Rheumatic Heart Disease (RHD) is a chronic condition resulting from acute rheumatic fever (ARF), which is itself a complication of untreated or inadequately treated Group A Streptococcal pharyngitis. It remains one of the leading causes of cardiovascular morbidity and mortality in children and young adults, particularly in developing countries (1,2). Although largely preventable, RHD continues to thrive in populations with limited access to healthcare and poor living conditions, making it a disease of social inequality (3).

Globally, the burden of RHD is estimated to affect over 33 million people, with the highest prevalence found in South Asia, Sub-Saharan Africa, and parts of the Pacific (4). India accounts for a significant proportion of this burden due to its vast population and persistent gaps in healthcare delivery between urban and rural regions (5). Multiple studies have shown a strong association between RHD and socioeconomic determinants such as poverty, overcrowding, limited education, and inadequate access to healthcare (6,7).

Urban and rural communities often experience different risk environments, with rural populations facing more pronounced barriers in accessing preventive and curative services (8). Understanding the influence of these socioeconomic factors is crucial for designing region-specific interventions. While several studies have addressed the epidemiology of RHD, there remains a paucity of comparative data analyzing its correlation with social determinants in both urban and rural settings within the Indian context.

This study aims to bridge that gap by evaluating the prevalence of RHD and its association with various socioeconomic indicators in urban and rural populations, thereby providing insights for more equitable health planning and policy development.

A cross-sectional, comparative observational study was conducted over a period of 12 months across selected urban and rural regions of Central India. Ethical clearance was obtained from the Institutional Ethics Committee before the commencement of the study, and informed consent was obtained from all participants or their guardians in the case of minors.

A total of 600 individuals aged between 10 and 40 years were recruited through stratified random sampling, with 300 participants each from urban and rural areas. Inclusion criteria included individuals residing in the selected regions for at least five years and those willing to participate. Exclusion criteria were individuals with congenital heart diseases, prior cardiac surgery, or a history of autoimmune disorders.

Each participant underwent a clinical evaluation, including a thorough medical history and physical examination. Suspected cases of RHD were referred for echocardiographic confirmation, following the World Heart Federation (WHF) diagnostic criteria for Rheumatic Heart Disease.

Socioeconomic data were collected through face-to-face interviews using a pre-validated semi-structured questionnaire. The questionnaire covered variables such as household income, parental education level, housing conditions, family size, and access to healthcare facilities. Socioeconomic status was classified using a modified Kuppuswamy scale for urban participants and a revised BG Prasad scale for rural participants.

The data were compiled and analyzed using SPSS version 25.0. Descriptive statistics were calculated for all variables. The Chi-square test was used to compare categorical variables, and binary logistic regression was applied to assess the association between RHD and socioeconomic determinants. A p-value of < 0.05 was considered statistically significant.

A total of 600 participants were included in the study, with 300 from urban areas and 300 from rural areas. The overall prevalence of Rheumatic Heart Disease (RHD) was 8.5%. RHD was significantly more prevalent in the rural population (11.3%) compared to the urban group (5.7%), and the difference was statistically significant (p = 0.01) (Table 1).

Table 1: Prevalence of RHD in Urban and Rural Populations

Socioeconomic indicators were analyzed to assess their association with RHD. Individuals from low-income households (monthly income < ₹10,000) had a prevalence of 14.2%, significantly higher than those from higher-income households (4.1%) (p < 0.001). Overcrowding (more than 3 persons per room) and lack of access to primary healthcare were also significantly associated with higher RHD rates (Table 2).

Table 2: Association Between Socioeconomic Determinants and RHD

A binary logistic regression analysis was performed to identify independent predictors of RHD. Low income (OR = 3.2; 95% CI: 1.7–5.8), overcrowding (OR = 2.1; 95% CI: 1.2–3.5), and poor access to healthcare (OR = 2.8; 95% CI: 1.5–5.2) emerged as significant risk factors (Table 3).

Table 3: Logistic Regression Analysis of Risk Factors for RHD

The findings underscore a strong link between poor socioeconomic status and the occurrence of RHD, with rural areas showing more pronounced vulnerability compared to urban populations (Tables 1–3).

This study highlights a significant association between socioeconomic determinants and the prevalence of Rheumatic Heart Disease (RHD), with rural populations demonstrating a markedly higher burden compared to their urban counterparts. The observed prevalence of RHD in the rural population (11.3%) is consistent with prior studies from developing nations, which report higher rates in low-resource settings due to limited access to healthcare and delayed diagnosis (1,2).

Our findings support the growing body of literature that identifies poverty as a critical risk factor for RHD (3,4). Participants from low-income households had over three times the odds of developing RHD, which aligns with studies conducted in India and sub-Saharan Africa (5,6). Poor financial status often limits timely access to antibiotics for streptococcal infections and adequate medical follow-up, both of which are crucial for the prevention of rheumatic fever and subsequent heart disease (7).

Overcrowded housing was another major predictor in our study. Similar findings were reported in Bangladesh and Nepal, where high person-per-room ratios contributed to increased exposure to respiratory infections and delayed treatment (8,9). Overcrowding creates an ideal environment for the transmission of Group A Streptococcus, especially in children and adolescents (10).

Access to primary healthcare was significantly associated with RHD prevalence. Participants with limited or no access to health services had nearly threefold increased odds of having RHD. This is consistent with previous studies emphasizing the importance of school-based screening and early intervention programs in reducing RHD burden in underserved communities (11,12).

Our study also observed that parental education, although not the strongest predictor, had a moderate effect on disease prevalence, particularly in the urban population. Educated parents are more likely to seek timely medical care and ensure adherence to antibiotic prophylaxis regimens (13).

Comparing urban and rural data, the disparity in disease burden appears to stem from multiple overlapping social determinants—ranging from financial instability to poor sanitation and lack of awareness. While urban slums also bear a high risk, rural communities often experience systemic neglect in terms of health infrastructure and outreach programs (14).

These findings highlight the need for an integrated public health approach that targets both clinical and social dimensions of disease. Strengthening rural healthcare delivery, improving health literacy, and implementing community-based rheumatic fever prevention programs could significantly curb the RHD burden (15).

The present study underscores a significant correlation between socioeconomic factors and the prevalence of Rheumatic Heart Disease, with rural populations being more adversely affected than their urban counterparts. Low household income, overcrowded living conditions, and poor access to healthcare services emerged as strong predictors of RHD. These findings reflect the broader social inequalities that continue to influence health outcomes, particularly in resource-limited settings. Addressing these determinants through targeted public health strategies—such as improving healthcare infrastructure in rural areas, enhancing community awareness, and promoting early detection programs—can play a crucial role in reducing the burden of RHD in vulnerable populations.

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