|Year : 2016 | Volume
| Issue : 1 | Page : 13-16
Utilization of who-ish 10-year cvd risk prediction chart as a screening tool among supporting staff of a tertiary care hospital, Mysuru, India
BB Savitharani, B Madhu, M Renuka, Sridevi, NC Ashok
Department of Community Medicine, JSS Medical College, JSS University, Mysuru, Karnataka, India
|Date of Web Publication||4-Mar-2016|
Department of Community Medicine, JSS Medical College, JSS University, Mysuru - 570 015, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Noncommunicable diseases are increasing and constitute a serious concern, accounting for 52% of the deaths and 38% of the disease burden in the World Health Organization (WHO) South-East Asia Region. Eighty percent of total deaths due to noncommunicable diseases occur in the low-income countries. Lifestyle changes are resulting in an increased risk of cardiovascular diseases (CVD). Surveillance of CVD risk factors is a key to reduce the burden of CVD. WHO–International Society of Hypertension (ISH) 10-year risk prediction charts have been developed for the screening of CVD risk factors in different regions. The National Programme for Prevention and Control of Diabetes, Cardiovascular Diseases and Stroke (NPDCS) has also recommended the utilization of these charts for routine screening. The present study has used the WHO-ISH CVD risk prediction chart to assess the feasibility of utilization of this chart as a predicting tool of a CVD event. Materials and Methods: A cross-sectional survey was conducted among supporting staff of JSS Hospital, Mysuru, Karnataka, India to assess the CVD risk factors and risk factor profiling, and the prediction of 10-year risk for CVD was done using a WHO-ISH risk prediction chart. Results: A total of 900 supporting staff were screened for CVD risks. Out of them, 30 (3.3%) had hypertension, 20 (2.2%) had diabetes mellitus, 18 (1.99%) consumed tobacco. The proportion of newly detected diabetes cases was 8 (0.9%) and of prediabetics was 32 (3.7%). The proportion of newly detected prehypertensives were 292 (39.08%), and 27 (3.61%) were hypertensives. Out of 175 individuals aged above 40 years, the WHO-ISH risk prediction chart predicted that 1.7% of them had >10% risk of CVD event within 10 years. Conclusion: Hidden, asymptomatic individual of diabetes, and hypertension were identified; the WHO-ISH 10 year risk prediction chart was easier for assessing the CVD risk factors and risk grouping, and could also be used to show them the extent of risk and predicting their 10-year risk of stroke or myocardial infarction (MI).
Keywords: Cardiovascular diseases (CVD) risk, screening, World Health Organization–International Society of Hypertension (WHO-ISH) 10-year CVD risk prediction chart
|How to cite this article:|
Savitharani B B, Madhu B, Renuka M, Sridevi, Ashok N C. 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
|How to cite this URL:|
Savitharani B B, Madhu B, Renuka M, Sridevi, Ashok N C. 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 [serial online] 2016 [cited 2019 Oct 15];4:13-6. Available from: http://www.heartindia.net/text.asp?2016/4/1/13/178119
| Introduction|| |
Noncommunicable diseases are increasing and constitute a serious concern, accounting for 52% of the deaths and 38% of the disease burden in the World Health Organization (WHO) South-East Asia Region. Eighty percent of total deaths due to noncommunicable diseases occur in the low-income countries. Cardiovascular diseases (CVD) will be the largest cause of death and disability in India by 2020.
A hospital setting-based approach for health promotion includes conducting risk factor surveillance as one of its components. Tertiary care hospitals with their huge resources and infrastructure are ideal for initiating preventive and promotional activities, for which baseline data on prevalence of CVD risk factors is essential. The present study was planned with the objectives of assessing the CVD risk factors and predicting the 10-year risk of stroke or myocardial infarction (MI) among the supporting staff (staff nurse, office staff, technicians, and others) of JSS Hospital, Mysuru, Karnataka, India.
| Materials and Methods|| |
Study settings and procedure
A cross-sectional study was carried out in JSS Hospital, Mysuru from October 2014 to December 2014. A screening program for all supporting staff of JSS Hospital, Mysuru was organized as a part of health appraisal/regular medical fitness for employment. Supporting staff who attended the screening program were included in the study. Sociodemographic information including age, sex, and occupation was collected. Diabetes mellitus, hypertension status, and smoking and alcohol history were taken. Blood pressure and random blood sugar measurements were recorded for each participant.
