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Quantifying Socioeconomic and 

Lifestyle Related Health Risks: 
Burden of Cardiovascular Disease Among 
Indian Males 

 

Neetu Purohit1, Divya K. Bhati1, 

Shiv D. Gupta1, Azad S. Kundu2 

 
1Indian Institute of Health Management Research 

University; 2Indian Council of Medical Research 

 

Vol. 4, No. 2 (2015)   |   ISSN 2166-7403 (online)  

DOI 10.5195/cajgh.2015.218 |   http://cajgh.pitt.edu 

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Abstract 

Background: Non-communicable diseases account for a significant disease burden in the South East Asia region. India is facing 

an increased incidence of lifestyle-related diseases, such as cardiovascular disease. Socioeconomic and lifestyle risk factors for 

cardiovascular disease (CVD) have been under investigated in India. This study was designed to explore risk factors contributing 

to the development of cardiovascular disease among Indian males. 

Methods: A population-based cross-sectional study was conducted among 2,235 males in the age group of 18-60 years across three 

states of India. A household survey was used to collect demographic and socioeconomic status information in addition to lifestyle-

related attributes such as smoking, alcohol consumption, diet, and physical activity. Descriptive statistics and logistic regression 

were performed to identify the role of various factors that may be associated with the development of cardiovascular disease in this 

population. 

Results: The prevalence of cardiovascular disease among the male respondents contacted through a household survey was reported 

to be 9.8%. Logistic regression revealed that males with higher education and higher income were more likely to report CVD. With 

age as a strong predictor of CVD, the risk of CVD was found to be five times higher in the older age group. Current smokers were 

1.3 times more likely to have CVD compared to those who never smoked. Those who were engaged in physical activity were less 

likely to have CVD; however, the adverse effects of smoking and excessive consumption of red meat showed a stronger association 

with CVD than the protective effects of physical activity.  

Conclusion: In developing countries, where the increase in earning capacity and change in lifestyle has been found to be 

accompanied by substantial risk of heart disease for males, public health measures like health promotion programs need to be 

implemented to decrease CVD burden. 

Keywords: cardiovascular diseases, risk factors, lifestyle, behavior, smoking, physical activity 

Quantifying Socioeconomic and 

Lifestyle Related Health Risks: 
Burden of Cardiovascular Disease Among 
Indian Males 
 
Neetu Purohit1, Divya K. Bhati1, Shiv 
D.Gupta1, Azad S.Kundu2 

1Indian Institute of Health Management Research University; 
2Indian Council of Medical Research 

Research 

Non-communicable diseases (NCDs) account 

for an increasing share of disease burden. In 1998, 43% 

(36 million) of global mortalities were due to NCDs and 

are expected to increase to 73% by 2020.1 Among NCDs, 

cancer, cardiovascular disease (CVD), and diabetes are 

of serious concern, accounting for 52% of all deaths and 

38% of disease burden in the World Health Organization 

South East Asia Region (WHO-SEAR). In the 

industrialized world and developing nations such as 

India,2 CVDs are the primary causes of death and 

disability.3 According to WHO, an estimated 17 million 

people died from CVD in 2005, comprising 80% of the 

deaths in low and middle income countries. In a 

developing country like India, 35% of all CVD deaths 

occur in working age adults (aged 35-64 years) which 

makes prevention of these deaths crucial for society.4 

Unlike other non-communicable diseases, CVD 

is one of the most preventable causes of death in the 

world, as a majority of its risk factors are controllable. 

Worldwide, approximately 31% of heart disease is 

believed to be attributable to poor diet and 22% to 

physical inactivity, and a further 22% is estimated to be 

attributable to smoking in industrialized countries.5 Until 

the 1990s, CVD was regarded as a disease of the affluent 

class in India.6 However, studies conducted in 1996, 

2004, and 2006 showed a higher incidence of CVD 

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events among lower socioeconomic groups, reflecting a 

