Possible topics for discussion:
There is a fatigue setting in with Nutrition data flying across this country at regular intervals. People have even become immune to it. Instead of reflecting about the plight of kids subsisting on rice with chilli and onion paste, and more rice with more chilli, or going to bed hungry, the excitement is in the possibility of a “better” analysis. The unflattering data is often used to demand accountability from the Government of the day, followed by denial, or a reluctant concession when 5 kg of grain was distributed per person per month during the lockdown…. In the name of food security. Figures representing Weights, heights, wasting, Anemia, and recently micronutrient deficiencies have been flogged to extract maximum mileage. Maybe we should pause and reflect on these figures in children <5years, such as 35%, stunted, and 33%, underweight and 17% wasted and 40- 60% Anaemic. My presentation will try to unpack the meanings of these indices, and raise a discussion to help rethink our priorities.
Do we – the English-speaking, mainly dominant caste, researcher community – have a detailed and nuanced understanding of the diverse food habits of communities across India? If yes, have these perspectives been captured in quantitative form? Drawing from research on food systems and my field experiences, I will attempt to link gaps in data to our incomplete understanding of food and nutrition, and discuss possible approaches (with or without computer science techniques) that could bridge these gaps.
Poor nutritional status is an issue of serious concern in India, especially since the country has experienced significant economic growth over the past decades. The social transformation led by growth in income influences both the composition of food and the quality of diet consumed. Against this backdrop of changing lifestyles and the rise in obesity and Non-Communicable Diseases, my talk will focus on changes in the quality of diet and the critical socio-economic correlates of this quality during 1983-2012. Using three rounds of the National Sample Survey data on household-level food consumption, we construct a diet quality index consisting of twelve macro and micronutrients, including carbohydrates, proteins, fats, fibre, calcium, phosphorus, iron, carotene, thiamine, riboflavin, niacin, and Vitamin C and use an adjusted measure of the nutritional intake of a household to account for nutritional intake emanating from increasing food consumption outside the home. We find that in relation to the Recommended Daily Allowance, fat consumption increased over time while protein and energy consumption decreased. The average diet quality index of macro and micronutrients improved in the rural sector while it deteriorated in the urban sector. Caste and religion are significant correlates of the diet quality index. It is suggested that the Indian Government may play a more proactive role in implementing coherent national policies in trade, food, and agriculture for protecting public health by promoting the demand for a healthy diet among consumers. In the end, I will highlight some data gaps and possible applications of ML in contributing to data analysis.
Cooking forms the core of our cultural identity other than being the basis of nutrition and health. The increasing availability of culinary data and the advent of computational methods for their scrutiny are dramatically changing the artistic outlook towards gastronomy. Starting with a seemingly simple question, ‘Why do we eat what we eat?’ data-driven research conducted in our lab has led to interesting explorations of traditional recipes, their flavor composition, and health associations. Our investigations have revealed ‘culinary fingerprints’ of regional cuisines across the world, starting with the case study of Indian cuisine. Application of data-driven strategies for investigating the gastronomic data has opened up exciting avenues giving rise to an all-new field of ‘Computational Gastronomy’. This emerging interdisciplinary science asks questions of culinary origin to seek their answers via the compilation of culinary data and their analysis using methods of statistics, computer science, and artificial intelligence. Along with complementary experimental studies, these endeavors have the potential to transform the food landscape by effectively leveraging data-driven food innovations for better health and nutrition.
Prof. Veena Shatrugna is a scientist at National Institute of Nutrition (Indian Council of Medical Research) and has many publications related to nutrition and health.
I have been volunteering and working with grassroots organizations and networks since 2002, and have designed and supported interventions in health, food and agriculture in Uttar Pradesh and Karnataka. I have researched topics such as health systems, obstetric care in urban areas, disease prevalence and community-based health interventions. During 2017-19, I was part of a multi-disciplinary team researching farming and food transitions in western Avadh, UP. Currently, we are developing an online portal to document this work.
Sourabh Paul is as assistant professor in economics at IIT Delhi. He received PhD in economics from the University of British Columbia, Vancouver and MS in Quantitative Economics from Indian Statistical Institute, Kolkata. Sourabh’s work broadly focuses on how some recent changes in the Indian economy have affected the most vulnerable sections of Indian society. His research encompasses issues such as castes and labour mobility, distributional aspects of trade policy, health, nutrition, gender, among others.
Dr. Ganesh Bagler is known for the pioneering research in ‘Computational Gastronomy,’ the emerging data science that blends food with artificial intelligence. Trailblazing research from his lab has established foundations of this niche area that deals with food, flavors, nutrition, and health. Dr. Bagler has an audacious dream of transforming the global food landscape through data-driven innovations.