Matin Qaim, University of Gottingen "How to Evaluate Nutrition and Health Impacts of Agricultural Innovations"

How to evaluate nutrition and
health impacts of agricultural
innovations
Matin Qaim
Agricultural Economics and Rural Development
CGIAR Science Forum, 23-25 September 2013, Bonn
“Nutrition and Health Outcomes: Targets for Agricultural Research”

Department of Agricultural Economics
and Rural Development
Introduction…
Many undernourished people depend on agriculture as a
source of food, income, and employment
Agriculture is an important entry point to improve these
people’s nutrition and health
Agricultural innovations can have important impacts on
nutrition and health, but relatively little is known about the
types and magnitudes of these effects at the micro level
Impact studies primarily look at productivity; some look at
income, very few explicitly at nutrition and health
(surprising in a CGIAR context)
PAS Study Week 2009 2

…Introduction
Can we always conclude that higher yields lead to
better nutrition? What exactly and how much?
Future impact analysis of agricultural innovations
should look at nutrition and health outcomes
more explicitly.
How can we do this? Are standard approaches
available?
No, this is the focus of this presentation.
Intention not to provide blueprint, but discuss possible
approaches and issues that need to be considered.

Overview
Conceptual framework of impact pathways
Metrics of nutrition
Metrics of health
Design of impact studies
Selected empirical examples

Conceptual framework
(impact pathways for farm households)
5
Agricultural innovation
Food quantity
produced
Food consumption/
nutrition
Food quality
produced
Food diversity
produced
Household
income
Health
Intra-household
distribution

Metrics of nutrition
1. Subjective food security assessment
2. Food consumption based measures
3. Anthropometric measures
4. Clinical assessment (e.g., blood)
If we want to evaluate nutrition
impacts of agricultural innovations,
we need to measure nutrition.

Criteria to choose most suitable
nutrition metric
Type of agricultural innovation
Expected impact pathways
Target group (children, women, or more general)
Intended sample size and regional coverage
Financial and human resources available
Etc.

Metrics of health
Incidence rates of adverse health outcomes
(diseases and premature deaths)
How to measure health outcomes?
For better comparison and economic evaluation:
Cost-of-illness (value of lost work days, physician
treatment, travel cost to physician etc.)
Disability-adjusted life years (DALYs) lost

Design of impact studies
Basic idea:
Collect data on nutrition/health variables for adopters and
non-adopters of innovation and compare.
Attribution problem:
Are observed differences only due to the innovation?
Possible solutions:
Assign innovation randomly (RCT)
Differencing techniques with panel data
Instrumental variable (IV) approaches or propensity
score matching (PSM), possible with cross-section data

Selected empirical examples
Tissue culture (TC) bananas in Kenya
In Kenya, banana is grown for home
consumption and local markets
TC is a technology where clean
planting material produced in the lab
is used instead of suckers from old
plantations
Together with improved management
techniques, TC technology can
increase banana yields significantly
We collected data from 385 farms in 2009 to assess
impacts on household income and food security

Impacts of TC bananas in Kenya
11
TC adoption by social network was used as instrument.
Other covariates not shown for brevity. *** p<0.01.
Source: Kabunga, Dubois, Qaim (2013)
-0,2
-0,1
0
0,1
0,2
0,3
Non-adopters Adopters
Index
Food insecurity (FI)
Severe food insecurity
(SFI)
We find large positive income effects of TC adoption
Food security was captured with HFIAS tool (9 questions)
Factor analysis used to construct two food insecurity indices
Food insecurity for TC adopters and
non-adopters
FI index SFI index
TC
adoption
-0.437*** -0.316***
Net treatment effects of TC
adoption on food insecurity
(IV models)

and Rural Development 12
Host plant resistance to major
cotton pest (bollworms).
In India, cotton is grown by
smallholder farmers.
Bt cotton was commercialized in
2002; by 2012, over 7 million
farmers had adopted (93%)
Bt cotton in India
We have collected panel data of over 500 farmers in four
rounds between 2002 and 2008 (in four states).
Panel fixed effects estimates show that Bt adoption entails:
Chemical pesticide reductions of 40-50%
Yield increases of 20-30%
Profit increases of 50%

Nutrition effects of Bt cotton adoption
Household food consumption data through 30-day recall
Converted to calorie consumption per adult equivalent (AE)
0
0,0001
0,0002
0,0003
0,0004
0,0005
0,0006
0,0007
500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
Density
kcal per AE and day
Non-adopters of Bt
Adopters of Bt
Source: Qaim and
Kouser (2013)
Calorie consumption of Bt adopters and non-
adopters