reversal of the social gradient of CVD within socially 

disadvantaged groups in India.7-10 

There are significant gaps in the knowledge of 

CVD associated risk factors in countries of the South 

Asian region. In India, there has been no national study 

that has used a uniform methodology to assess prevalence 

of multiple cardiovascular risk factors. Existing studies 

in India were done at different geographic locations and 

in different time periods.11 A recently published report 

indicated that new and more rigorous research and 

surveillance studies are needed in India to assess the 

extent of NCD burden.12 Due to scarce national level 

data, there is a lack of effort to initiate policy changes for 

controlling the CVD epidemic.13 However, a few public 

health sentinel surveys have found that a cluster of major 

risk factors (tobacco, alcohol, inappropriate diet, and 

physical inactivity) govern the occurrence of CVDs in 

India.14 Studies have also found that rapid dietary 

changes associated with a decrease in levels of physical 

activity also play a particularly important role in the 

increasing incidence of cardiovascular diseases.15 

The purpose of this multi-site study was to 

determine the contribution of several socioeconomic and 

lifestyle factors to cardiovascular diseases among the 

adult male population of India. It was hypothesized that 

lifestyle factors, such as socioeconomic characteristics 

(e.g. age, education, place of residence, income, 

occupation) and lifestyle factors (e.g. smoking, alcohol 

consumption, red meat consumption, physical activity) 

are predictors of CVD in Indian population.   

 

Methods  

Sample size calculation, site, and study tools 

A population-based, multi-centric, cross-

sectional survey was conducted in three major states in 

India, including Rajasthan, Maharashtra, and West 

Bengal, which represent the Northern, Western, and 

Eastern regions of India, respectively (Figure 1). The 

appropriate sample size needed was determined using the 

standard formula as described in World Health 

Organization sample size determination manual.16 

 

Figure 1. Study locations in India: Rajasthan, 

Maharashtra and West Bengal  

 

The sample size of 1,480 adults per state was 

calculated using 10% precision and took into account a 

non-response rate of 15%. Thus, the total study sample 

included 4,460 adults in the age group of 18-60 years 

(2,225 females and 2,235 males). This paper presents the 

sub-study focusing on data collected from 2,235 male 

participants (Figure 2). In 2001-2003, a large scale study 

was conducted by the Registrar General of India, which 

reported that cardiovascular disease (CVD) was the 

major cause of deaths in males (20.3%) as compared to 

females (16.9%);17 hence, the authors decided to report 

results on  the male population first. Further, the data 

from females was not considered for this particular paper 

as the risk factors for females are not necessarily identical 

to males and a separate analysis quantifying risk factors 

among females is proposed in a separate follow up 

publication.  

 

Figure 2. Sample selection flow-chart 

 

The multilingual household survey 

questionnaire was prepared by the Indian Council of 

Medical Research (ICMR, Delhi). The structured survey 

questionnaire and its contents were validated with the 

help of literature review and face validity was conducted 

with experts working in the area of NCDs / CVDs. The 

questionnaire was translated into Hindi / relevant 

regional languages and subjected to forward and 

backward translation. The structured questionnaire was 

pre-tested with respondents with similar characteristics 

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who reside in a different geographical area (other than the 

study area) to ensure the sequencing and understanding 

of the questions. Suggestions from the study team and 

experts were incorporated into the questionnaire before 

its administration within the study area. Ethical clearance 

for the study was obtained from the ethical review board 

of Indian Council of Medical Research (ICMR), which 

was the funding agency for this multi-centric study. 

Verbal consent (due to concern about literacy level) was 

obtained from study respondents prior to survey 

administration. The study team was comprised of a 

principal coordinator and research officers. The study 

team provided uniform study procedure-related training 

to the field investigators of the respective states. The field 

investigators administered the structured questionnaire 

through face-to-face interviews. The responses were 

recorded by the field investigators in a standardized 

format.  

Definitions and measurement 

The outcome variable was the presence or 

absence of self- reported cardiovascular disease, which 

was defined as per World Health Organization.17 For the 

purpose of this study, cardiovascular disease has been 

defined as coronary heart disease (heart attacks), 

cerebrovascular disease (stroke), high blood pressure 

(hypertension), peripheral artery disease, rheumatic heart 

disease, congenital heart disease, and congestive heart 

failure.18 Information on demographic, socioeconomic 

and lifestyle risk factors was ascertained through the 

questionnaire developed by the study team. Study 

population was divided into two age categories (18 to 40 

years) and (41 to 60 years). Current place of residence 

was classified as rural or urban. Self-reported educational 

attainment levels were grouped in five categories (i.e. 

