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 QaimAgricultural 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 quantityproduced

Food consumption/nutrition

Food qualityproduced

Food diversityproduced

Householdincome

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

Inde

x

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)

Department of Agricultural Economics 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

Den

sity

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 model s)


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 quantityproduced

Food consumption/nutrition

Food qualityproduced

Food diversityproduced

Householdincome

Health

Intra-household distribution

Department of Agricultural Economics and Rural Development EPSO Conference 2008 17

Assessing nutrition related health effectsMalnutrition (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

DALYsLost


Potential health benefits of biofortification(Ex ante analysis for India)


Wheat/rice(iron)

Wheat/rice(zinc)

Golden Rice (vitamin A)

DALYs lost w/obiofortification

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.


Conclusion1. 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

Technology

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