Unleash Your Potential - Namagunga Girls Coding Club
Impacts of aflatoxin contamination on livelihoods of the poor
1. Impacts of aflatoxin contamination
on livelihoods of the poor households
Marites Tiongco, IFPRI
on behalf of the Aflacontrol team
November 30, 2011
International Food Policy Research Institute Uniformed Services University of the Health Sciences
International Center for the Improvement of Maize ACDI/VOCA/Kenya Maize Development Program
and Wheat Kenya Agricultural Research Institute
International Crops Research Institute for the Semi- Institut d’Economie Rurale
Arid Tropics The Eastern Africa Grain Council
University of Pittsburgh
2. Used semi-structured
interviews and focus group
discussions(value chain
approach):
• Role of maize in people’s
livelihoods (diversified
by gender)
• Production, storage,
marketing practices
• Sources of information
regarding inputs,
improving production
practices, disease,
market information Kenya – 6 villages – 3 east; 3 west
• Knowledge about
aflatoxin risk
3. • Conducted household surveys t o 1344 HHs in
Kenya (from 120 sublocations in 6 AEZ)+ 300
HHs from prevalence sample;
• Main objective is to assess the effect of
“aflatoxin contamination” on income and
wealth.
• We take the farm household as the unit of
analysis
• Treat aflatoxin contamination as a negative
externality to the production function
• Measure health costs and production costs
(including aflatoxin contamination)
4. Number of
households
Number of per Number of
sublocation sublocaton household
Lowland Tropics 15 6 90
Dry mid-
altitudes 18 12 217
Dry transitional 18 12 203
Moist
Transitional 30 12 354
Moist Mid-
altitudes 20 12 240
Highlands 20 12 240
total 1344
Sample of 217 HHs from districts
that experienced aflatoxicosis
outbreak in 2004 in Kenya—151 HHs
are in dry transitional and 66 are in
dry mid altitude)
5. All
Dry Dry Mid- Moist Mid- Moist Household
Transitional Altitudes Altitude Transitional High Tropics Low Tropics s
Proportion of
female
household
heads 19% 22% 25% 14% 17% 8% 18%
Household
head's age
(years) 55 52 52 52 52 52 52
Household
head's years
of education 7 6 7 7 7 7 7
Years of
farming
experience 29 28 24 27 26 24 26
6. Low Dry Mid- Moist
Tropics altitudes Dry Moist High Mid- All
Transitional Transitional Tropics Altitude Households
Household size 6 6 6 6 6 8 6
Proportion of
children (<15 years
old) in the
household 39% 41% 49% 37% 41% 48% 42%
(<5 years old) 11% 12% 12% 10% 10% 12% 11%
Annual income (in
1000 KShs) 157,961 98,474 106,982 368,925 188,811 142,727 200,298
Share of income
from maize to total
annual income 20.5% 28.9% 26.2% 9.3% 22.0% 21.7% 16.5%
9. dry mid-altitutes
moist mid-altitudes
lowland tropics
dry transitional
moist transitional
high tropics
0 2 4 6 8
p 50 of hfias
Note: The Household Food Insecurity Index (Coates et al) ranges from 0 -
27 with 0 being the least food insecure and 27 being the most food
insecure. Given the food insecurity situation, the most vulnerable to
demand shocks would be the poorest among the poor HHs.
10. Low Dry Mid- Dry Moist High Moist Mid- All
Tropics altitudes Transitional Transitional Tropics altitudes Households
50% loss in
production +
50% fall in price 17% 21% 18% 12% 13% 16% 14%
50% reduction
in price of maize 11% 14% 12% 8% 8% 11% 10%
70% reduction
in price of maize 16% 20% 17% 11% 12% 15% 14%
50% increase in
price (effect on
net buyers) 32% 63% 54% 30% 46% 37% 30%
Note: Income changes are higher for those HHs
with higher share of income from maize; income
effects on average are small
11. Share of income from maize production to
total household income on average is small
because of diversified income sources
Income changes are higher for those
households with higher share of income from
maize
Income effects due to price changes are
significant relative to maize income
increase in prices affects net buyers more
12. Estimate the productivity loss in terms of
human health effects
Investigate if there are differences in income
effects between high risk and low risk areas
using prevalence data