illiterate/no-schooling, primary [≤5thgrade], secondary 

[≤12th grade], graduate [including post-graduate], and 

professional degree). Occupation was divided into 8 

categories: skilled or unskilled labor, agriculture, 

military/police, office job, business/shop, managerial 

position, unemployed, and teachers/small traders. Per 

capita monthly family income from all sources was 

grouped into three categories: low income group (LIG): 

< 5,326 INR (< $83.75), middle income group (MIG): 

5,327 INR – 21,067 INR ($83.76 - $331.25), and high 

income group (HIG): > 21,068 INR (>$331.26).19 As per 

the Global Adult Tobacco Survey report in 2009,20 

current smoker has been defined as a person who had 

smoked over their lifetime, and continued to smoke every 

day or some days. Ever smoker was defined as a person 

who had smoked sometime in their lifetime, but does not 

smoke currently. A never smoker was defined as a person 

who never smoked over their lifetime.20 Current alcohol 

user was defined as a person who consumes alcohol 

every day or some days. Ever alcohol user was defined 

as a person who was consuming alcohol in the past and 

stopped consuming alcohol. A never alcohol user was 

defined as person who never consumed alcohol over their 

lifetime.21 Diet was categorized in terms of consumption 

of non-vegetarian food (i.e.consumption of red meat 

daily or 3 to 5 times a week, and no consumption of red 

meat). Physical activity time was defined based on the 

WHO global recommendation on involvement in any 

physical activity for 30 minutes or more per day.22 

Statistical analysis  

Descriptive statistics were used to describe the 

sample characteristics. Bivariate regression model 

estimates the contribution of indicators of socioeconomic 

status and lifestyle factors to self reported CVD. The 

dependent variable was presence or absence of self-

reported CVDs. Statistical assessments were carried out 

using Statistical Package for Social Sciences (SPSS) 

version 20.0 (Chicago IL). All statistical analyses were 

considered significant when the p-value was < 0.05 at 

95% confidence interval.  

 

 

 

 

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Results 

Population characteristic: Socioeconomic and lifestyle 

attributesof respondents  

A total of 2,235 males from three states were 

included in the present subanalysis. Their socioeconomic 

status and lifestyle factors are presented in Table 2 by 

geographical region. Of the total interviewed males, the 

prevalence of self-reported cardiovascular disease was 

found to be around 9.8%.  The age of interviewed 

respondents ranged from 18 to 60 years with a mean age 

37.51+12.16 (Table 2). The majority (61.0%) of 

respondents were in the 18 to 40 years age group. 

 

Table 1. Percent distribution of respondents by 

socioeconomic characteristics and lifestyle factors 

 

Table 1 also shows that approximately 45% of 

the respondents were residing in rural areas. Nearly 

37.5% of the respondents completed elementary 

education. Education beyond grade school was reported 

by 31.3% males and 10.9% reported having a 

professional degree. Occupation of the interviewed 

respondents shows that around 40.6% were engaged in 

professions involving physical activity, such as skilled 

/unskilled labor, agriculture, and police or military 

service. About 21% and 12.9 % of the respondents were 

from high and middle income categories, respectively. 

The proportion of smokers, alcohol consumers, those 

who consumed red meat daily (or 3 to 5 times a week), 

and those engaged in regular physical activity was also 

assessed. Results showed that never smokers and those 

who never consumed alcohol constituted 50.0% and 

64.1% of the sample, respectively.  About 18.1% of the 

respondents consumed red meat daily or 3 to 5 times a 

week. Results also showed that involvement in regular 

physical activity was as high as 76.0%. 

 

 

Predictors of CVD 

Based on bivariate logistic regression analysis, 

Table 2 illustrates the estimated odds ratios for 

association between CVD and socioeconomic and 

lifestyle related attributes. Age was a strong predictor of 

CVD; males who were 41-60 years old had a 5-fold 

increased risk of having CVD compared to those in the 

age group of 18-40 years. Compared to males who were 

illiterate or have received only non-formal education (i.e. 

able to write their names and read and write on 

rudimentary level), those with a professional degree were 

2.1 times more likely to have CVD. Further, males who 

were living in urban areas were 1.5 times more likely to 

have CVD as compared to those living in rural areas.  

