Assessment of cardiovascular risk among adults in a rural area of Kancheepuram district, Tamil Nadu

INTRODUCTION

The increasing lifespan of the world’s population over the years has resulted in a dramatic change in the health care needs of the people, with non-communicable diseases (NCDs), rapidly replacing infectious diseases and malnutrition as the leading causes of disability and premature death. According to the Global Health Observatory Data of the WHO, ischemic heart disease, stroke and chronic obstructive lung disease have remained the top killers during the past decade.¹ India presents a bleak picture with ischemic heart disease being the leading cause of death currently with an alarming increase of 41.5% from 2005 to 2016.² Compared to other developed countries, the hallmarks of cardiovascular disease (CVD) epidemiology in India are high mortality rates, premature CHD, and increasing burden all across the country.³ CVD has emerged as the leading cause of death in all parts of India, including poorer states and rural areas. The improvements in socioeconomic status leading to changes in dietary patterns, high prevalence of diabetes, tobacco use, lack of timely medical care, etc are reasons stated for increased morbidity and mortality of CVD in rural areas of the country.⁴ Early detection and innovative, customized preventive strategies are the need of the hour to counter rising trends of CVDs especially in rural areas. Assessment of the prevalence of cardiovascular risk factors is the first step towards developing any interventional or preventive strategy but risk scores based upon studies conducted in high income countries may not be suitable for use in low-resource settings. The World Health Organization and the International Society of Hypertension (WHO/ISH) developed sets of regional risk prediction charts based on fewer risk factors that can be assessed by physicians and non-physician health workers in primary care setting. In this study, we have used the WHO/ISH risk prediction charts tailor – made for the SEAR D region, under which India falls, to assess the cardiovascular risk of a rural population residing in Kancheepuram district of Tamil Nadu.

METHODS

In this cross- sectional study, we have attempted to assess the CVD risk score and prevalence of CVD risk factors among the target population, by utilizing the risk charts and studying other established risk factors for the same.

This study was carried out during August to October 2015 in three villages of Chunampet in Kancheepuram district with a population of 3145 individuals from among 10 villages falling under the Rural Health Training Centre of the Pondicherry Institute of Medical Sciences by simple random sampling.

All available individuals aged more than 40 years were invited to take part in the study. Subjects unavailable during home visits on two separate days were excluded from the study. In addition, those individuals with confirmed atherosclerotic CVD and those who were critically ill were excluded from the study. In total, 400 subjects participated in the assessment.

After obtaining verbal consent, interview was done using pre designed and pre-tested questionnaire. Anthropometric measurements like standing height (in cms) and weight (in kgs) without shoes or chappals were recorded close to one decimal point after standardization using stadiometer and weighing machine, respectively; waist circumference was measured using inch tape. Two Blood pressure readings were measured in sitting position at an interval of 5 minutes using sphygmomanometer. Blood cholesterol levels of subjects if available were also documented. Cardiovascular risk was predicted using WHO – ISH Risk prediction charts for South East Asian region.

Operational definitions

For the categorization of the work status (viz. employed and unemployed) guidelines of Census 2001, recommended by the Government of India were utilized.⁵ BG Prasad modified classification was employed for classifying the study population as per their socio-economic status.⁶ Smoking was defined as the use of any smoke form of tobacco product in the last six months. Alcohol use was defined as consumption of any type of alcohol in the last one year. Hypertension grading was done based on the JNC classification.⁷

Statistical analysis

The collected data was entered in Microsoft Excel. Data were analyzed by the SPSS version 16.0 for Windows (SPSS Inc., Chicago, IL, USA). Frequency distributions and percentages were computed for all the variables. The association between various study categorical variables and gender was calculated by using Chi-Square test. P-values were considered significant when values were less than 0.05.

RESULTS

Majority of the study participants belonged to the age group 41-50 years. Female participants (54.3%) were higher than male participants (45.7%). About 54% of the study participants had no formal schooling. Majority of the participants were daily wage laborers (39.5%) and belonged to the Class IV socio economic status (34.3%) and most of them were married (90.5%).

Among the study participants 338 (84.5%) of them had their blood pressure checked at least once by a health worker or doctor and 166 (41.5%) were in stage I or stage II hypertension and 252 (63%) of the study participants had their blood sugar checked at least once out of which 73 of them (28.9%) had high blood sugar. Out of the participants who had high blood sugar, 46 (63.01%) was taking treatment for the same, either tablets or insulin.

Among the study participants 14.8% were smoking tobacco products. Twenty nine percent of the study population was using oral tobacco products. Among the study participants 29.8% of them consume alcohol (former & present alcoholics).

The Table 1 shows that 85.5% of the study participants had <10% of cardiovascular risk.

About 9.3% of the study population was not taking any fruits in their daily diet while 56.5% were taking fruits for two days in a week. Close to half (45.5%) of the study population were taking vegetables all the days of the week and 41.5% of the study population were using unsaturated cooking oil for cooking

Regarding physical activity, 48.8% of the study participants’ occupation involved moderate physical activity and 80% of the study population either walked or used a bicycle for at least 15 minutes a day to travel.

DISCUSSION

This study was done in a rural area to assess the cardiovascular risk among the individuals aged 40 and above. The study results showed a cardiovascular risk score of more than 10% among 14.5% individuals while a low cardiovascular risk score of less than 10% among 85.5% of study participants. In a similar study by Ghorpade et al in a rural population in South India, using WHO risk charts to predict the CV risk, 86% of the population had low risk less than 10% and a risk score of more than 20% was seen among 10.2% of the population.⁸ These findings are similar to our study. Various studies have revealed a variable level of prevalence of CVD risk using the similar WHO/ISH risk prediction charts in some of the Asian countries (viz. China 1.1%, Iran 1.7%, Sri Lanka 2.2%, Nepal 9.8%, and Pakistan 10.0%).^9,10 These differences can be attributed to the differences in population genetically and according to their lifestyle followed. Among the participants in our study, 41.5% were in stage I or II hypertension. The findings were slightly higher than other Indian studies where the prevalence of hypertension ranged from 26%-33%. This shows that there is an increasing trend of CVD risk factors especially in the rural areas. In our study, people who belonged to the class II SES had higher risk for CVD when compared to class V SES and is statistically significant (p=0.000). It is similar to a study done by Ghaffar et al in India which showed that individuals with high levels of income are at a higher risk, thus suggesting that CVD burden is high among the upper socio-economic class even in rural areas.¹¹ Use of oral tobacco, saturated cooking oils and sedentary occupation was found to be associated with high CV risk, in our study, similar to other studies.^12,13 However the association of CV risk with other risk factors like smoking and BMI is inconsistent and not statistically significant.

Limitation

The present study was conducted in only three of the villages of rural Tamil Nadu (viz. sample size being small) and thus findings of the study cannot be generalized to the other populations.

Recommendation

The risk prediction chart used in this study can be used in primary care setting and hence developing a comprehensive risk prediction chart for the Asian population including specific risk factors relevant to the population shall be more fruitful.

ACKNOWLEDGEMENTS

The Authors would like to acknowledge the support of Interns, Medical Officers and Field staff of Rural Health Training Centre of PIMS in carrying out this study.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: Not required

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