The Impact of Orange-Fleshed Sweet Potato

on Vitamin A Deficiency in Uganda:

Gender Dimensions and Asset Implications

Presented by Sylvia Magezi, CIP

Daniel O. Gilligan, IFPRI

ILRI Campus, Nairobi Kenya

05 November 2010

• Compare two interventions (‘treatments’) to see which one is more cost effective

• Model 1: Intensive two-year intervention with initial vine distribution and subsequent trainings

• Model 2: Less intensive; identical to Model 1 in year 1, but little activity or costs in year 2

• Evaluation design: randomized, controlled field experiment with baseline household and nutrition survey in 2007 and an endline surveys in 2009 (n=1,594 households)

• Assigned 84 FGs to Model 1, Model 2 or Control group at random. Makes it possible to claim causal impacts—that differences in outcomes are due to the project

• Survey topics: household socioeconomic and agriculture survey; individual dietary intakes of vitamin A of young children and their mothers

The Impact Evaluation

Key Findings: Adoption I

Impact on OFSP Adoption in 2009

0 20 40 60 80

Control

Model 2

Model 1

%

Cultivated OFSP

Impact: Model -ControlM1: 64 % ***M2: 57 % ***

• It resulted in a 57-64 % point increase in the probability of OFSP adoption in Uganda

• There were no significant differences in these estimates across the two different models

Key Findings: Adoption II

Impact on Proportion OFSP in SP Area, 2007-09

0 20 40 60 80

Control

Model 2

Model 1

%

Project End

Baseline

Impact: ΔM-ΔCM1: 46 %***M2: 41 %***Δ = change

ΔM1= 47.6

ΔM2= 42.9

ΔC= 1.8

• The project increased the share of OFSP in total sweet potato (SP) area by 41 to 46 % points in Uganda (from a base of 0%)

• Differences in impacts were no significant between Model 1 and Model 2

Key Findings: Adoption III

• Past interest and experience growing sweet potato was an important determinant of success in OFSP adoption

• Smaller farmers more likely to adopt: households in lowest tercile of land area were 14 percentage points more likely to adopt than those in the highest tercile

• OFSP diffusion from farmer-to-farmer is essential to sustainability and cost-effectiveness

– half of project farmers shared OFSP vines with other farmers

– each project farmer gave OFSP vines to 1.3 farmers on average

– 80% of these recipient farmers were first-time OFSP growers

– suggests 10,000 primary beneficiaries gave vines to another 13,000 secondary beneficiaries

1%

34%

53%

66%

47%

18%

33%

19%

29%

Control

Model 2

Model 1

Orange Yellow White

110 g/d

100 g/d

118 g/d

Note: Data labels in bars show intake of sweet potato by type as a % of total sweet potato intakes. Total sweet potato intakes (bold) represent mean intakes by all participants. Data are for a cross-sectional group of children 6-35 months of age at the project end.

Sweet Potato Intake (by type) in grams/day for

children 6-35 months at Project End, Uganda

The REU intervention resulted in a significant increase in total vitamin A intakes among young children, older children, and women in Uganda

• The change in vitamin A intakes in the intervention groups was accounted for by the increased intake of vitamin A from OFSP

• OFSP contributed about 44-60% of the total vitamin A intakes

• Impact approximately 30% higher if we only consider adopting households

• Preliminary estimates indicate that project also substantially reduced the prevalence of inadequate vitamin A intakes

Key Findings: Vitamin A Intakes

0 100 200 300 400 500

Control

Model 2

Model 1

Vitamin A μg RAE per day

Project End

Baseline

Change Model 2 = 169

Change Control = -55

Change Model 1 = 137

Impact:Model 1: 192 μg RAE/day* Model 2: 224 μg RAE/day **

Impact estimates are difference-in-difference ‘intent-to-treat’ effects on all REU participants, including adopters and non-adopters.

Significance levels for t-statistics are: * 10% level, ** 5% level, *** 1% level.

The EAR for Vitamin A for children 1-3 years of age is 210 µg RAE/day.