 

Table 2. Bivariate logistic regression analysis of 

predictors of cardiovascular diseases 

 

For occupation, compared to those engaged in 

skilled/unskilled labor, males in teaching and trading jobs 

were 1.8 times more likely to get CVD. The odds for 

other occupation categories did not show a significant 

relationship with CVD. Income level has also been 

associated with CVD level. Compared to those in a low 

income category, participants with a high income had a 

marginally significant increased odds of having CVD 

(OR=1.39, p=0.09). With respect to lifestyle related 

attributes, smoking and consumption of red meat daily or 

3-5 times a week showed a significant positive 

relationship with CVD. Males who consumed red meat 

were 1.6 times more likely to have CVD than those who 

did not consume red meat at all. Smoking was found to 

be adversely affecting cardiovascular health. Compared 

to those who did not smoke, smokers were 1.3 times more 

likely to get CVD. Engagement in physical activity 

showed a negative significant relationship with CVD, 

which indicated that compared to those who did not 

engage in physical activity, those who engaged in 

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physical activity had 0.7 times less likelihood of 

reporting CVD. 

Encouraged by the findings on the protective 

role of physical activity for CVD, we attempted to 

investigate the interaction effect of physical activity with 

red meat consumption and physical activity with 

smoking. These lifestyle variables were univariably 

marginally or significantly associated with CVD. We 

then tested whether or not there was an interaction 

between the lifestyle factors; however, all interactions 

tests were non-significant (Table 3). 

 

Table 3. Logistic regression of predictors of 

cardiovascular diseases: Examining interactions 

 

The first interaction examined was the 

interaction between red meat consumption and physical 

activity. Red meat consumption increased the odds of 

having CVD, although not significant, while physical 

activity significantly reduced the odds of reporting CVD. 

The interaction effect suggested that there may be an 

interaction between these two factors, as the significance 

of red meat consumption was attenuated when adjusting 

for this interaction. However, this interaction effect was 

not found to be statistically significant (p=0.40). Our 

results suggest that the risks of CVD associated with 

excessive consumption of red meat cannot be ruled out, 

even in presence of engaging in physical activity. The 

second interaction examined was the one between 

smoking and physical activity. Simlarly with the previous 

interaction test, physical activity was still significantly 

associated with lower odds of having CVD, while 

smoking increased the odds of reporting CVD. This 

interaction effect also suggests that there may have been 

an interaction between smoking and physical activity due 

to the attenuated significance of the effects of smoking. 

However, this interaction was not found to be statistically 

significant (p=0.33). 

Discussion  

This study examined the association between 

lifestyle and CVD among Indian males. Physical activity 

was found to reduce the odds of having CVD by 28%, 

while red meat consumption and smoking increased the 

odds of having CVD by 62% and 38%, respectively.  

Major causes of morbidity and mortality have 

undergone an epidemiologic transition from 

predominantly nutritional deficiencies and infectious 

diseases in developing nations to chronic diseases such 

as cardiovascular disease.23 With the epidemiological 

transition and increased urbanization associated with the 

increase in CVD risk factors (behavioral, social, and 

lifestyle patterns), the CVD burden is increasing in 

developing countries including India.24 Previous 

literature provides evidence that while the prevalence and 

mortality rate of CVD has decreased in developed 

nations, it has substantially increased in India, which has 

been undergoing rapid demographic, social, and 

economic change.25 Studies have shown a major income 

decline due to CVD-related losses in productive labor.3 

Understanding the health characteristics of young and 

middle aged males (18–60 years) will allow public health 

experts and policy makers to adopt focused interventions 

for prevention of disease and promoting lifestyle 

modifications. 

Age, as a risk factor for CVD, is well 

established26 and was confirmed in the current study. 

Prevalence of cardiovascular disease was found to be 

higher in the age group of 41-60 years. Additionally, 

males with higher education were found to be more 

vulnerable to the risk of reporting cardiovascular disease, 

which could be due to bias, as more educated adults may 

be more likely to report a disease. An earlier study carried 

out in the capital city of India also demonstrated that 

prevalence of heart disease was higher among literate as 

compared to illiterate participants.26 Thus, population-

specific interventions need to be designed for various 

educational groups to promote a healthy lifestyle. 

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The study findings provided further evidence 

suggesting that males in the high income group had an 

increased likelihood of reporting CVD. A study from 

southern India also reported a higher prevalence of 

coronary heart disease in high socioeconomic groups.27 

Occupation is also used as a marker in epidemiological 

studies of cardiovascular disease. A systematic review 

carried out in 2010 demonstrated an increased risk of 

cardiovascular disease in occupations involving 

prolonged sitting.28 However, the current study did not 

find any significant association of CVD with office jobs. 

