Anaemia severely impacts physical and mental abilities, raises health risks, and diminishes the quality of life and work capacity. It is a leading cause of adverse pregnancy outcomes and maternal mortality, especially in developing nations like India, where recent data on anaemia from National Family and Health Survey (NFHS-4) (2015–16) and NFHS-5 (2019–21) indicate a tremendous rise. Anaemia is a marker of poor nutrition and health, and socio-economic factors such as gender norms, race, income, and living conditions influence its impact. As a result, there are disparities in how anaemia affects different segments of society. However, existing research on health inequity and anaemia often employs a single-axis analytical framework of social power. These studies operate under the assumption that gender, economic class, ethnicity, and caste are inherently distinct and mutually exclusive categories and fail to provide a comprehensive understanding of anaemia prevalence. Therefore, the study has adopted the theoretical framework of intersectionality and analysed the NFHS-5 (2019–21) data using bivariate cross-tabulations and binary logistic regression models to understand how gender, class, caste, and place of residence are associated with the prevalence of anaemia. The results suggest that the women of Scheduled Tribes (ST) and Scheduled Castes (SC) share a disproportionate burden of anaemia. This study confirms that economic class and gender, geographical location, level of education, and body mass index significantly determine the prevalence of anaemia. The ST and SC women who are economically marginalised and reside in rural areas with high levels of poverty, exclusion, and poor nutritional status have a higher prevalence of anaemia than other population groups. Thus, the study suggests that intersections of multiple factors such as caste, class, gender, and place of residence significantly determine ‘who is anaemic in India’.