CVD risk factor profiling of the staff was done using WHO–International Society of Hypertension (ISH) risk prediction chart to calculate the 10-year risk of fatal or nonfatal major cardiovascular events according to age, gender, blood pressure, smoking status, and presence or absence of diabetes.
Blood pressure was measured using the mercury sphygmomanometer. As the screening program was carried out during working hours, we could not estimate fasting blood glucose, but we were able to measure random blood sugar using a glucometer. All newly detected diabetic and hypertensive subjects were referred for further evaluation.
Necessary prior permission was obtained from the Director and Superintendent of the Hospital and informed consent was obtained from each participant.
The statistical package SPSS (version 22) developed by IBM (International Business Machines) was used for analysis, proportions were calculated for nominal data, and continuous data were given as mean and standard deviation, while categorical variables were compared using the chi-square test for difference of proportion.
All analyses were two-tailed, and P< 0.05 was considered as statistically significant.
| Results|| |
Around 900 supporting staff of different cadres attended the screening program. The mean age of the study population was 33.2 (±8.1) years, and 400 (40%) were males and 598 (59.9%) were females [total N = 998]; the remaining were missing data.
Occupational data was available for 883 records, and of them 580 (65.7%) were staff nurses, 129 (14.6%) were office staff, 100 (11.3%) were technicians (x-ray technician, lab technician, cath lab technicians, and all other technicians), and 74 (8.4%) were employed in other jobs (engineers, ward boys, pharmacists)) [Table 1].
Among 900 employees, 30 (3.3%) had hypertension and 20 (2.2%) were known cases of diabetes mellitus and were on treatment. Excluding the known diabetics, the remaining 869 were screened for diabetes mellitus, of whom 32 (3.7%) were prediabetics and 8 (0.9%) were diabetics and it showed significance (P = 0.05). The proportion of newly detected prehypertensives was 292 (39.08%), and 2 7 (3.61%) were hypertensives [Table 2].
Out of the 20 known diabetics, 9 (45%) had controlled blood glucose levels. Among 30 known cases of hypertension, 13 (43.33%) were under controlled status [Table 3]. The information on the systolic blood pressure and diastolic blood pressure was available for 776 individuals and random blood sugar was estimated for 989 individuals. The mean values of these variables are described in [Table 4].
|Table 4: Mean difference of age, blood glucose, and blood pressure between males and females|
Click here to view
Around 18 (1.99%) of them gave a history of consuming tobacco, and 5 out of 679 (0.7%) gave a history of consuming alcohol. Around 175 individuals were aged above 40 years, for whom we applied the WHO-ISH risk prediction chart, 3 (1.7%) had >10% of CVD 10-year risk and 172 (98.3%) had less than 10% risk [Table 5].
|Table 5: 10-year risk of cardiovascular disease according to WHO-ISH risk prediction chart|
Click here to view
| Discussion|| |
Industrialization, globalization, urbanization, and economic transition bring about lifestyle changes that promote heart diseases. The risk factors include tobacco use, physical inactivity, and unhealthy diet. Life expectancy in developing countries is rising sharply and people are exposed to these risk factors for longer periods, CVD burden in terms of morbidity and mortality are increasing among the poorest in low- and middle-income countries (LMIC).
Our results reinforce the need for low-cost workplace intervention programs. Hidden, asymptomatic individuals with diabetes mellitus and hypertension were identified and 10-year risk for CVD was assessed using the WHO-ISH 10-year risk prediction chart. Additionally, we did a risk profile for CVD among supporting staff and we were able to show and describe to them where they stand on the risk for CVD using this chart.
The prediction of a high-risk group for CVD is essential because the high-risk approach is concerned not only with treating those who will benefit the most but also with avoiding unnecessary cost and adverse effects in a large number of individuals, of whom only a modest number will derive any benefit.
One hundred seventy-five were aged above 40 years, for whom we applied the WHO-ISH risk prediction chart, 3 (1.7%) had >10% of CVD risk within the next 10 years, 172 (98.3%) had less than 10% risk. However, low risk does not mean “no risk.” So measures that have positive impact on health should be taken to reduce the burden.
