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Madhya Pradesh, the central state of India, has a larger share of the population depending on the agricultural sector, mainly belonging to tribal groups and are largely marginal and small landholders. Though the sector performed a double-digit growth rate in recent years, this is skewed towards very few districts, whereas others remain neglected. These increasing disparities may lead to increased vulnerability to climate change in the backward districts of this sector. This study assessed the spatial and temporal vulnerability of the sector to climate change with the agricultural vulnerability index prepared using the IPCC approach at the district level for 5 decades (1970s–2010s). Hotspots of agricultural vulnerability where targeted policy interventions are required were located. Through spatial autocorrelation techniques, we identified whether the clustering of agricultural vulnerability exists and detected changes over the decades. This study has wide applications for the agricultural sector in Madhya Pradesh and other Indian states, which possess similar agricultural characteristics.

Climate change disproportionately impacts different sections of a population depending on their inherent vulnerability characterized by access to basic facilities, assets and other entitlements, place of residence, and demographic characteristics. Indigenous communities are more vulnerable than other social groups in a population due to their natural resource dependent livelihood and isolation from the mainstream population. Madhya Pradesh, the tribal state of India, has a higher share of marginalized populations (Scheduled Castes (SC) and Scheduled Tribes (ST)) and is characterized by higher disparities among the social groups. By constructing indices for socioeconomic, infrastructural and agricultural vulnerability for social groups and climate indices at the district level, this study attempted to assess differences in the vulnerability of each social group to climate change in districts of Madhya Pradesh. The study showed that SC and ST possess significantly high vulnerability to climate change than Non SC/ST due to significant differences in socioeconomic, infrastructural and agricultural vulnerability. The districts where each social group was most vulnerable differed, but the reasons for higher vulnerability remained the same across the groups. The results contribute to vulnerability reduction efforts of the state by identifying the districts most vulnerable to climate change for each social group and most vulnerable social groups in the district as well as at the state level. This study also provides wide applications in climate change vulnerability assessment of other Indian states and developing countries with similar socioeconomic and demographic characteristics.

The public health sector of India suffers from higher inequalities despite interventions introduced from time to time. The groups suffering the most are the populations in Empowered Action Group (EAG) states, with limited access to health interventions and higher mortality and morbidity rates. Madhya Pradesh, an EAG state, is infamous for its low-level health status due to disparities in access to health care. This study aimed to understand how access to health care differs spatially in the state and identify the hotspots for urgent attention. Indicators related to health were selected from the association of Sustainable Development Goal 3 (Good Health and Wellbeing) with other SDGs, especially from 1 to 10. Principal Component Analysis was used to construct two indices, viz. Health Status Index (HSI) and Health Intervention Index (HII) out of the indicators. The results showed that the spatial distribution of HSI and HII possess a positive Moran’s I, indicating spatial clustering of these indices in the state. The bivariate association between the two indices is positive but close to zero, indicating a lower association between coverage of health indicators and health status among districts of Madhya Pradesh. These results can provide wide applications while targeting health interventions at the district level.