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SPATIAL ANALYSIS OF FOOD
SYSTEMS AND NUTRITIONAL
OUTCOMES IN
DISTRICTS ACROSS INDIA
Submitted By:
Adinath Ghosh
Alisha Rout
Jaydip Biniwale
Shwetank Pandey
Submitted to:
Prof. Vidya Vemireddy
Centre for Management in Agriculture, IIM
Ahmedabad
ePost Graduate Program in Advanced Business Analytics (2020-2021)
Indian Institute of Management Ahmedabad
Background
Women:
● Malnutrition & Anaemia affect over 800 million women worldwide.
● India faces a serious nutritional challenge, having the largest number of anemic women in the world and having to deal
with an increasing number of ailments linked to obesity.(World Health Assembly, 2015-16)
● More than half (51%) of all women of reproductive age in India have anaemia, while more than one in five (22%) of adult
women are overweight. (Global Nutrition Report 2017)
● Between 2005-06 & 2015-16, the prevalence of undernutrition and anaemia reduced by 13 and 5 percentage points
respectively, whereas overnutrition increased by 4 percentage points. (NFHS:2005-06, NFHS:2015-16)
● Globally, overweight and obesity are on the rise, with 31% of adult women overweight and 9% obese (Global Nutrition
Report, 2020)
Children:
● India has the largest number of stunted children in the world and is among the highest of any country outside sub-
Saharan Africa.
● More than half the children under four were underweight and stunted. One in six children was wasted. (NFHS, 1992-
1993)
● Between 2005-06 and 2015-16, India made substantial progress, lowering the share of stunted children by nearly 10
percentage points.
● Rates of overweight and obesity among young children are increasing rapidly.
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)
● High quality and diverse diet suffices both, the energy requirements as well as necessary nutrients, for
healthy growth and well-being (Hawkes & Ruel, 2006)
● 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)
● Low BMI and low dietary intake is highly correlated, and it has consequences of low manual work capacity
and has high susceptibility to 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 a 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 increase in the production of high-calorific foods such as vegetable oils, sweeteners, etc., has
altered quantity and prices, thus influencing access and intake of these foods, sometimes leading to obesity
in children and women because of excess intake of high calorific foods.
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
● 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 bridge this gap, is
quite important.
Geospatial
Analysis
Agricultural
Diversity
Dietary
diversity
Nutrition
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
Problem Solving
Methodology
Hypotheses
At a subnational level
● Dietary Diversity is positively correlated with the nutritional outcomes
● Production Diversity is positively correlated with the nutritional
outcomes
● Production Diversity is positively correlated with the dietary diversity
● There is a significant spatial autocorrelation in the nutritional outcomes
● Higher Cereal/Staple crop production is associated with low dietary
diversity
● Higher Cash crop diversity is associated with Higher Dietary Diversity
Dataset Information
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
Tableau Dashboards

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Capstone final part 1

  • 1. SPATIAL ANALYSIS OF FOOD SYSTEMS AND NUTRITIONAL OUTCOMES IN DISTRICTS ACROSS INDIA Submitted By: Adinath Ghosh Alisha Rout Jaydip Biniwale Shwetank Pandey Submitted to: Prof. Vidya Vemireddy Centre for Management in Agriculture, IIM Ahmedabad ePost Graduate Program in Advanced Business Analytics (2020-2021) Indian Institute of Management Ahmedabad
  • 2. Background Women: ● Malnutrition & Anaemia affect over 800 million women worldwide. ● India faces a serious nutritional challenge, having the largest number of anemic women in the world and having to deal with an increasing number of ailments linked to obesity.(World Health Assembly, 2015-16) ● More than half (51%) of all women of reproductive age in India have anaemia, while more than one in five (22%) of adult women are overweight. (Global Nutrition Report 2017) ● Between 2005-06 & 2015-16, the prevalence of undernutrition and anaemia reduced by 13 and 5 percentage points respectively, whereas overnutrition increased by 4 percentage points. (NFHS:2005-06, NFHS:2015-16) ● Globally, overweight and obesity are on the rise, with 31% of adult women overweight and 9% obese (Global Nutrition Report, 2020) Children: ● India has the largest number of stunted children in the world and is among the highest of any country outside sub- Saharan Africa. ● More than half the children under four were underweight and stunted. One in six children was wasted. (NFHS, 1992- 1993) ● Between 2005-06 and 2015-16, India made substantial progress, lowering the share of stunted children by nearly 10 percentage points. ● Rates of overweight and obesity among young children are increasing rapidly.
  • 3. 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) ● High quality and diverse diet suffices both, the energy requirements as well as necessary nutrients, for healthy growth and well-being (Hawkes & Ruel, 2006) ● 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) ● Low BMI and low dietary intake is highly correlated, and it has consequences of low manual work capacity and has high susceptibility to 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 a 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 increase in the production of high-calorific foods such as vegetable oils, sweeteners, etc., has altered quantity and prices, thus influencing access and intake of these foods, sometimes leading to obesity in children and women because of excess intake of high calorific foods.
  • 4. 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 ● 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 bridge this gap, is quite important. Geospatial Analysis Agricultural Diversity Dietary diversity Nutrition
  • 5. 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. Hypotheses At a subnational level ● Dietary Diversity is positively correlated with the nutritional outcomes ● Production Diversity is positively correlated with the nutritional outcomes ● Production Diversity is positively correlated with the dietary diversity ● There is a significant spatial autocorrelation in the nutritional outcomes ● Higher Cereal/Staple crop production is associated with low dietary diversity ● Higher Cash crop diversity is associated with Higher Dietary Diversity
  • 9. 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