Another study in Seychelles reported 5.1% of the population (40-64 years old) with high total CVD risk in 2004. The prevalence of high total CVD risk was estimated to be less than 10% in people aged 40 or over in eight LMIC: China 1.1%, Iran 1.7%, Sri Lanka 2.2%, Cuba 2.8%, Nigeria 5.0%, Georgia 9.6%, Pakistan 10.0%. Another study reported the prevalence of WHO-ISH “high CVD risk” (≥20% chance of developing a cardiovascular event over 10 years) of 6%, 2.3%, and 1.3% in Mongolia, Malaysia, and Cambodia, respectively.
Since the publication of the first risk scores from the Framingham Heart Study in 1976, many scores have been developed and are in use from other cohort studies, mainly in developed countries, involving Caucasian populations.,,,,,, The scores vary widely in terms of study characteristics, predictors, and CVD outcomes investigated. Risk scores based upon studies conducted in high-income countries (HIC) may not be suitable for use in low-resource settings. Therefore, the WHO-ISH developed sets of regional risk prediction charts based on fewer risk factors that can be assessed by physicians and nonphysician health workers in primary care settings for CVD prevention in each of the 14 WHO subregions.
Because of the increasing importance of cost-effectiveness, there have been a number of simplified risk-estimation systems developed recently that use a reduced number of risk factors., These systems also enhance accessibility because several eliminate the need for laboratory measurements. This means that the risk estimate can be calculated on the basis of risk factors. The WHO-ISH have developed their risk charts in formats that exclude lipid measurements; these are particularly suited to areas in the developing world where access to medical facilities is limited.
| Conclusion|| |
The WHO-ISH risk prediction chart can be used at a low-cost resource setting as a tool to predict CVD risk among asymptomatic individuals.
It can also be used as a screening tool in preplacement examinations to predict CVD risk among staff and reduce sickness absenteeism.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Mather's CD, Bernard C, Iburg KM, Inoue M, Ma Fat D, Shibuya K, et al
. Global Burden of Disease in 2002: Data Sources, Methods and Results. Global Programme on Evidence for Health Policy Discussion Paper No. 54. Geneva: World Health Organization; 2003 (revised 2004).
World Health Organization. The World Health Report 2002. Geneva: WHO; 2002.
Kar SS, Thakur JS, Jain S, Kumar R. Cardiovascular disease risk management in a primary health care setting of North India. Indian Heart J 2008;60:19-25.
Prabhakaran D, Shah P, Chaturvedi V, Ramakrishnan L, Manhapra A, Reddy KS. Cardiovascular risk factor prevalence among men in a large industry of northern India. Natl Med J India 2005;18:59-65.
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.
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.
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.
Kannel WB, McGee D, Gordon T. A general cardiovascular risk profile: The Framingham Study. Am J Cardiol 1976;38:46-51.
Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study. Circulation 2002;105:310-5.
Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al
.; SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. Eur Heart J 2003;24:987-1003.
D'Agostino RB, Russell MW, Huse DM, Ellison RC, Silbershatz H, Wilson PW, et al
. Primary and subsequent coronary risk appraisal: New results from The Framingham Study. Am Heart J 2000;139:272-81.
Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, May M, Brindle P. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: Prospective open cohort study. BMJ 2007;335:136.
Jones AF, Walker J, Jewkes C, Game FL, Bartlett WA, Marshall T, et al
. Comparative accuracy of cardiovascular risk prediction methods in primary care patients. Heart 2001;85:37-43.
Prevention of coronary heart disease in clinical practice: Recommendations of the Second Joint Task Force of European and other Societies on coronary prevention. Eur Heart J 1998;19:1434-503.
Joint British recommendations on prevention of coronary heart disease in clinical practice. British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society, endorsed by the British Diabetic Association. Heart 1998;80(Suppl 2):S1-29.
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.
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.
Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: The NHANES I Follow-up Study cohort. Lancet 2008;371:923-31.
Prevention of Cardiovascular Disease: Guidelines for Assessment and Management of Cardiovascular Risk. Geneva, Switzerland: World Health Organization; 2007.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]