Barriers beyond illness: social exclusion and healthcare disparities in Jhargram, West Bengal, India

Equitable healthcare mandated the establishment of a robust and inclusive healthcare system; however, developing nations often lacked such mechanisms. This study provided a snapshot of the Social Determinants of Health (SDoH) associated with health exclusions and the marginalization of Dalits and Adivasis in the Jhargram district of West Bengal. A cross-sectional survey was conducted across 450 households, interviewing 1,925 consenting adults between February and April 2021. Cochrane’s formula was applied to determine the sample size. The study used a mixed method approach. While the quantitative arm sought to identify and quantify the social exclusion and discrimination faced by the marginalized groups, which act as barriers in access to healthcare services, the qualitative arm then tried to unpack the mechanisms of exclusion. The qualitative findings helped to supplement the quantitative results. The Social Exclusion Index (SEI) was utilised as a novel analytical framework to identify and correlate discriminatory constructs. The sample showed equal caste and gender representation of Dalits and Adivasis, most residing in villages and practicing Hinduism. The majority had only primary education, were married, and one-third were aged 18–35, typically in larger families. Agriculture was the main occupation. Most households lived in kaccha dwellings with access to safe water, though open defecation was widespread. Solid fuel use for cooking created smoke-related health risks. Nearly 40% of families lived below the poverty line and faced unfair wages. Mortality was higher among Adivasis, largely due to geriatric conditions. Contributing factors included poor living standards, inadequate healthcare, restrictive norms, indigenous practices, and extreme poverty. Healthcare options were limited to private clinics (38.3%) and public health centers (44.5%), the latter often understaffed, distant, and poorly managed. Awareness of state health schemes was low. Statistical analyses validated the SEI (Cronbach’s alpha = 0.93), identifying unmet medical needs and illiteracy as the strongest mortality predictors. The SEI proved to be a novel and robust tool for socioeconomic health surveys, effectively integrating qualitative and quantitative dimensions to capture nuanced relationships. Illiteracy, poverty, and unmet medical needs were the dominant determinants of high mortality, particularly among Adivasis. Knowledge about health programs and insurance schemes are limited among these marginalised groups. The findings underscored the urgent need for inclusive and targeted health policies by the government to achieve equitable healthcare.