Impact on Vitamin A Intakes of Children

6-35 months, Uganda

Impact on Vitamin A Intakes of Children age 5-7 years, Uganda

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Control

Model 2

Model 1

Vitamin A μg RAE per day

Project End

Baseline

ΔM2= 646

ΔC= 19

ΔM1= 333

Impact: ΔM-ΔCModel 1: 314 μg ** Model 2: 627 μg ***

Impact estimates are difference-in-difference ‘intent-to-treat’ effects on all REU participants, including adopters and non-adopters.

Significance levels for t-statistics are: * 10% level, ** 5% level, *** 1% level.

Impact on Vitamin A Intakes of Women age 18 years and older, Uganda

Impact estimates are difference-in-difference ‘intent-to-treat’ effects on all REU participants, including adopters and non-adopters.

Significance levels for t-statistics are: * 10% level, ** 5% level, *** 1% level.

0 200 400 600 800 1000 1200 1400 1600

Control

Model 2

Model 1

Vitamin A μg RAE per day

Project End

Baseline

ΔM2= 531

ΔC= -117

ΔM1= 678

Impact: ΔM-ΔCModel 1: 795 μg *** Model 2: 648 μg ***

Model 2 is more cost effective than Model 1

• Model 2 was cheaper to implement by almost one-third

• No difference in impact between models on rate of adoption of OFSP, increase in vitamin A intakes or many other key outcomes

• Plans to disseminate OFSP in the future should have an intensive initial phase of vine distribution and limited nutrition messages, followed by light advertising and policies to promote OFSP crop diffusion

Differences in Costs & Impact

• What assets are affected? • nutrition of children and adult women: argue to take

human capital seriously as an asset• access to land, control over durable assets, income

• Next steps• Third round of household survey data collection in 2011• Qualitative and formative research• Research topics:

• Role of social networks in OFSP technology diffusion• how to rely on social networks to reduce cost of diffusion

• Impact of OFSP project on gender distribution of land and durable assets

• Gender dimensions of OFSP adoption• Gender dimensions of nutrition knowledge, risk

preferences, dietary intakes, diffusion

Gender Dimensions & Assets

• How do gender dimensions of control over assets, nutrition knowledge and attitudes toward risk affect adoption rates and intensity?

• gender-disaggregated data on ownership/control of household assets, 2007-09

• truthfully: in 2009, retroactively asked about gender control of assets listed in 2007

• are households in which women have more control over assets pre-project more likely to adopt?

• does female control over assets change due to project

• detailed modules on mother’s and father’s nutrition knowledge in both rounds

• collected information on risk preferences of spousal pairs on subsample of data in 2007 and 2009

Intriguing Issues

• Hypothetical choice between safe and risky crop: Women are somewhat less risk averse than men

Gender, Risk Attitudes and Crop Choice

0.2

.4.6

.81

P(C

hoo

se s

afe

cro

p)

10 20 30 40 50 60 70 80 90 100

Probability of Good Rainfall %

Neutral Male Female

Nm = 94 ; Nf = 100Information on yields only

Men vs Women

Fig. 3. Proportion Choosing Safe Crop

• After being given information that riskier crop is also more healthy, women ignore production risk more than men to gain access to healthy crop

Gender, Risk, Health and Crop Choice

0.2

.4.6

.81

P(C

hoo

se s

afe

cro

p)

10 20 30 40 50 60 70 80 90 100

Probability of Good Rainfall %

Neutral Male Female

Nm = 88 ; Nf = 88Information on yields and health

Men vs Women

Fig. 4. Proportion Choosing Safe Crop when Risky Crop Healthy

• Gender, social networks and agricultural technology diffusion

• Social networks as institutions of exchange: farmer-to-farmer exchange of vines more common than access through markets

• Women played a critical role in diffusion of crop to other households: 75% of recipients of OFSP vines from project households were women

• A detailed on-going social networks analysis will determine the role of gender in shaping how social networks encouraged adoption and diffusion.

• The survey round planned for 2011 will further examine the role of gender in promoting diffusion of OFSP vines to farmers living nearby but outside the original project locations.

Intriguing Issues