Abstract / Summary
Background/Objectives: Beta-thalassemia and sickle cell disorders are among the most common inherited hemoglobin disorders affecting tribal populations in India, with marked ethnic and geographic heterogeneity. Although exploratory multivariate approaches have been used, only limited evidence is available regarding the distribution and clustering patterns of these disorders among Scheduled Tribe populations in Tamil Nadu. This study aimed to examine the distribution and population-specific clustering of beta-thalassemia- and sickle cell-related disorders among hematologically confirmed cases of the scheduled tribes from the selected districts. Methods: A cross-sectional analytical study was conducted among the Scheduled Tribe populations in the selected districts of Tamil Nadu. Confirmed cases of hemoglobin disorders were identified through complete blood count, peripheral smear examination, reticulocyte count, and high-performance liquid chromatography (HPLC). A total of 89 confirmed cases were included in the exploratory analysis. Disease forms were categorised as beta (β)-thalassemia related disorders and sickle cell- related disorders, including sickle cell β-thalassemia. Chi-square tests were performed to assess associations with socio-demographic and environmental variables. Correspondence analysis and multidimensional scaling were applied to identify clustering patterns and structural relationships. Results: Of the 89 confirmed cases, 48 (53.9%) had β-thalassemia and related disorders (predominantly beta-thalassemia minor), while 41 (46.1%) had sickle cell-related and combined forms (predominantly sickle cell trait). There were significant associations between disease forms and tribal affiliation (p < 0.001), drinking water source (p < 0.001), and altitude of residence (p = 0.003). Correspondence analysis demonstrated distinct clustering of β-thalassemia- and sickle cell-related disorders across tribes and districts. Multidimensional scaling further indicated that population structure and geographic context were more strongly associated with disease distribution than individual demographic variables. Conclusions: Hemoglobinopathy disease forms among Scheduled Tribes in the selected districts of Tamil Nadu showed clear eco-geographical and population-specific clustering patterns. The combination of correspondence analysis and multidimensional scaling revealed latent clustering patterns beyond those identified using traditional statistical analyses, emphasizing the intricate relationship between mutation distribution, environment, and population structure. These results highlight the significance of tribe-specific, equity-focused screening and genetic counselling programmes. To close diagnostic gaps and improve precision-based approaches in underserved populations, public health interventions must be tailored to intra-tribal heterogeneity. These findings may help inform future studies on targeted, population-specific screening and decentralised diagnostic strategies to reduce health inequities in the selected Scheduled Tribe populations.