Research Article: Association between socioeconomic position and cardiovascular disease risk factors in rural north India: The Solan Surveillance Study

Date Published: July 8, 2019

Publisher: Public Library of Science

Author(s): Anubha Agarwal, Devraj Jindal, Vamadevan S. Ajay, Dimple Kondal, Siddhartha Mandal, Shreeparna Ghosh, Mumtaj Ali, Kavita Singh, Mark D. Huffman, Nikhil Tandon, Dorairaj Prabhakaran, Antonio Palazón-Bru.

http://doi.org/10.1371/journal.pone.0217834

Abstract

Although most Indians live in rural settings, data on cardiovascular disease risk factors in these groups are limited. We describe the association between socioeconomic position and cardiovascular disease risk factors in a large rural population in north India.

We performed representative, community-based sampling from 2013 to 2014 of Solan district in Himachal Pradesh. We used education, occupation, household income, and household assets as indicators of socioeconomic position. We used tobacco use, alcohol use, low physical activity, obesity, hypertension, and diabetes as risk factors for cardiovascular disease. We performed hierarchical multivariable logistic regression, adjusting for age, sex and clustering of the health sub-centers, to evaluate the cross-sectional association of socioeconomic position indicators and cardiovascular disease risk factors.

Among 38,457 participants, mean (SD) age was 42.7 (15.9) years, and 57% were women. The odds of tobacco use was lowest in participants with graduate school and above education (adjusted OR 0.11, 95% CI 0.09, 0.13), household income >15,000 INR (adjusted OR 0.35, 95% CI 0.29, 0.43), and highest quartile of assets (adjusted OR 0.28, 95% CI 0.24, 0.34) compared with other groups but not occupation (skilled worker adjusted OR 0.93, 95% CI 0.74, 1.16). Alcohol use was lower among individuals in the higher quartile of income (adjusted OR 0.75, 95% CI 0.64, 0.88) and assets (adjusted OR 0.70, 95% CI 0.59, 0.82). The odds of obesity was highest in participants with graduate school and above education (adjusted OR 2.33, 95% CI 1.85, 2.94), household income > 15,000 Indian rupees (adjusted OR 1.89, 95% CI 1.63, 2.19), and highest quartile of household assets (adjusted OR 2.87, 95% CI 2.39, 3.45). The odds of prevalent hypertension and diabetes were also generally higher among individuals with higher socioeconomic position.

Individuals with lower socioeconomic position in Himachal Pradesh were more likely to have abnormal behavioral risk factors, and individuals with higher socioeconomic position were more likely to have abnormal clinical risk factors.

Partial Text

Cardiovascular disease is the leading cause of mortality in India.[1,2] United Nations Member States agreed on selected risk factor targets to reduce premature mortality from cardiovascular and other non-communicable diseases by 25% by 2025 and by one-third by 2030.[3–5] These risk factors for cardiovascular disease such as high systolic blood pressure, high fasting plasma glucose, high total cholesterol and high body mass index (BMI) contributed about twice as many disability adjusted life years in India in 2016 compared to 1990 according to the Global Burden of Disease Study.[6] A 2017 meta-analysis of 1.7 million individuals demonstrated an inverse association between socioeconomic position and premature mortality, highlighting social determinants as a key target for improving population health.[7] To achieve progressive global health targets, a better understanding of the sociodemographic patterning of cardiovascular disease risk factors is needed in rural India, where the majority of India’s population resides.[4] To address this gap, we sought to describe the distribution and association between indicators of socioeconomic position and cardiovascular disease risk factors in a large, representative rural population in Himachal Pradesh, India.

We enrolled 40,017 participants. We excluded 1,560 participants (3.9%) with missing data in the exposures or outcomes to arrive at a complete case analysis of 38,457 participants. The characteristics of participants with missing data are presented in S2 Table. A greater proportion of excluded participants with missing data had primary school and below education (24.7% vs 20.3%, P <0.001), household income less than or equal to 5,000 INR (34.8% vs 29.9%, P <0.001), and low household assets (33.8% vs 24.7%, P <0.001). There were no differences between excluded and included participants in current tobacco use (12.2% vs 11.0%, P = 0.12) and current alcohol use (8.3% vs 7.5%, P = 0.24). In this large, representative rural population in Himachal Pradesh, India, we observed mixed patterns between the association of socioeconomic position and cardiovascular disease risk factors. Low socioeconomic position as measured by education, household income, and household assets was associated with abnormal behavioral risk factors of tobacco and alcohol use. In contrast, high socioeconomic position as measured by education, household income, and household assets was associated with abnormal clinical risk factors of obesity, hypertension, and diabetes. There was no consistent pattern amongst occupation and cardiovascular disease risk factors in rural Himachal Pradesh, which may be due to high rates of not working or homemaker status. In this large, representative rural population in Himachal Pradesh, India, we observed mixed patterns between the association of socioeconomic position and cardiovascular disease risk factors. Individuals with lower socioeconomic position were more likely to have abnormal behavioral risk factors, and individuals with higher socioeconomic position were more likely to have abnormal clinical risk factors. Thus, context is essential in understanding the relationship between disadvantage and disease. We demonstrate that the patterns of higher prevalence of obesity, hypertension, and diabetes amongst the wealthier strata observed in urban India are also observed in rural India.[10] A better understanding of the social patterning of disease can guide cardiovascular disease prevention efforts to target higher risk groups in rural India.   Source: http://doi.org/10.1371/journal.pone.0217834

 

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