Nutrition effects of Bt cotton adoption
Treatment effects per AE (fixed-effects panel models)
Calories
(kcal)
Bt (per ha) 73.71***
Bt (average
household)
145.19***
Increase +5.1%
Non-
staple
calories
23.17**
45.70**
+7.2%
Iron
(mg)
Zinc
(mg)
Vitamin A
(µµµµg)
0.57*** 0.30*** 15.54**
1.12*** 0.59*** 30.61**
+4.6% +4.5% +9.6%
*** p<0.01; ** p<0.05. Source: Qaim and Kouser (2013).
Simulation analysis with these results suggests that Bt cotton
has reduced food insecurity among Indian cotton growers by
15-20%.

Health effects of Bt cotton adoption
We have analyzed health effects of Bt
adoption related to reduced exposure of
farmers to chemical pesticides.
Manual application of toxic pesticides
regularly leads to poisoning symptoms
(skin, eye, breathing, stomach etc.).
Poisoning incidence
Bt (per ha) -0.26**
Treatment effect of Bt adoption
** p<0.05. Poisson fixed effects panel regression. Other covariates not shown for
space reasons. Source: Kouser and Qaim (2011).
For total area under Bt cotton in India (per year):
2.6 million fewer cases of pesticide poisoning
US$ 15 million lower cost-of-illness

Impact pathways
16
Agricultural innovation
Food quantity
produced
Food consumption/
nutrition
Food quality
produced
Food diversity
produced
Household
income
Health
Intra-household
distribution

and Rural Development EPSO Conference 2008 17
Assessing nutrition related health effects
Malnutrition (nutrient deficiencies) entails adverse health
outcomes, causing a health burden for individuals & society.
The DALYs approach (disability-adjusted life years)
can measure health burden by combining mortality and morbidity
within a single index (Murray/Lopez 1996, Stein/Qaim 2007):
DALYsLost =
Years lost to mortality
+ Years with disability
x Disability weight
Without
innovation
With
innovation
Health benefit of
innovation
DALYs
Lost

Potential health benefits of biofortification
(Ex ante analysis for India)
Wheat/rice
(iron)
Wheat/rice
(zinc)
Golden Rice
(vitamin A)
DALYs lost w/o
biofortification
4.0 million 2.8 million 2.3 million
DALYs saved
through
biofortification
2.3 million 1.6 million 1.4 million
Reduction in
health burden
58% 55% 59%
Internal rate of
return
168% 153% 77%
Source: Qaim, Stein, Meenakshi (2007).
Results refer to “optimistic” scenario assumptions.

Conclusion
1. Most studies on impacts of agricultural innovations
only look at productivity and/or income.
2. Nutrition and health effects should be analyzed more
explicitly in future impact studies.
3. This is important to better understand what works.
4. Interesting methodological approaches are available,
but more work is required:
What type of data and metrics for what questions?
Issues of intra-household distribution and gender
Efficient survey design
Etc.

Backup slides

Subjective food security assessment
Food security self-assessment
questions covering certain recall
period (e.g., HFIAS tool)
Construct subjective food
security indices
Advantages
Relatively easy to collect with standardized questionnaire
Various aspects of diet quantity and quality captured
Disadvantages
How reliable and comparable are subjective measures?
Intra-household distribution cannot be captured

Food consumption based measures
Collect detailed data on food consumption for specified
recall period (e.g. 24 hours, 7 days, 30 days)
Convert to calorie and nutrient consumption per capita
Advantages
Relatively easy to collect as part of living standard
module in survey questionnaire
Diet quantity, quality, and diversity can be assessed
Disadvantages
Measurement error (e.g., food waste)
Intra-household food distribution difficult to capture

Anthropometric measures
Data on age, weight, height etc. from
individual household members
Calculate Z-scores (or BMI)
Advantages
More precise measures of nutrition status
Individual based (no distribution assumptions required)
Disadvantages
Not easy to cover all household members in one visit
(potential bias if only those at home covered)
Diet quantity, quality, and diversity cannot be assessed
More difficult to control for confounding factors

Matin Qaim, University of Gottingen "How to Evaluate Nutrition and Health Impacts of Agricultural Innovations"

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Matin Qaim, University of Gottingen "How to Evaluate Nutrition and Health Impacts of Agricultural Innovations"