Shifting landscape of disability and development in India: Analysis from historical trends to future predictions 2001-2031

TL;DR

This study analyzes state-level disability burdens in India by decomposing Disability-Adjusted Life Years ($DALYs$) into Type A (communicable), Type B (noncommunicable), and Type C (injury) categories and relating them to the Human Development Index ($HDI$). Using decadal data from the 2001 and 2011 Censuses, IHME, and Global Data Lab, the authors fit regression models to trace past trends and forecast values for 2031, finding a strong inverse $HDI$ relationship for communicable diseases, a stagnant or rising burden for noncommunicable diseases, and a moderate decline in injury DALYs; gender overrepresentation in disability persists. The methodology includes predicting 2031 $HDI$ via linear regression on 2001/2011/2021 data and projecting each DALY type with tailored models (Exponential Decay for Type A; Linear for Types B and C), allowing a decoupled view of development–disease dynamics. The results support a shifted public health focus toward chronic disease prevention and gender-inclusive access to care, and they underscore the importance of continued improvements in sanitation and safety infrastructure to sustain health gains. Overall, the paper highlights India’s epidemiological transition and provides state-level projections that can inform targeted policy interventions aimed at reducing disability burden while promoting equitable development.

Abstract

This study delves into the causes and trends of disability-related health burdens across Indian states. Through multiple Disability-Adjusted Life Years (DALY) types (covering communicable diseases, noncommunicable diseases, and injuries), gender disparities, and Human Development Index (HDI) values, these disability trends were evaluated. The data for this study was compiled from censuses, health research organisations, and data centres, among various other sources. We built regression models and used them to analyze trends across past decades and make projections for 2031. Our regression results show a strong inverse relationship between communicable disease DALYs and HDI. In other words, ongoing improvements in development and infrastructure significantly reduced communicable disease DALYs. In contrast, noncommunicable DALYs did not decrease despite rising HDI. And lastly, injury DALYs showed moderate declines with higher HDI, which reflects improvements in healthcare and safety systems. Gender analysis showed male overrepresentation among people with disabilities. These results from our study support that there is a need to shift public health focus toward chronic diseases and address gender disparities in disability outcomes.

Figures (12)

• Figure 1: Comparison between the HDI and the DALY per 100,000 for communicable diseases in various Indian states in the years 2001 and 2011
• Figure 2: Comparison between the HDI and the DALY per 100,000 for noncommunicable diseases in various Indian states in the years 2001 and 2011
• Figure 3: Comparison between the HDI and the DALY per 100,000 for injuries in various Indian states in the years 2001 and 2011
• Figure 4: Scatterplot comparing the ratio of disabled males to females (y-axis) against the overall male-to-female population ratio (x-axis) for 2001. The line indicates a 1:1 correspondence
• Figure 5: Scatterplot comparing the ratio of disabled males to females (y-axis) against the overall male-to-female population ratio (x-axis) for 2011. The line indicates a 1:1 correspondence