Cardiovascular risk according to educational status in India
Introduction
Cardiovascular diseases are epidemic in India (Murray and Lopez, 1997, Gupta et al., 2008). These diseases are considered to be more prevalent in upper socioeconomic status (SES) subjects (Sarvotham and Berry, 1968, Reddy, 1993). Using the corollary of North American and Western European countries where cardiovascular diseases were more frequent in upper SES subjects till 1960s and then became more among the poor (Marmot, 1992), it has been argued that burden of cardiovascular diseases could be shifting in India and presently may be more in poor subjects (Gupta and Gupta, 2009). However, reliable national SES specific mortality statistics do not exist (Registrar General of India, 2009). Many cardiovascular risk factor epidemiological studies in mid and late 20th century reported that risk factors were more in upper SES subjects as compared to the poor (Padmavati, 1962, Sarvotham and Berry, 1968, Chadha et al., 1990). Recent case-control studies in India have reported that SES, as measured by educational status (ES), is inversely related to acute myocardial infarction (Pais et al., 1996, Rosengren et al., 2009) and observational studies have reported that low SES subjects are more likely to die from acute coronary events as compared to the rich (Xavier et al., 2008).
In India, the urban population is facing major brunt of cardiovascular epidemic and it is likely that the epidemiological transition has evolved here (Yusuf et al., 2001). No previous population based studies from India have reported comprehensive cardiovascular risk (Gupta et al., 2008) especially in low SES subjects (Gupta and Gupta, 2009). A revised version of Framingham risk score has been developed to quantify cardiovascular risk and predict coronary heart disease, stroke, peripheral arterial disease and heart failure (D'Agostino et al., 2008). There are no specific risk scores derived for South Asian or Indian populations although the revised British risk score (QRISK2) (Hippisley-Cox et al., 2008) and WHO risk chart (WHO 2007) have separate focus for South Asians. The British risk score has not been validated in India and the WHO cardiovascular risk prediction charts for South East Asian subjects provide only a visual algorithm and cannot be used to quantify the risk. Chow et al. (2009) recalibrated the Framingham risk score using mortality data in an Indian rural population and found that the predictive value of the locally developed score was the same as the original. We performed a study using the Framingham risk score to determine cardiovascular risk in different ES subjects (as marker of SES) in an Indian urban population.
Section snippets
Methods
We performed cross sectional epidemiological studies to determine cardiovascular risk factors in urban populations in Jaipur (India) in years 1999–2003. The studies were approved by the institutional ethics committee. We conducted stratified cluster sampling on the Voters' lists in six and two locations in Jaipur in two separate studies respectively. The study subjects were representative of local population as reported earlier (Gupta et al., 2002). In the first study (Gupta et al., 2002) of
Results
Age-adjusted prevalence of various cardiovascular risk factors was current smoking in 205 (15.4%), obesity in 219 (17.0%), truncal obesity in 785 (61.3%), hypertension in 347 (26.7%), hypercholesterolemia in 422 (33.0%), low HDL cholesterol in 722 (56.5%), diabetes in 82 (6.4%) and metabolic syndrome in 332 (25.9%). There were very few ex-smokers (10 men). Isolated non-smoked tobacco was low in men (n = 2) and high in women (n = 32). Illiteracy and low ES was present in 306 subjects (23.9%), middle
Discussion
This study shows that urban Indian subjects with low and middle educational status have greater cardiovascular risk than the highly educated. The greater risk is principally due to the high prevalence of smoking in these groups. Gupta et al. (1994) reported greater prevalence of multiple cardiovascular risk factors (smoking, sedentary lifestyle and hypertension) among the illiterate in a rural Indian population. Reddy et al. (2007) reported correlation of educational status with multiple
Conflict of interest statement
The authors declare that there are no conflicts of interest.
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