Home to one-quarter of humanity—one-fifth of whom are youth—South Asia has the world’s largest concentration of poverty and malnutrition (1–3). Despite producing one-quarter of the world’s consumed food, the region’s agrifood systems face formidable challenges in producing an adequate and affordable supply of the diverse foods needed for sustainable healthy diets (4,5). Unhealthy food consumption is rising, and farming systems are threatened by unsustainable groundwater withdrawal due to poorly developed food and energy policies. In addition, South Asia’s farmers are both contributors and victims of climate change and extreme weather, which contributes to rural out-migration—particularly of youth—resulting in rising labor scarcity and increased production costs. TAFSSA (Transforming Agrifood Systems in South Asia), a CGIAR Regional Integrated Initiative, aims to address these challenges by delivering actionable evidence and scalable innovations across these regions through a coordinated program of research and engagement from farmer to consumer. One of the roadblocks to addressing these challenges is the lack of credible and high-resolution data on food systems in the region. The TAFSSA food systems assessment aims to provide a reliable, accessible and integrated evidence base that links farm production, market access, dietary patterns, climate risk responses, and natural resource management in Bangladesh, India, Nepal and Pakistan. It is intended to be a multi-year assessment.

The rising consumption of ultra-processed foods (UPFs) and paid food away from home (FAFH) is a growing concern for developing countries like India, which face the double burden of persistent malnutrition and increasing obesity. This paper examines the trends and drivers of UPF and paid meal consumption in rural and urban India from 2014 to 2019. Using high-frequency household consumption survey data, we estimate the expenditure elasticity of these food categories. Our results show a significant increase in the consumption of UPFs and paid meals over the study period. The expenditure elasticity of both UPF and FAFH exceeds 1 on average, indicating that they are highly responsive to income growth. Notably, poorer and urban households display higher elasticities compared to wealthier and rural households. Oaxaca-Blinder decomposition reveals that rising incomes and evolving dietary preferences contribute to the increase in UPF and paid meal consumption. These findings underscore the need for targeted interventions to promote healthier food choices, especially among lower-income groups, as India's economy continues to grow.

India has recorded high levels of unemployment and low labor force participation rates in recent years even before the onset of the COVID-19 pandemic and the lockdown. How does an episode of unemployment or loss of income affect household consumption expenditure is an important question for designing effective safety nets. We use data on household-specific episodes of job loss and decline in income, from an earlier year (March-April 2019) to estimate the household response to employment shocks. We apply diff-in-diff and quantile regressions to a high-frequency panel data from a nationally representative survey of 1,75,000 households to estimate the impact of a job loss (and change in income) on household consumption expenditure—for urban and rural households, and households across different expenditure levels. We find that loss of employment of an earning member leads to a significant immediate decline in household consumption expenditure. The decline is much larger for urban households and households in the lowest and the highest deciles of monthly per capita. Durable expenses go down the most. Expenditure on health and education also goes down significantly and there is evidence of adjustments in discretionary expenses too, especially for urban households. For households with only one earning member, borrowing does not increase after the job loss, suggesting credit constraints. Government cash transfers help rural households, as the beneficiaries show a smaller reduction in consumption expenditure after the shock. Our findings highlight the high vulnerability of urban households to economic shocks and can inform the design and targeting of income support and other safety-net programs in India and other developing countries.