1) The document analyzes the spatial relationship between food systems, dietary diversity, and nutritional outcomes in districts across India. 2) It finds strong positive spatial clustering for various measures of dietary diversity and nutrition levels (anemia, stunting, etc.), indicating geographic patterns. 3) Correlation analysis found positive associations between dietary diversity and animal protein consumption, but negative correlations between dietary diversity and measures of undernutrition among women and children.

1. SPATIAL ANALYSIS
OF FOOD SYSTEMS
AND NUTRITIONAL
OUTCOMES IN
DISTRICTS ACROSS
INDIA

2. Submitted By- Vyom Bhatiya Fan Club
Alisha Adinath Jaydip Shwetank
Vyom Bhatiya’s profile

3. Background
● India has the largest number of stunted children in the world,
and among the highest of any country outside sub-Saharan
Africa. More than half the children under four were
underweight and stunted. One in every six children was
wasted.(NFHS, 1992-1993)
● However, between NFHS 2005-06 and 2015-16, India made
substantial progress, lowering the share of stunted children by
nearly 10 percentage points.
● India ranks 94 among 107 countries on the basis of total
undernourishment of the population, child stunting, wasting
and child mortality. (Global Hunger Index, 2020)
● Rates of overweight and obesity among young children are
increasing rapidly

4. What does the literature say ?
● Nutrition is still frequently associated with calorie consumption or food expenditures, factoring out diversity in dietary intake and
micronutrient status measurements. (Kadiyala, Harris, Headey, Yosef, & Gillespie, 2014)
● A high quality and diverse diet suffices both, the energy requirements as well as necessary nutrients, for healthy growth and
well-being (Hawkes & Ruel, 2006)
● Various studies provide evidence that suggests individuals consuming more diverse diets are thought to be more likely to meet
their nutrient needs (Arimond & Ruel, 2004).
● Ensuring year-round availability & intake of micronutrient-rich foods in poor households by introducing dietary diversification,
proved to decrease Anaemia prevalence and reduction in night blindness among children in program households. (Talukder, et
al., 2010).
● It has been observed that low BMI and low dietary intake is highly correlated, and it has consequences of low manual work
capacity and has highly susceptible for infection ()
● At the household level, lower socioeconomic status and lower dietary diversity can be linked with obesity (Aiyar, Rahman, &
Pingali, 2021; Gupta, Sundar, & Pingali, 2020).
● Health considerations play minimal role in production decisions made by farmers or policy decisions made by agricultural
ministries (Hawkes & Ruel, 2006)
● Agricultural outputs are also linked with overnutrition and diet-related chronic diseases. Significant increases in the production
of vegetable oils, sweeteners, and other foods have altered quantity and prices, thus influencing access to these foods,
sometimes leading to obesity in children and women because of excess intake of high calorific foods.

5. What’s missing so far?
● Literature establishing household-level
relationship between dietary diversity,
agricultural diversity and nutritional outcomes is
available in abundance, but an analysis at a
subnational level granularity is scarce
● Also, the literature doesn’t talk much about the
geospatial patterns and relationships between
agricultural patterns, diet diversity and nutritional
outcomes.
● Hence a study which helps plug this gap, is quite
important.
Geospatial
Analysis
Agricultural
diversity
Dietary
diversity
Nutrition

6. Objectives
The primary objective is to examine the geospatial relationship between food systems and nutritional
outcomes at district level in India, through spatial analysis
1. Whether agricultural diversification within a district increases dietary diversification
2. Is there a significant relationship between nutritional levels of women and children, and agricultural practices prevalent, at the
district level?
3. Are there any significant spatial patterns when it comes to nutritional levels and dietary diversity

7. Problem Solving Methodology

8. Hypothesis

9. Dataset
Information

10. Dataset Processing workflow
Crop Yield
Animal Husbandry
Source: 20th Livestock Census
(2019)
Source: Cost of cultivation Scheme
(2015-2016)
Food Systems Data
Yield, Productivity & Cost
Related Calculations
Aggregation of data
at district level
Geospatial Data Prep
Correlation Analysis
Spatial Clustering
Analysis
Nutrition & Diet Data
Women’s Nutrition
Data
Children’s Nutrition
Data
GPS Locations
of Surveys
Source: NHS 4
Dashboard

11. Tableau Dashboards

13. Spatial Clustering Analysis

14. Variables Moran’s I P-value
Avg Dietary Diversity 0.71 0.01
Average Dietary Diversity - 7 0.75 0.01
Median Dietary Diversity - 7 0.68 0.01
Average Dietary Diversity above 3 0.74 0.01
Anemia (Women %) 0.6 0.01
Underweight (Women %) 0.7 0.01
Obese (Women %) 0.6 0.01
Stunted (Children %) 0.62 0.01
Underweight (Children %) 0.73 0.01
Wasted (Children %) 0.48 0.01
Obese (Children %) 0.29 0.01
Overview

15. Average Dietary Diversity

16. Average Dietary Diversity - 7

17. Median Dietary Diversity - 7

18. Average Dietary Diversity above 3

19. Wasted (% Children)

20. Underweight (% Women)

21. Anemia (% Women)

22. Obesity (% Women)

23. Stunting (% Children)

24. Underweight (% Children)

25. Correlation Analysis

26. ● Strong positive correlation is observed among
the consumers of animal-protein sources viz.
Eggs, Fish, Poultry, etc.
● Positive correlation is observed between
average dietary diversity and percentage of
animal-protein consumers.
● Very little association between percentage of
obese women and children, and average
dietary diversity, implying that they’re not
correlated.
● Percentage of anemic,underweight women
and average dietary diversity has a strong
negative correlation which implies that the
prevalence of anemia in women increases with
decrease in dietary diversity
● Similarly, percentage of stunted, underweight
and wasted children has a strong negative
correlation with dietary diversity
● Strong negative correlation between daily or
weekly fruit consumption and the percentage
of underweight women and children.
Nutrition vs Diet Diversity

27. Correlation between Production Diversity and Dietary Diversity
● Average dietary diversity is negatively
correlated with
➸ Type of crops produced in the
district
➸ Number of distinct crops
produced in the district
➸ Type of crops produced per
cultivator
➸ Number of distinct crops
produced per cultivator
● All of the nutrition related indicators are
negatively correlated with the
production diversity indicators, but the
strength of correlation is mild

28. Conclusion

29. Future Scope

30. Thank You

31. Appendix A

32. Appendix B

33. Appendix C