We found that teachers and small traders are more 

vulnerable to CVD, but this finding was only marginally 

significant. The current study also found that urban males 

were at significantly greater risk compared to their rural 

counterparts. This is consistent with other published 

studies.29,30 

Corroborating earlier studies, this study 

reported that smoking adversely affects cardiovascular 

health. Smoking has been shown to be a major risk factor 

for chronic illnesses in males below 65 years of age in 

developing countries.31 In long-term smokers, smoking is 

responsible for more than 50% of avoidable deaths, and 

one half of these are due to CVD.31 Our study did not 

establish any significant association of alcohol 

consumption with CVD. However, the results of current 

study support the findings of 2010, WHO-Global status 

report on Non-Communicable Diseases, which states that 

there is a direct relationship between higher levels of 

alcohol consumption and the rise in risk of cardiovascular 

disease, which is dependent on the amount and pattern of 

alcohol consumption.32  

A systematic review carried out between 1992 

and 2009, which included 17 cohort and 3 case-control 

studies, showed that processed red meat was associated 

with a higher incidence of coronary heart disease (CHD) 

when compared with unprocessed red meat.33 A 

previously published study failed to establish a 

significant link between meat consumption with chronic 

diseases like coronary heart disease (CHD), stroke, and 

Type 2 diabetes mellitus.34 Thus, this study provides 

interesting new information.  

The benefits of physical activity on 

cardiovascular health were well established in the past 

review of key issues in public health.35 People who are 

insufficiently physically active have a 20–30% increased 

risk of all-cause mortality compared to those who engage 

in at least 30 minutes of moderate intensity physical 

activity on most days of the week. Previous studies also 

suggest that physical activity lowers the risk of stroke and 

hypertension.36 Consistent with previously published 

research, this study also reported the importance of 

regular physical activity in reducing the risk of CVD. 

This study reinforces the need to consider current 

prevention and treatment strategies at the national level 

to include behavior change,37 early diagnosis, screening, 

and early detection. Cardiovascular health awareness 

programs including but not limited to those focusing on 

obesity and smoking need to be continued and expanded 

to better educate populations about healthy lifestyles. 

However, awareness is only the first step towards 

behavior change and other factors, like developing public 

health infrastructure (i.e. parks, cycling tracks, public 

sport centers, primary care clinics, obesity prevention 

programs, addiction treatment centers), that could 

facilitate healthy lifestyle choices to be promoted. 

The results from this study add to the existing 

knowledge on the associated risk factors and their role in 

causing cardiovascular diseases among males in India. 

The primary limitation of this study was that no medical 

examination was conducted to assess the presence of 

cardiovascular diseases, and only self-reported 

cardiovascular diseases were taken into consideration. 

However, the findings of this study are relevant for other 

developing countries undergoing the edpidemiologic 

transition. Public health programs need to focus on 

building awaremenss about healthy lifestyles and 

changing public health infrastructure to promote 

healthier lifestyles, which could benefit all segments of 

society. 

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Competing interests 

The author declares that they have no competing 

interests. 

 

Acknowledgements 

The study was supported by the Indian Council 

of Medical Research, New Delhi for a grant-in-aid under 

extramural research projects to Indian Institute of Health 

Management Research, Jaipur, India. 

 

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PUROHIT 

 

 

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Table 1. Percent distribution of respondents by socioeconomic characteristics and lifestyle 

factors  

Variables 

Northern 

Region 

M±SD or % 

Western 

Region 

M±SD or % 

Eastern 

Region 

M±SD or % 

Total 

 

