrated disease surveillance project, 2007-2008. New Delhi: Royal Offset Press; 2009.
  34. Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009; 57: 163-70.
  35. Cooney MT, Dudina A, D'Agostino R, Graham IM. Cardiovascular risk-estimation systems in primary prevention: do they differ? Do they make a difference? Can we see the future? Circulation 2010; 122: 300-10. doi: 10.1161/circulationaha.109.852756
  36. Wassenberg MW, Willemsen JM, Gaillard CA, Braam B. Hypertension management in primary care: standard care and attitude towards a disease management model. Neth J Med 2004; 62: 375-82.
  37. Erhardt L, Moller R, Puig JG. Comprehensive cardiovascular risk management - what does it mean in practice? Vasc Health Risk Manag 2007; 3: 587-603.
  38. Ferket BS, Colkesen EB, Visser JJ, Spronk S, Kraaijenhagen RA, Steyerberg EW, et al. Systematic review of guidelines on cardiovascular risk assessment: which recommendations should clinicians follow for a cardiovascular health check? Arch Intern Med 2010; 170: 27-40.
  39. Selvarajah S, Kaur G, Haniff J, Cheong KC, Hiong TG, van der Graaf Y, et al. Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. Int J Cardiol 2014; 176: 211-8. doi: 10.1016/j.ijcard.2014.07.066
  40. World Health Organization (WHO). Prevention of cardiovascular diseases - Pocket guidelines for assessment and management of cardiovascular risk. Geneva: WHO; 2007.
  41. Mendis S, Lindholm LH, Anderson SG, Alwan A, Koju R, Onwubere BJ, et al. Total cardiovascular risk approach to improve efficiency of cardiovascular prevention in resource constrain settings. J Clin Epidemiol 2011; 64: 1451-62. doi: 10.1016/j.jclinepi.2011.02.001
  42. Koju R, Gurung R, Pant P, Humagain S, Yogol CM, Koju A, et al. Prediction of cardiovascular disease in suburban population of 3 municipalities in Nepal. Nepalese Heart Journal 2011; 8: 3-7. doi: 10.3126/njh.v8i1.8328
  43. 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. doi: 10.1186/1471-2458-13-539
  44. World Health Organization (WHO). Target 8: Provide drug therapy to prevent heart diseases [internet]. 2014. [cited 2014 Nov 19]. Available from: http://www.who.int/nmh/ncd-tools/target8/en/
  45. Shivaramakrishna HR, Wantamutte AS, Sangolli HN, Mallapur MD. Risk factors of coronary heart disease among bank employees of Belgaum city - Cross-sectional study. Al Ameen J Med Sci 2010; 3: 152-9.