M±SD or % 

N 740 755 740 2235 

Age 38.45±11.75 36.64±12.93 37.46±11.69 37.51±12.16 

Age group in years 

     18-40 59.9 62.6 60.4 61.0 

     41-60 40.1 37.4 39.6 39.0 

Cardiovascular disease status 

     No 91.2 93.5 85.9 90.2 

     Yes 8.8 6.5 14.1 9.8 

Area of residence  

     Rural 40.5 53.4 40.4 44.8 

     Urban 59.5 46.6 59.6 55.2 

Education level  

     Primary 35.9 29.3 47.6 37.5 

     Secondary 33.9 37.0 23.0 31.3 

     Graduate 16.5          24.8 19.5 20.3 

     Professional  13.6 9.0 10.0 10.9 

Occupation  

     Skilled/unskilled labour 26.1 20.5 31.8 26.1 

     Agriculture 14.3 17.1 9.1 13.5 

     Official/job-clerical 8.2 20.8 15.1 14.8 

     Military/police 0.7 1.3 0.4 0.8 

     Business/shops 26.2 15.2 24.7 22.0 

     Manager/professional 8.5 10.3 6.2 8.4 

     Unemployed 4.5 8.2 3.8 5.5 

     Teacher/small traders 11.5 6.5 8.9 8.9 

Income  

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Note: M: Mean, SD: Standard Deviation 

 

 

 

 

 

 

 

 

 

      Low income  100.0 44.6 53.9 66.0 

      Middle income  0 22.8 15.8 12.9 

      High income  0 32.6 30.3 21.0 

Smoking status  

     Current/ever smoked 51.2 36.8 62.2 50.0 

     Never smoked 48.8 63.2 37.8 50.0 

Alcohol consumption  

     Current/ever use 33.0 30.9 43.9 35.9 

     Never use 67.0 69.1 56.1 64.1 

Red-meat consumption  

     No consumption 94.2 89.9 61.5 81.9 

     ≥3 times/week 5.8 10.1 38.5 18.1 

Engagement in physical activity  

     0 to 30 minutes 24.5 15.8 32.3 24.0 

     >30 minutes  75.6 84.2 67.7 76.0 

     

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PUROHIT 

 

 

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Table 2.Bivariate logistic regression analysis of predictors of cardiovascular diseases 

Risk factors Odds ratio 95% CI p-value 

Age in years    

     18-40 - - - 

     41-60 4.57 3.29 – 6.34 <0.001** 

Area of residence    

     Rural - - - 

     Urban 1.59 1.09 - 2.29 0.014* 

Education    

     Primary - - - 

     Secondary 1.25 0.78 – 1.98 0.354 

     Graduate 1.66 0.97 – 2.82 0.064† 

     Professional  2.11 1.03 – 4.33 0.041* 

Occupation    

     Skilled/unskilled labour - - - 

     Agriculture 1.03 0.54 – 1.95 0.924 

     Official/job-clerical 1.56 0.85 – 2.82 0.146 

     Military/police 1.36 0.26 – 6.90 0.712 

     Business/shops 1.37 0.80 – 2.33 0.249 

     Manager/professional 1.24 0.62 – 2.47 0.542 

     Unemployed 1.38 0.58 – 3.22 0.463 

     Teachers/small traders 1.85 0.98 – 3.46 0.054† 

Income     

     Low income - - - 

     Middle income  0.76 0.44 – 1.29 0.310 

     High income  1.39 0.94 – 2.02 0.092† 

Smoking status    

     Never smoked - - - 

     Current/ever smoked 1.383 0.99 – 1.91 0.052† 

Alcohol consumption    

     Never use - - - 

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Note: †p< 0.1, *p< 0.05, **p< 0.001 

  

     Current/ever use 1.17 0.84 – 1.61 0.333 

Red meat consumption    

     No consumption - - - 

     ≥3 times/week 1.615 1.125 – 2.31 0.009** 

Engagement in physical activity    

     0 to 30 minutes - - - 

     30 minutes or more 0.719 0.51 – 1.00 0.052† 

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PUROHIT 

 

 

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Table 3.Logistic regression of predictors of cardiovascular diseases: Examining interactions 

 Odds Ratio 95% CI p-value 

Physical activity (≥30 minutes) 0.39 0.25 – 0.62 <0.001** 

Red meat consumption (≥3 times/week) 1.43 0.89 – 2.29 0.138 

Physical activity x Red meat consumption 1.32 0.68 – 2.56 0.409 

Physical activity (≥30 minutes) 0.39 0.25 – 0.62 <0.001** 

Smoking status (current/ever) 1.37 0.94 – 1.99 0.103 

Physical activity x Smoking status 1.33 0.74 – 2.39 0.335 

Note: †p< 0.1, *p< 0.05, **p< 0.001 

 

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Figure 1. Study locations in India: Rajasthan, Maharashtra and West Bengal 

 x` 

 

 

 

 

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PUROHIT 

 

 

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Figure 2. Sample selection flow-chart 

 

 

 

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